Metabolome and Transcriptome Analysis of Flavor Components and Flavonoid Biosynthesis in Fig Fruit (Ficus Carica L.) After Bagging

doi:10.21203/rs.3.rs-81494/v1

Download PDF

Research article

Metabolome and Transcriptome Analysis of Flavor Components and Flavonoid Biosynthesis in Fig Fruit (Ficus Carica L.) After Bagging

https://doi.org/10.21203/rs.3.rs-81494/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background: Bagging can improve the appearance of fruits and increase the food safety and commodification, it also has effects on intrinsic quality of the fruits, which was commonly reported negative changes. Fig can be regarded as a new model fruit with its relatively small genome size and long fruit season.

Results: In this study, widely targeted metabolomics based on HPLC MS/MS and RNA-seq of the fruit tissue of the ‘Zibao’ fig before and after bagging were analyzed to reveal the metabolites changes of the edible part of figs and the underneath gene expression network changes. A total of 771 metabolites were identified in the metabolome analysis using fig female flower tissue. Of these, 88 metabolites (including one carbohydrate, eight organic acids, seven amino acids, and two vitamins) showed significant differences in fruit tissue before and after bagging. Changes in 16 structural genes, 13 MYB transcription factors, and endogenous hormone (ABA, IAA, and GA) metabolism and signal transduction-related genes in the biosynthesis pathway of flavonoids after bagging were analyzed by transcriptome analysis. KEGG enrichment analysis also determined significant differences in flavonoid biosynthesis pathways in female flower tissue before and after bagging.

Conclusions: This work provided comprehensive information on the composition and abundance of metabolites in the female flower tissue of fig. The results showed that the differences in flavor components of the fruit before and after bagging could be explained by changes in the composition and abundance of carbohydrates, organic acids, amino acids, and phenolic compounds. This study provides new insights into the effects of bagging on changes in the intrinsic and appearance quality of fruit.

Plant Physiology and Morphology

Plant Molecular Biology and Genetics

Fig

Ficus carica

RNA-seq

Metabolites

Bagging

Female flower tissues

Flavonoids

Flavor substance

Fig (Ficus carica L.) belongs to the Ficus genus of the Moraceae family and is the world's oldest cultivated fruit tree. It originated in the West Asia area and was introduced to China along the Silk Road thousands of years ago. Fig fruit contains a variety of healthy and beneficial bioactive ingredients, in addition to providing sugar and energy, fig fruit is also rich in dietary fiber and is considered a good source of minerals [1], sterols [2], carotenoids [3], anthocyanins [4], and polyphenols [5]. The development of fig fruit demonstrates a typical double-S-shaped curve, with two rapid growth phases (phases I and III) and one slow growth phase (phase II) between them. Fig is a female flower hermaphrodite plant with diverse fruit color, the edible part is the compound fruit formed from the enlarged inflorescence and receptacle of female flowers, botanically, it is a false fruit termed ‘Syconium’. The coloration of fig pericarp and female flower tissue shows obvious space-time and expression differences in that the coloration of female flower tissue initiates very early, while the accumulation of anthocyanin in the pericarp is significantly later. The process of anthocyanin accumulation in the pericarp is very fast compared with that of female flower tissue, and the concentration is also significantly higher. Fruit color is an important index to evaluate the fresh food quality and commodity value of fruit because a bright and attractive fruit color is one of the most important factors affecting the choice of growers and consumers [7, 8].

Anthocyanins, water-soluble flavonoids, are important secondary metabolites in plants and have the physiological function of resisting UV damage, pests and diseases, and attracting insect pollination [9]. They also have a strong free radical scavenging effect and have many biological activities, such as cardiovascular protection [10] and anti-tumor properties [11]. Anthocyanins are classified according to the location of phenolic hydroxyl and methyl groups, there are at least 13 types of anthocyanins in nature, six of which are common and include petunidin, peonidin, cyanidin, delphinidin, pelargonidin, and malvidin. Currently, these six types of anthocyanins and their derivatives are about 95% of the total amount of anthocyanins in nature. The biosynthesis pathway of anthocyanins has been studied in horticultural plants in detail. These studies have identified important upstream structural genes, such as chalcone synthase (CHS) and chalcone isomerase (CHI), and downstream structural genes, such as dihydroflavonol reductase (DFR), anthocyanidin synthase (ANS), and flavonoid 3-O-glycosyl transferase (UFGT), in the flavonoid biosynthesis pathway. The expression of anthocyanin synthetic structural genes is regulated by a variety of transcription factors (TFs). According to the different conserved domains contained in TFs, they are roughly divided into MYB, bHLH, WD40, MADS-box, and bZIP families [12], among which the most studied is the MYB family. MYB is one of the most characteristic families of TFs, widely distributed in all eukaryotes, including animals, plants, and fungi. MYB proteins can be divided into four types based on the number of MYB repeats:1 R-MYB, R2R3-MYB, R1R2R3-MYB, and 4 R-MYB [13]. The studies on the regulation of anthocyanin biosynthesis in the MYB TF family mainly focus on the R2R3-MYB TF, and the study on the regulation of anthocyanin in fruit trees by the R2R3-MYB TF began late. In 2006, Espley et al. found a light-induced anthocyanin synthesis gene MdMYB1 in apple, followed by two types of genes regulating anthocyanin biosynthesis in pulp, MdMYB10 [14] and MdMYB110a [15]. With the separation and functional validation of the key TFs, MdMYB1 and MdMYB10, of anthocyanin in apple, the homologous genes were isolated successively in plants such as strawberry [16], peach [17], pear [18], sweet cherry [19], and pomegranate [20]. R2R3-MYB regulation can be divided into activation and inhibition, for example, FaMYB1 in strawberries [21], AtMYBL2 in Arabidopsis [22], and VvMYBC in grapes [23], which inhibit anthocyanin synthesis.

Bagging is used frequently in the cultivation and management of fruit trees and is widely applied in apple, pear, grape, and other fruit trees. Fruit bagging can improve the appearance and intrinsic quality of fruit to a certain extent, reduce pesticide residues, and improve the food safety and commodification of fruit. When there is a difference in light sensitivity between the pericarp and pulp coloration, bagging can change the influence of external environmental factors, especially the light signal, on anthocyanin synthesis. Bagging also has effects on intrinsic quality of the fruits, which was commonly reported negative changes. Fig can be regarded as a new model fruit with its relatively small genome size and long fruit season. As a non-photosensitive part, the anthocyanin synthesis regulation gene and the appearance of flavor components of the female flower tissue of fig may have another regulatory mechanism. Arabidopsis with mutant cop1 can maintain anthocyanin synthesis under dark conditions, PAP1 and PAP2 activate structural genes PALs, CHS, CHI, F3H, F3ʹH, ANS, and DFR, promoting anthocyanin biosynthesis [24]. Bagging has no great influence on anthocyanin accumulation in non-photosensitive fruits, but it has a great impact on the formation of flavor components and taste. The appearance of the fruit after bagging improves significantly, however, the taste and flavor of the fruit is another important factor affecting customer choice. Fruit odor (caused by volatile compounds such as phenols and alcohols) and taste (determined by the proportion and concentration of sugars, organic acids, and amino acids) contribute to the formation of fruit flavor [25]. Previous studies have focused on the identification of color, soluble solids, total sugar, and total acid components of the fruit after bagging, however, research on the changes of internal transcription and metabolite networks in the fruit after bagging is lacking.

In this study, the fig variety ‘Zibao’ with both colored pericarp and pulp was used as the research material. To better understand the effect of bagging treatment on fruit color quality and flavor components, the transcriptome and widely targeted metabolome were used jointly to analyze bagged fruit. The changes of related secondary metabolites including carbohydrates, organic acids, and amino acids in female flower tissues before and after bagging in fig fruit were identified by the metabolome, and the differential changes of related MYB TFs, structural genes and endogenous hormone (ABA, IAA, and GA) metabolism and signal transduction-related genes in the anthocyanin synthesis pathway were analyzed through the transcriptome. This study investigated how the molecular mechanism of bagging affects the color quality and the formation of flavor components in fig fruit, which provides a theoretical basis for in-depth analysis into the gene regulation mechanism of fig fruit coloration and further delivers a reference to produce high-quality fig fruit.

2.1 Plant material and treatment

The common fig cultivar ‘Zibao’ (the formal identification was approved by the State Forestry Administration of China, the new variety right number [20150145]) was planted at the Shangzhuang Experimental Station (40°23ʹ N, 116°49ʹ W) of China Agricultural University, Haidian District, Beijing, China. The original source of the fig materials used from Weihai Changshoukang Food Co., Ltd. in Shandong province. Experimental research on fig comply with China and Shandong province local legislation. The trees have been cultivated for 5 years and planted in a greenhouse with a row spacing and plant spacing of 2 m × 3 m. Double-layer opaque paper bags with a black inside and light brown outside (150 mm × 150 mm, Zhengguo Paper Bag, Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences) were used for shading the figs. Figs were sampled in the late stage of phase III and termed CK (natural growth of female flowers) and BF (bagged female flowers). There were three biological replicates per sample each with 30 fruits collected randomly from five trees. We took the figs back to the laboratory, and the female flowers (about 10 g in weight) were carefully excised with a razor blade. The female flowers were immediately frozen in liquid nitrogen and stored at -80 °C for further use.

2.2 Sample preparation and metabolite extraction

Fig female flower samples were further ground and thoroughly mixed with a mortar and pestle in liquid nitrogen. The freeze-dried tissue was crushed using a mixer mill (MM 400, Retsch) with Zirconia beads for 1.5 min at 30 Hz. The powdered sample (100 mg) was weighed and extracted overnight at 4 °C with 1.0 mL 70% aqueous methanol. Following centrifugation at 10,000 × g for 10 min, the extracts were absorbed (CNWBOND Carbon-GCB SPE Cartridge, 250 mg, 3 mL; ANPEL, Shanghai, China, www.anpel.com.cn/cnw) and filtrated (SCAA-104, 0.22 µm pore size; ANPEL) before LC-MS analysis.

The fig female flower sample extracts were analyzed using an LC-ESI-MS/MS system (HPLC, Shim-pack UFLC SHIMADZU CBM30A system, www.shimadzu.com.cn; MS, Applied Biosystems 6500 Q TRAP, www.appliedbiosystems.com.cn). The analytical conditions were as follows: HPLC column, Waters ACQUITY UPLC HSS T3 C18 (1.8 µm, 2.1 mm ⋅ 100 mm); the solvent system was water (0.04% acetic acid) and acetonitrile (0.04% acetic acid); gradient program, 95:5 V/V at 0 min, 5:95 V/V at 11.0 min, 5:95 V/V at 12.0 min, 95:5 V/V at 12.1 min, 95:5 V/V at 15.0 min; flow rate, 0.40 ml/min; temperature, 40 °C; injection volume, 2 µL. The effluent was alternatively connected to an ESI-triple quadrupole-linear ion trap (Q TRAP)-MS [26].

2.3 Metabolite identification and quantification

LIT and triple quadrupole (QQQ) scans were acquired on a QQQ-linear ion trap mass spectrometer (Q TRAP), API 6500 Q TRAP LC/MS/MS system, equipped with an ESI Turbo Ion-Spray interface, operating in a positive ion mode and controlled by Analyst 1.6.3 software (AB Sciex). The ESI source operation parameters were as follows: ion source, turbo spray; source temperature, 500 °C; ion spray voltage (IS) 5500 V; ion source gas I (GSI), gas II (GSII), curtain gas (CUR) were set at 55, 60, and 25.0 psi, respectively; the collision gas (CAD) was high. Instrument tuning and mass calibration were performed with 10 and 100 µmol/L polypropylene glycol solutions in QQQ and LIT modes, respectively. QQQ scans were acquired as MRM experiments with collision gas (nitrogen) set to 5 psi. Declustering potentials (DP) and collision energies (CE) for individual MRM transitions were done with further DP and CE optimization. A specific set of MRM transitions were monitored for each period according to the metabolites eluted within this period. Metabolite data analysis was conducted with Analyst 1.6.1 software (AB SCIEX, Ontario, Canada). Metabolite quantification was carried out using MRM. Partial least squares discriminant analysis (PLS-DA) was carried out with the metabolites identified. Metabolites with significant differences in content were set with thresholds of variable importance in projection (VIP) ≥ 1 and fold change ≥ 2 or ≤ 0.5 [27, 28].

2.4 RNA-seq and annotation

Six libraries representing the two female flower samples and the three replicates were constructed for transcriptome sequencing. Total RNA extraction from fig material was performed using the CTAB method [29]. RNA concentration and purity were measured by NanoDrop 2000 (NanoDrop Technologies, Wilmington, DE, USA) and the Agilent Bioanalyzer 2100 system (Agilent Technologies, Palo Alto, CA, USA), respectively. After RNA integrity was determined by 1% agarose gel electrophoresis, RNA concentration was adjusted to the same level. mRNA was isolated from total RNA using magnetic beads with oligo (dT); cDNA was synthesized using a cDNA Synthesis Kit (TaKaRa, Japan) and linking the sequencing adapter to both ends [30]. The library preparations were sequenced on an Illumina HiSeq 4000 platform and the unigene sequences obtained from our laboratory transcriptome database by RSEM software were integrated for annotation [29].

2.5 Transcriptome data analysis

Raw reads were processed with FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc) to filter out adapters and low-quality sequences. For gene expression analysis, counts were mapped to the reading of each gene by HTSeq (v0.5.4p3) and then normalized to fragments per kilobase of transcript per million mapped reads (FPKM). EdgeR software (http://www.bioconductor.org/packages/2.12/bioc/html/edgeR.html) was used to analyze differentially expressed genes (DEGs). Screening of significant DEGs was performed with p-value (p-FDR) ≤ 0.05 and |log2FC| ≥ 1 as the criteria. Enrichment analyses were performed using GOatools (https://github.com/tanghaibao/GOatools) and Fisher’s exact test. To control the calculated false positive rate, the p-values were corrected using four multiple test methods, and significant differences in GO functionalization were performed on the differential genes at p ≤ 0.05. KEGG pathway enrichment analysis was performed using KOBAS software (http://kobas.cbi.pku.edu.cn/home.do) with a corrected P-value ≤ 0.05 [27].

2.6 Verification by using RT-qPCR

Based on the transcriptome data of CK and BF fig female flowers, the expression level of 15 DEGs were validated. The PCR was performed with an ABI 7500 Fast Real-Time Detection System (Applied Biosystems) using the Ultra SYBR Mix kit (TaKaRa, Japan). The amplification system consisted of 10 µL Ultra SYBR Premix System II, 0.5 µL of 10 µmol/L upstream primer, 0.5 µL of 10 µmol/L downstream primer, 2 µL template, and double distilled water to a total volume of 20 µL. The amplification program was 95 °C for 10 min, followed by 40 cycles of 95 °C for 5 s and 58 °C for 30 s. Relative quantitative analysis of data was performed by the 2^−ΔΔCT method with β-actin as the reference gene. The primers used for RT-qPCR are listed as Additional file 1: Table S1.

3.1 Widely targeted metabolome and KEGG classification analysis of differential metabolites

The coloration of mature fig pericarp must be illuminated to promote anthocyanin accumulation under pulsed light irradiation [31]. The subsequent experiments showed that the coloration of fruit pericarp was regulated by the light signal, and the accumulation of anthocyanin stopped almost completely under bagging conditions. However, the coloration of the female flower tissue of fig was not affected by the light signal, and the development of anthocyanin in the female flower was barely affected under the condition of fruit bagging, and the content of anthocyanins of female flower in the mature stage was basically the same as that of the control group, for the red variety; the female flower tissue in the mature stage is bright red (Fig. 1). Although there is no significant difference in the color of female flower tissue, the flavor and taste are still slightly different. To explore the effect of bagging on fruit flavor components, the secondary metabolites of samples before and after bagging were analyzed by a widely targeted metabolome. A total of 771 compounds in 16 classes were detected (Table S2). Principal component analysis (PCA) was conducted with 771 metabolites, 49.21% of PC1 and 16.02% of PC2. PCA separated the two varieties and the quality control (QC) samples, the significance was 0.01 (Fig. 2A). With Log2FC ≥ 2 and ≤ 0.5, and VIP ≥ 1, 43 upregulated and five downregulated metabolites were identified (Fig. 2B). Using metabolite concentration data for the cluster analysis of a stratified heat map of the samples, it was observed that all biological replicates were grouped together (top of the figure), which indicates a high reliability of the resulting metabolome data (Fig. 2C). Interestingly, a clear distinction between the unbagged fruit samples (CK) and the bagged fruit samples (BF) were observed, suggesting a distinct difference in metabolite characteristics in both samples. The metabolites (left side of the figure) were also clustered into two main groups, showing opposite accumulation levels between red female flower tissue samples before and after bagging. A total of 771 metabolites were mapped to the KEGG database and the results indicated that most metabolites were associated with “metabolism”. Some metabolites were classified as “biological systems” or “human diseases”, which suggested that some metabolites in the female flower tissues of fig may have potential health effects. KEGG enrichment analysis showed that there were mainly 35 groups, among which, the metabolites of “biosynthesis of plant secondary metabolites”, “flavone and flavonol biosynthesis”, and “metabolic pathway” were three groups with significantly different female flower tissues before and after bagging (p < 0.05) (Fig. 2D).

3.2 Phenylpropanoids, flavone, flavonol, flavanone, and anthocyanins

A total of 234 substances were detected by flavonoid metabolite analysis, of which 32 reached a level of significant difference. For further mining differential metabolites, data was analyzed by PLS-DA (Figure S1). The PLS-DA score map exhibited a distinct separation between groups and obvious clustering within the group, which further suggested that the difference between the two groups is significant. The quality parameters of the model with two principal components were as follows: R2X = 0.643, R2Y R2X = 0.995, and Q2R2X = 0.739, which indicated that the current model had a better ability to interpret and predict data. Using VIP ≥ 1.0 and | Log₂FC | ≥ 1 as a threshold for significant differences, 32 flavonoid metabolites were identified from ‘CK vs. BF’ samples as significantly differentially expressed, including 12 flavones, nine phenylpropanoids, five flavonols, three anthocyanins, and one flavanone (Table 1). The cyanidin O-acetylhexoside and cyanidin 3-O-malonylhexoside were found to be upregulated by 1.13 times and 1.06 times compared with CK in the female flower tissue of the bagged fruit, which explained the slightly darker color of the bagged fruit compared with CK. The phenylpropanoid biosynthesis pathway is upstream of the anthocyanin and flavonoid biosynthesis pathway. Nine phenylpropanoid secondary metabolites were identified, among which the expression of six was upregulated and three were downregulated. The phenethyl caffeate, angelicin, and methyl p-coumarate contents in female flower tissues increased 8.26 times, 2.87 times, and 2.20 times in ‘CK vs. BF’, while the contents of 3,4,5- trimethoxycinnamic acid, ioacteoside, and 3,4-dihydrocoumarin decreased 2.26,1.48, and 1.09 times, respectively. Twelve flavonoids were detected in female flower tissue, 11 of which were upregulated. The biggest differences were shown in three groups: apigenin, nobiletin, and tangeretin. Among them, the upstream substrate apigenin of luteolin increased significantly in BF and was upregulated by 11.11 times.

Table 1

Differentially accumulated phenolic compounds with VIP (variable importance in projection) ≥ 1, and | Log₂FC| ≥ 1 as for upregulation/downregulation in the ‘Zibao’ female flower tissues (CK) by bagging (BF)
Component name	Metabolite name	Content		Log₂FC (CK vs. BF)	VIP
Component name	Metabolite name	CK	BF	Log₂FC (CK vs. BF)	VIP	Type
Anthocyanin	Cyanidin O-acetylhexoside	1.91E + 05	4.13E + 05	1.11E + 00	1.45E + 00	up
Anthocyanin	Cyanidin 3-O-malonylhexoside	2.91E + 05	6.08E + 05	1.06E + 00	1.46E + 00	up
Phenylpropanoids	Phenethyl caffeate	9.00E + 00	2.77E + 03	8.26E + 00	1.20E + 00	up
	Angelicin	1.84E + 03	1.35E + 04	2.87E + 00	1.35E + 00	up
	Methyl p-coumarate	2.29E + 03	1.05E + 04	2.20E + 00	1.30E + 00	up
	Cinnamic acid	4.31E + 04	1.54E + 05	1.84E + 00	1.23E + 00	up
	Psoralen	5.76E + 03	1.76E + 04	1.61E + 00	1.55E + 00	up
	trans-Cinnamate	5.38E + 04	1.63E + 05	1.60E + 00	1.20E + 00	up
	3,4-Dihydrocoumarin	4.61E + 04	2.16E + 04	-1.09E + 00	1.53E + 00	down
	Isoacteoside	8.83E + 03	3.17E + 03	-1.48E + 00	1.16E + 00	down
	3,4,5-Trimethoxycinnamic acid	2.09E + 04	4.35E + 03	-2.26E + 00	1.27E + 00	down
Flavone	Apigenin	9.00E + 00	1.99E + 04	1.11E + 01	1.69E + 00	up
	Nobiletin	8.70E + 03	3.11E + 04	1.84E + 00	1.39E + 00	up
	Tangeretin	5.89E + 03	2.07E + 04	1.81E + 00	1.53E + 00	up
	Apigenin 7-O-glucoside (Cosmosiin)	1.17E + 05	3.43E + 05	1.56E + 00	1.53E + 00	up
	Luteolin 7-O-glucoside (Cynaroside)	3.35E + 05	9.00E + 05	1.43E + 00	1.42E + 00	up
	Velutin	1.45E + 04	3.78E + 04	1.38E + 00	1.36E + 00	up
	Chrysin O-hexoside	1.66E + 04	4.24E + 04	1.36E + 00	1.45E + 00	up
	Chrysin 5-O-glucoside (Toringin)	1.68E + 04	4.06E + 04	1.27E + 00	1.34E + 00	up
	Acacetin	6.46E + 04	1.38E + 05	1.09E + 00	1.37E + 00	up
	Chrysoeriol 5-O-hexoside	1.71E + 05	3.60E + 05	1.08E + 00	1.53E + 00	up
	Luteolin	4.97E + 03	1.02E + 04	1.03E + 00	1.54E + 00	up
	Tricin 5-O-rutinoside	8.81E + 03	3.44E + 03	-1.36E + 00	1.17E + 00	down
Flavonol	Kaempferol 3-O-rhamnoside (Kaempferin)	1.20E + 04	4.00E + 04	1.74E + 00	1.48E + 00	up
	Kaempferol 7-O-rhamnoside	1.78E + 04	5.28E + 04	1.57E + 00	1.41E + 00	up
	Kumatakenin	2.33E + 04	5.93E + 04	1.35E + 00	1.41E + 00	up
	Morin	3.29E + 05	7.77E + 05	1.24E + 00	1.14E + 00	up
	Kaempferol 3-O-galactoside (Trifolin)	2.10E + 05	4.75E + 05	1.18E + 00	1.45E + 00	up
Flavanone	Pinocembrin (Dihydrochrysin)	2.19E + 04	1.62E + 05	2.88E + 00	1.32E + 00	up
Isoflavone	2'-Hydroxygenistein	3.50E + 03	1.30E + 04	1.89E + 00	1.51E + 00	up
	Sissotrin	1.64E + 04	7.01E + 04	2.10E + 00	1.46E + 00	up
	Prunetin	6.50E + 04	1.43E + 05	1.14E + 00	1.39E + 00	up

3.3 Carbohydrates, amino acids, organic acids, and vitamins

Flavor and nutrient components are mainly composed of carbohydrates, organic acids, and amino acids. VIP ≥ 1, and fold change ≥ 1.6 and ≤ 0.6 was set as the threshold of significant difference, a total of 19 significantly differentially expressed flavor-related metabolites were identified from the ‘CK vs. BF’ samples, including one carbohydrate, seven amino acids and derivatives, eight organic acids and derivatives, and three vitamins and derivatives (Table 2). D(-)-Threose was upregulated 3.70 times more than that of CK in the female flower tissues of bagged fruit. Seven substances of amino acids and derivatives were screened from the female flower tissue before and after bagging, two of which were upregulated, while five were downregulated. In the significantly downregulated metabolites, L-aspartic acid, CYS-GLY, Lhomocysteine, phenylacetyl-L-glutamine, and aspartic acid all reached more than five times the significant difference level, which indicates that the bagged fruit did not have a rich proportion of sugar and acid compared with the CK, leading to a reduction in the flavor. Among them, the upstream substrate apigenin of luteolin increased significantly in BF and was upregulated by 11.11 times. The phenylpropanoid biosynthesis pathway is upstream of the anthocyanin and flavonoid biosynthesis pathway. In ‘CK vs. BF’, eight significantly different organic acids and derivatives were screened, of which seven were upregulated and one was down-regulated. Among these, the α-hydroxyisobutyric acid, (S)-(-)-2-hydroxyisocaproic acid, and isochlorogenic acid B contents increased 4.61 times, 3.05 times, and 2.28 times, respectively, while the phosphoenolpyruvate trisodium salt content decreased 1.46 times.

Table 2

Differentially accumulated carbohydrates, amino acids, organic acids and vitamins compounds with VIP (variable importance in projection) ≥ 1, and fold change ≥ 1.6 and ≤ 0.6 as for as for upregulation/downregulation in the cv. ‘Zibao’ CK and BF
Component name	Metabolite name	Average content		Fold change (CK vs. BF)	VIP	Type
Component name	Metabolite name	CK	BF	Fold change (CK vs. BF)	VIP	Type
Carbohydrates	D(-)-Threose	5.60E + 03	8.46E + 03	3.70E + 00	1.03E + 00	up
Amino acid and derivatives	L-Tyramine	2.01E + 05	7.84E + 05	3.90E + 00	1.40E + 00	up
	N-γ-Acetyl-N-2-Formyl-5-methoxykynurenamine	2.63E + 05	4.23E + 05	1.61E + 00	1.47E + 00	up
	L-Aspartic acid	1.19E + 07	7.10E + 06	5.98E-01	1.07E + 00	down
	CYS-GLY	5.61E + 04	3.25E + 04	5.79E-01	1.49E + 00	down
	L-Homocystine	2.09E + 05	1.19E + 05	5.72E-01	1.28E + 00	down
	Phenylacetyl-L-glutamine	1.61E + 05	9.01E + 04	5.61E-01	1.06E + 00	down
	Aspartic acid	1.05E + 07	5.83E + 06	5.55E-01	1.15E + 00	down
Organic acids and derivatives	α-Hydroxyisobutyric acid	1.80E + 05	8.28E + 05	4.61E + 00	1.37E + 00	up
	(S)-(-)-2-Hydroxyisocaproic acid	2.59E + 04	7.88E + 04	3.05E + 00	1.15E + 00	up
	Isochlorogenic acid B	7.36E + 04	1.68E + 05	2.28E + 00	1.37E + 00	up
	Chlorogenic acid methyl ester	2.26E + 04	4.39E + 04	1.94E + 00	1.14E + 00	up
	2,3-Dihydroxybenzoic acid	9.30E + 05	1.74E + 06	1.87E + 00	1.41E + 00	up
	2-Hydroxybutanoic acid	3.35E + 04	5.67E + 04	1.69E + 00	1.48E + 00	up
	D-Pantothenic dcid	1.39E + 04	2.35E + 04	1.69E + 00	1.19E + 00	up
	Phosphoenolpyruvate trisodium salt	7.34E + 04	4.08E + 04	5.56E-01	1.46E + 00	down
Vitamins and derivatives	delta-Tocopherol	2.68E + 03	9.71E + 03	3.62E + 00	1.48E + 00	up
	Thiamine pyrophosphate	8.41E + 03	1.44E + 04	1.71E + 00	1.46E + 00	up
	Orotic acid	1.52E + 05	2.59E + 05	1.71E + 00	1.57E + 00	up

3.4 RNA-seq analysis

The control and treatment groups of the ‘Zibao’ fig female flower tissue in a total of two samples, each with three biological replicates, were sequenced in this study. The control group (CK) was the female flower tissue at the end of phase III, and the treatment group was the female flower tissue after bagging and named bagged flower (BF). The double-terminal reading of the cDNA library of the two samples was performed using the Illumina HiSeq 4000 platform, which produced 7,394,743,914 and 9,582,970,682 paired-end original reads of 200 bp in length. The low-quality reads were deleted and the joint sequences were removed, resulting in the acquisition of 6,747,389,564 and 9,137,841,606 clean data for CK and SF libraries, respectively. Mapping ratios compared to reference databases were 91.37% and 91.32%, respectively (Table S3). Different genes were identified between the two samples and filtrated and corrected by FDR < 0.05 and | log2FC | ≥ 2. By comparing the number of different genes between the control and bagged group between the pericarp and the female flower, 2389 significantly different genes were found in the ‘CK vs. BF’, among which the number of up-regulated genes was slightly higher than that of down-regulated genes, 1208 and 1181, respectively (Figure S2 A). Gene Ontology (GO, http://www.geneontology.org/) annotation of the DEGs found that 1,154 unigenes were annotated to ‘Biological Process’, 674 unigenes were annotated to ‘Cellular Component’, and 572 unigenes were annotated to ‘Molecular Function’ (Figure S2 B). To identify the biological pathways activated in fig female flowers, the normative reference pathway for annotation sequences to the KEGG database was chosen. In KEGG pathways, protein processing in the endoplasmic reticulum, plant hormone signal transduction, and plant-pathogen interaction pathways were significantly changed in the ‘CK vs. BF’ group with corrected P-value ≤ 0.05 (Table S4, Figure S2 C).

3.5 Flavonoid biosynthesis pathway and transcriptional regulation

The expression of nine structural genes of the flavonoid biosynthesis pathway (PAL, C4H, 4CL, CHS, CHI, F3H, F3ʹH, DFR, ANS, and UFGT) play a critical role in anthocyanin biosynthesis. To better understand the time-space difference of coloration between the pericarp and the female flower of fig, 16 important structural genes differentially expressed in the female flower tissues of the fig ‘Zibao’ were selected. Of these, PAL, FcPAL (c388_g2), was significantly increased 2.71 times after bagging, C4H, FcC4H (c39884_g1), was significantly increased 2.12 times after bagging, and CHS, FcCHS (c46769_g3), was significantly upregulated 6.37 times in female flower tissue after bagging. FcCHI (c46816_g1) was downregulated 2.12 times in female flower tissue. No significant changes were found in F3H and F3ʹH expression in female flower tissues after bagging. In ‘CK vs. SF’, FcDFR (c18574_g2) was significantly upregulated by three times. Three ANS genes were selected, in ‘CK vs. BF’, FcANS1, FcANS2, and FcANS3 all showed a trend of upregulation, 2.92 times, 2.28 times, and 1.99 times, respectively. There were six UFGT genes, four of these (FcUFGT1, FcUFGT2, FcUFGT3, and FcUFGT4) were significantly upregulated in ‘CK vs. BF’, 2.8 times, 2.68, 2.52, and 2.52 times, respectively, two UFGT genes, FcUFGT5 (c41071_g2) and FcUFGT6 (c47047_g2), in ‘CK vs. BF’ were significantly downregulated 2.73 times and 5.93 times, respectively (Fig. 3A).

Gene expression at the transcriptional level plays an important role in regulating and controlling many biological processes, TFs are the key to the regulation of secondary metabolite genes. After bagging, the original red pulp of the fig ‘Zibao’ did not change, showing non-light dependency. In ‘CK vs. BF’, 13 MYB and 17 bHLH family members showed significant differences. MYB TFs are widely found in plants and are involved in almost all aspects of plant development and metabolism. In these MYB families, the expression of 12 genes was upregulated, of which c43673_g1, c12586_g1, c44925_g1, and c36728_g1 were different by more than four times, 4.87, 4.81, 4.24, and 4.14 times, respectively, while c66005_g2 was downregulated 3.8 times (Fig. 3B). The basic helix-loop-helix (bHLH) family is the second largest family of TFs in plants and has many functions, including regulating flower organ development, photomorphogenesis, epidermal hair, and stomatal formation, plant hormone response, and flavonoid metabolism [12] Eight genes from the bHLH family were significantly upregulated in the ‘CK vs. BF’, c66694_g1(4.94), c81283_g1(3.68), c72970_g1(3.66), c43099_g1(3.42), c25473_g1(2.92), c43008_g2(2.72), c39854_g1(2.16), and c33397_g1(2.12), while nine genes showed a trend of significant downregulation, c43844_g1 and c40266_g1 were different by more than three times, 3.71 and 4.39 times, respectively (Fig. 3B). The bHLH family members are associated with anthocyanin biosynthesis in fruit trees and have been shown to interact with MYB TFs to regulate fruit color. The co-expression of bHLH transcription factor VvMYC1 and VvMYBA1 can accumulate anthocyanins in grape suspension cells [32]. The interaction of MdbHLH3 and MdbHLH33 with MYB TFs is involved in the regulation of anthocyanin synthesis in apple fruit [33].

3.6 Changes of endogenous plant hormone metabolism and signal transduction genes after bagging

The endogenous hormones GA and ABA are transformed from glucose molecules, a direct product of photosynthesis, through plant isoprene biosynthesis, which regulates anthocyanin biosynthesis [34]. In ABA biosynthesis, except for c36086_g2, which was significantly upregulated, all of the other four 9-cis-epoxycarotene dioxygenase (NCED) genes were significantly downregulated. Eight genes were annotated as possible protein phosphatase 2 C (PP2C), significantly upregulated, and two genes (c2285_g1 and c25449_g1) were annotated as ABA-activated protein kinase 2(SNRK2) in female flowers, and four ABRE binding factor (ABF) genes were significantly downregulated after bagging. One ABA 8ʹ- hydroxylase (ABA 8ʹ-h) gene (c23609_g1) was significantly downregulated 3.17 times for ABA catabolism (Fig. 4A). In IAA biosynthetic genes, three were annotated as indole-3-acetic acid-inducible protein (ARG7) genes: one significantly upregulated gene c39732_g4, two significantly downregulated genes c1801_g1 and c45831_g4, three auxin response factors (ARF) were upregulated, c20025_g1 and c20025_g2, and downregulated, c32996_g1. Moreover, there was one upregulated Gretchen Hagen3 (GH3) gene c78527_g1, one upregulated signal transduction auxin-instream vector (AUX1) gene, and two IAA-amino acid hydrolase (IAH) genes c32134_g2 and c32501_g1 (Fig. 4B). Gibberellin GA plays an important role in the ripening of strawberries and sweet cherries [35]. The GA degradation gene GA2 oxidase (GA2ox) c32275_g2 was significantly up-regulated by 2.88 times in the ‘CK vs. BF’, and the GA stimulus transcript (GASTI) gene c27193_1 was inversely regulated, which decreased 2.32 times in the bagged female flower tissue (Fig. 4C).

3.7 The qRT-PCR validation

To verify the key results of the RNA-seq, the number of 15 flavonoid biosynthesis pathways structural genes and endogenous hormone signal transduction pathway genes were selected for validation and their expression levels in CK and BF were analyzed by qRT-PCR (Figure S3). The results confirmed that the expression level of these structural genes was similar to that of the RNA-seq results, and there was good agreement with the up- and downregulated gene expression at the RNA-seq level.

Bagging can improve the sensitivity of the fruit to light and affect the intrinsic and appearance quality of the fruit while changing the microenvironment of fruit development. The flavor components of fruit are generally related to the contents of sugar, organic acids, and phenols. Previous studies have focused on the effect of bagging on pericarp color, while studies on flavor changes have just focused on several specific types of metabolites, such as sugars (fructose, glucose, and sucrose), organic acids, amino acids, and alcohols [36, 37]. To date, the overall variation of secondary metabolites of fig fruits by bagging has not been studied. In this study, an LC-MS/MS-based widely targeted metabolomics approach was used to understand the flavor changes of fig fruit after bagging. A total of 771 metabolites were identified, 88 of which were accumulated in female flower tissues after bagging in a differentially expressed manner. A large amount of carbohydrates were confirmed in the tissues of female fig flowers (Table S2), including 20 sugars, 12 of which had significantly reduced concentrations in female flower tissue after bagging, including D-glucose 6-, D-fructose 6-, ribulose-5-phosphate, glucose-1-phosphate, and D-fructose 6-phosphate-disodium salt. These five reduced sugar types are the main sugar types that form the flavor of fig fruit, while 115 types of organic acids were identified, the concentration of half (52) were significantly reduced in female flower tissue after bagging, which can partly explain the change in the flavor of the fruit. The composition and richness of amino acids are the key indexes of nutritional quality and are also important for determining flavor [38]. Previous studies have identified 12 amino acids in fig fruit [39]. However, 99 amino acids were identified by widely targeted metabolome analysis, seven of these accumulated differences between CK and SF (Table 2). Five of these amino acids (L-aspartic acid, CYS-GLY, L-homocysteine, phenylacetyl-L-glutamine, and aspartic acid) were significantly reduced after bagging (Table 2). Therefore, the results show that differences in amino acid composition and abundance can also lead to changes in flavor matter.

Plant hormones play important roles in inducing anthocyanin accumulation. Plant hormones usually interact with light signaling pathways to regulate plant growth. E3 ubiquitin ligase-based constitutively photomorphogrnic1 (COP1) is a decisive inhibitor of photomorphogenesis in the process of signal transduction, and a ‘molecular switch’ located downstream of the photoreceptor. Under dark conditions, COP1 proteins enter the nucleus and can form complexes with suppressor of phyA-105 (SPA1) [40]. Then, ubiquitin degrading photomorphogenesis promotes TF HY5, and inactivates them or leaves their areas of action, thereby regulating anthocyanin synthesis [41]. Under light condition conditions, COP1 transfers from the nucleus to the cytoplasm and HY5 accumulation initiates photomorphogenesis. ABA metabolism and signal transduction gene synthesis were significantly differentially expressed by light regulation in this study. Studies have demonstrated that members of the ABA pathway can be associated with both HY5 and PIF3, indicating that ABA may be the most important plant hormone in light-dependent anthocyanin biosynthesis [35]. The GO enrichment analysis of the DEGs described above indicates that, functionally, GA participates in photo-mediated anthocyanin biosynthesis (Figs. 4). Meanwhile, HY5 and PP2CA, as well as PIF3 and PYL10, are co-expressed with other TFs and structural genes involved in anthocyanin biosynthesis. Similarly, members of possible interaction pathways HY5-SLY1-GASA3 and PIF3-GID1A are co-expressed with anthocyanin biosynthetic genes. At present, it has been found that ABA plays an important role in the development, maturation, and postharvest stage of fig female flower tissue. ABA is produced rapidly in female flower tissue in figs before color conversion and reaches the highest level before the commercial maturation period, whereas the anthocyanin content changes later than ABA. The ABA synthesis inhibitor NDGA inhibits the accumulation of anthocyanin, which indicates that ABA is one of the important factors to promote fruit coloring during the normal development of fig [35]. Hence, this study proposes a co-expression network that involves ABA-HY5-MYB in the biosynthesis of anthocyanin in female flower tissue. To understand whether the change of the expression level of numerous hormone metabolism and synthesis-related genes in fruit affects the change of flavor components in a later stage of fruit, future studies will be carried out on hormone metabolites in fruit after bagging. This study will lay the foundation for exploring the molecular and metabolic mechanisms of plant hormones and fruit flavor component formation.

In this study, HPLC-MS/MS-based metabolome and transcriptome analysis were successfully performed to systematically compare flavor component differences and flavonoid biosynthesis changes before and after bagging in fig fruit. This work provided comprehensive information on the composition and abundance of metabolites in the female flower tissue of fig. It also preliminarily explored the difference in patterns of the space-time coloration of different fig tissues. To identify the various regulatory patterns of structural genes and MYB TFs involved in flavonoid biosynthesis pathways, as well as component differences and concentration changes of carbohydrates, organic acids, amino acids, phenols, and alcohols in female flower tissue, the underlying causes of changes in fruit flavor quality after bagging were determined.

ANS

Anthocyanidin synthase; bHLH:Basic helix-loop-helix; CHI:Chalcone isomerase; CHS:Chalcone synthase; COG:Clusters of orthologous groups of proteins database; DEG:Differentially expressed gene; DFR:Dihydroflavonol 4-reductase; FPKM:Fragments per kilobase of exon model per million mapped reads; F3H:Flavanone 3-hydroxylase; F3′H:Flavanone 3′-hydroxylase; GO:Gene Ontology; KEGG:Kyoto Encyclopedia of Genes and Genomes; LAR:Leucoanthocyanidin reductase; MYB:v-myb avian myeloblastosis viral oncogene homolo; PAL:Phenylalanine ammonia-lyase; TFs:transcription factors; UFGT:UDP-glucose:flavonoid 3-O-glucosyltransferase.

Acknowledgments

We thank the staff of Wuhan Metware Biotechnology Co., Ltd. (Wuhan, China), for their support during the metabolite data analysis.

Funding

This work was supported by the Natural Science Foundation of China project NSFC [31372007], the funder provided fees for transcriptome and metabolomics testing. Major Science and Technology Project of Yunnan Province (Special Project of Green Food International Cooperation Research Center) [2019ZG00907], Science Research Fund Project of Yunnan Provincial Department of Education [2020J0247], the funders provided the cost of reagents required for later test verification and paper publication fees, etc.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its Supplementary information files. The raw RNA-seq data are freely available at: www.ncbi.nlm.nih.gov/bioproject/ PRJNA494945.

Authors’ contributions

HM and SC designed the experiments. ZW and MS conducted the experiments and analyzed the results. ZW, MS, SC, and HM prepared the manuscript. All authors have read and approved the manuscript for publication.

Ethics approval and consent to participate

The experiments did not involve endangered or protected species. No specific permits were required for these activities because the figs used in this study were obtained from an orchard in Beijing, which was a demonstration base of China Agricultural University.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

USDA. Nutritive Value of Foods., U.S. Department of Agriculture, Agricultural Research Service, Nutrient Data Labora-tory, Beltsville, Maryland. Available at http://www.nal.usda.gov/fnic/foodcomp/Data/HG72/hg72_2002.pdf(Accessed 3 December 2008); 2002.
Jeong WS, Lachance PA. Phytosterols and fatty acids in fig (Ficus carica, var. mission) fruit and tree components. J Food Sci. 2001;66(2):278–81.
Su Q, Rowley KG, Itsiopoulos C, O"Dea K. Identification and quantitation of major carotenoids in selected components of the mediterranean diet: green leafy vegetables, figs and olive oil. Eur J Clin Nutr. 2002;56(11):1149–54.
Solomon A, Golubowicz S, Yablowicz Z, Grossman S, Bergman M, Gottlieb HE, et al. Antioxidant activities and anthocyanin content of fresh fruits of common fig (Ficus carica L.). J Agric Food Chem. 2006;54(20):7717–23.
Caro AD, Piga A. Polyphenol composition of peel and pulp of two italian fresh fig fruits cultivars (Ficus carica L.). Eur Food Res Technol. 2008;226(4):715–9.
Zhou J, Cao L, Chen S, Perl A, Ma H. Consumer-assisted selection: the preference for new tablegrape cultivars in china. Aust J Grape Wine Res. 2015;21(3):351–60.
Wang Z, Zhou J, Xu X, Perl A, Chen S, Ma H. Adoption of table grape cultivars: An attribute preference study on Chinese grape growers. Sci Hortic. 2017;216:66–75.
Elisa Schulz. The role of flavonols and anthocyanins in the cold an UV-B acclimation of Arabidopsis thaliana (L.). BMC Gastroenterol. 2014;11(1):1–10.
Wallace TC, Slavin M, Frankenfeld CL. Systematic Review of Anthocyanins Markers of Cardiovascular Disease Nutrients. 2016;8(1):32.
Riaz M, Zia-Ul-Haq M, Saad B. Anthocyanins effects on carcinogenesis, immune system and the central nervous system. Anthocyanins and Human Health: Biomolecular and therapeutic aspects. Springer International Publishing; 2016.
Hichri I, Heppel SC, Pillet J, Leon C, Czemmel S, Delrot S, et al. The Basic Helix-Loop-Helix Transcription Factor MYC1 Is Involved in the Regulation of the Flavonoid Biosynthesis Pathway in Grapevine. Mol Plant. 2010;3(3):509–23.
Liu J, Osbourn A, Ma P. MYB Transcription Factors as Regulators of Phenylpropanoid Metabolism in Plants. Mol Plant. 2015;8(5):689–708.
Espley RV, Brendolise C, Chagne D, Kuttyamma S, Green S, Volz RK, et al. Multiple Repeats of a Promoter Segment Causes Transcription Factor Autoregulation in Red Apples. Plant Cell. 2009;21(1):168–83.
Chagne D, Linwang K, Espley RV, Volz RK, How NM, Rouse S, et al. An Ancient Duplication of Apple MYB Transcription Factors Is Responsible for Novel Red Fruit-Flesh Phenotypes. Plant Physiol. 2013;161(1):225–39.
Aharoni A, De Vos CH, Wein M, Sun Z, Greco R, Kroon A, et al. The strawberry FaMYB1 transcription factor suppresses anthocyanin and flavonol accumulation in transgenic tobacco. Plant J. 2001;28(3):319–32.
Zhou H, Linwang K, Wang H, Gu C, Dare AP, Espley RV, et al. Molecular genetics of blood-fleshed peach reveals activation of anthocyanin biosynthesis by NAC transcription factors. Plant J. 2015;82(1):105–21.
Liu B, Wang L, Wang S, Li W, Liu D, Guo X, Qu B. Transcriptomic analysis of bagging-treated ‘Pingguo’ pear shows that MYB4-like1, MYB4-like2, MYB1R1 and WDR involved in anthocyanin biosynthesis are up-regulated in fruit peels in response to light. Sci Hortic. 2019;244:428–34.
Jin W, Wang H, Li M, Wang J, Yang Y, Zhang X, et al. The R2R3 MYB transcription factor PavMYB10.1 involves in anthocyanin biosynthesis and determines fruit skin colour in sweet cherry (Prunus avium L.). Plant Biotechnol J. 2016;14(11):2120–33.
Rouholamin S, Zahedi B, Nazarianfirouzabadi F, Saei A. Expression analysis of anthocyanin biosynthesis key regulatory genes involved in pomegranate (Punica granatum L.). Sci Hortic. 2015;186:84–8.
Paolocci F, Robbins MP, Passeri V, Hauck B, Morris P, Rubini A, et al. The strawberry transcription factor FaMYB1 inhibits the biosynthesis of proanthocyanidins in Lotus corniculatus leaves. J Exp Bot. 2011;62(3):1189–200.
Matsui K, Umemura Y, Ohmetakagi M. AtMYBL2, a protein with a single MYB domain, acts as a negative regulator of anthocyanin biosynthesis in Arabidopsis. Plant J. 2008;55(6):954–67.
Cavallini E, Matus JT, Finezzo L, Zenoni S, Loyola R, Guzzo F, et al. The Phenylpropanoid Pathway Is Controlled at Different Branches by a Set of R2R3-MYB C2 Repressors in Grapevine. Plant Physiol. 2015;167(4):1448–70.
Mitsunami T, Nishihara M, Galis I, Alamgir KM, Hojo Y, Fujita K, et al. Overexpression of the PAP1 Transcription Factor Reveals a Complex Regulation of Flavonoid and Phenylpropanoid Metabolism in Nicotiana tabacum Plants Attacked by Spodoptera litura. PLOS ONE. 2014;9(9):e108849.
Zou S, Wu J, Shahid MQ, He Y, Yang X. Identification of key taste components in loquat using widely targeted metabolomics. Food Chem. 2020;323:126822.
Zhang Q, Wang L, Liu Z, Zhao Z, Zhao J, Wang Z, et al. Transcriptome and metabolome profiling unveil the mechanisms of Ziziphus jujuba Mill. peel coloration. Food Chem. 2020;312:125903.
Wang Z, Cui Y, Vainstein A, Chen S, Ma H. Regulation of Fig (Ficus carica L.) Fruit Color: Metabolomic and Transcriptomic Analyses of the Flavonoid Biosynthetic Pathway. Frontiers in Plant Science. 2017; 8:1990.
Liu Y, Lv J, Liu Z, Wang J, Yang B, Chen W, et al. Integrative analysis of metabolome and transcriptome reveals the mechanism of color formation in pepper fruit (Capsicum annuum L.). Food Chem. 2020;306:125629.
Wang Z, Song M, Li Y, Chen S, Ma H. Differential color development and response to light deprivation of fig (Ficus carica L.) syconia peel and female flower tissues: transcriptome elucidation. BMC Plant Biol. 2019;19(1):217.
Chai L, Wang Z, Chai P, Chen S, Ma H. Transcriptome analysis of san pedro-type fig (Ficus carica L.) parthenocarpic breba and non-parthenocarpic main crop reveals divergent phytohormone-related gene expression. Tree Genetics Genomes. 2017;13(4):1–14.
Rodov V, Vinokur Y, Horev B. Brief postharvest exposure to pulsed light stimulates coloration and anthocyanin accumulation in fig fruit (Ficus carica L.). Postharvest Biol Technol. 2012;68(8):43–6.
Guan L, Li JH, Fan PG, Li SH, Fang JB, Dai ZW, et al. Regulation of anthocyanin biosynthesis in tissues of a teinturier grape cultivar under sunlight exclusion. American Journal of Enology Viticulture. 2014;65(3):363–74.
Xie XB, Li S, Zhang RF, Zhao J, Hao YJ. The bHLH transcription factor MdbHLH3 promotes anthocyanin accumulation and fruit coloration in response to low temperature in apples. Plant Cell Environment. 2012;35(11):1884–97.
Rudell DR, Mattheis JP. Synergism exists between ethylene and methyl jasmonate in artificial light-induced pigment enhancement of 'Fuji' apple fruit peel. Postharvest Biol Technol. 2008;47(1):136–40.
Shen X, Zhao K, Liu L, Zhang K, Yuan H, Liao X, et al. A role for PacMYBA in ABA-regulated anthocyanin biosynthesis in red-colored sweet cherry cv. Hong Deng (Prunus avium L.). Plant and Cell Physiology. 2014; 55(5):862–880.
Chen FX, Liu XH, Chen LS. Developmental changes in pulp organic acid concentration and activities of acid-metabolising enzymes during the fruit development of two loquat (Eriobotrya japonica Lindl.) cultivars differing in fruit acidity. Food Chem. 2009;114:657–64.
Lombardo VA, Osorio S, Borsani J, Lauxmann MA, Bustamante CA, Budde CO, et al. Metabolic profiling during peach fruit development and ripening reveals the metabolic networks that underpin each developmental stage. Plant physiology. 2011;157(4):1696–710.
Choi SH, Ahn JB, Kim HJ, Im NK, Kozukue N, Levin CE, et al. Changes in free amino acid, protein, and flavonoid content in Jujube (Ziziphus jujube) fruit during eight stages of growth and antioxidative and cancer cell inhibitory effects by extracts. Journal Agricultural Food Chemistry. 2012;60:10245–55.
Slatnar A, Klancar U, Stampar F, Veberic R. Effect of drying of figs (Ficus carica L.) on the contents of sugars, organic acids, and phenolic compounds. Journal of Agricultural Food Chemistry. 2011;59(21):11696–702.
Saijo Y, Zhu D, Li J, Rubio V, Zhou Z, Shen Y, Deng XW. Arabidopsis COP1/SPA1 complex and FHY1/FHY3 associate with distinct phosphorylated forms of phytochrome A in balancing light signaling. Mol Cell. 2008;31(4):607–13.
Li Y, Mao K, Zhao C, Zhao X, Zhang H, Shu H, Hao Y. MdCOP1 ubiquitin E3 ligases interact with MdMYB1 to regulate light-induced anthocyanin biosynthesis and red fruit coloration in apple. Plant Physiol. 2012;160(2):1011–22.

Additionalfile20200921.pdf

Download PDF

Editorial decision: Major revision
06 May, 2021
Review #2 received at journal
10 Mar, 2021
Reviewer #2 agreed at journal
15 Feb, 2021
Review #1 received at journal
18 Dec, 2020
Reviewer #1 agreed at journal
22 Nov, 2020
Reviewers invited by journal
19 Nov, 2020
First submitted to journal
24 Sep, 2020
Editor assigned by journal
24 Sep, 2020
Submission checks completed at journal
23 Sep, 2020
Editor invited by journal
23 Sep, 2020

You are reading this latest preprint version

Metabolome and Transcriptome Analysis of Flavor Components and Flavonoid Biosynthesis in Fig Fruit (Ficus Carica L.) After Bagging

Status:

Version 1

Abstract

Figures

1. Background

2. Materials And Methods

2.1 Plant material and treatment

2.2 Sample preparation and metabolite extraction

2.3 Metabolite identification and quantification

2.4 RNA-seq and annotation

2.5 Transcriptome data analysis

2.6 Verification by using RT-qPCR

3. Results

3.1 Widely targeted metabolome and KEGG classification analysis of differential metabolites

3.2 Phenylpropanoids, flavone, flavonol, flavanone, and anthocyanins

3.3 Carbohydrates, amino acids, organic acids, and vitamins

3.4 RNA-seq analysis

3.5 Flavonoid biosynthesis pathway and transcriptional regulation

3.6 Changes of endogenous plant hormone metabolism and signal transduction genes after bagging

3.7 The qRT-PCR validation

4. Discussion

5. Conclusions

Abbreviations

Declarations

References

Supplementary Files

Status:

Version 1