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2022 Volume 2
Article Contents
Abstract
Introduction
Materials and methods
Plant materials
Protein extraction
Trypsin digestion
Affinity enrichment of ubiquitinated peptides
Lc-ms/ms and data analysis
Bioinformatics methods
Results
Overview of the ubiquitomic analysis
Properties of ubiquitinated proteins and motifs
A temperature-regulated rice endosperm ubiquitome
Functions for differentially expressed ubiquitinated proteins
Discussion
Ubiquitination of heat shock proteins and transcription factors under high-temperature stress
Sucrose and starch metabolism are modified by ubiquitination under high-temperature stress
Ubiquitination affects sucrose hydrolysis
Ubiquitination of adp-glucose pyrophosphorylase (agpase)
Ubiquitination regulates amylose biosynthesis
Ubiquitination regulates amylopectin biosynthesis
Ubiquitination affects ribosomal systems under high-temperature stress
Author contributions
Data availability
Acknowledgments
Conflict of interest
Supplementary information
Rights and permissions
References
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ARTICLE   Open Access    

cDNA-AFLP analysis reveals altered gene expression profiles involved in juice sac granulation in pummelo (Citrus grandis)

  • 1.

    School of Horticulture Landscape Architecture, Henan Institute of Science and Technology, Henan 453003, China

  • 2.

    Henan Province Engineering Research Center of Horticultural Plant Resource Utilization and Germplasm Enhancement, Xinxiang 453003, China

  • 3.

    College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China

More Information
  • Citrus fruits produced in China are often affected by granulation. Granulation is an altered physiological state of citrus fruits occurring usually before harvest but whose underlying mechanisms remain elusive. In this study, cDNA-AFLP technology enabled the identification of 116 granulation-associated genes in pummelo (C. grandis) juice sacs. Differentially expressed transcript-derived fragments (TDFs) were shown to be mainly involved in biological regulation and signal transduction, carbohydrate and energy metabolism, nucleic acid, protein metabolism, stress responses, and cell metabolism. Therefore, granulation in pummelo juice sacs seems to involve the following alterations: (1) changes in hormone levels; (2) activation of metabolic pathways related to ATP and sugar synthesis to produce more energy; (3) nucleic acid accumulation and increased protein degradation; (4) activation of stress-responsive metabolic pathways; (5) accelerated juice sac senescence. Our findings provide an overview of differential responses occurring at the transcriptional level in granulated juice sacs, thus revealing new insights into the adaptive mechanisms underlying this altered physiological state in 'Guanximiyou' pummelo (C. grandis) juice sacs.

  • Introduction

    Rice (Oryza sativa L.) is a world staple crop that feeds over half of the world's population[1,2]. In recent years, high-temperature events are becoming more frequent and intensive as a result of global warming, which can severely affect rice grain yield and quality[3,4]. During flowering and grain filling stages, high-temperature stress can result in a significant reduction in seed setting rate and influence amylose content, starch fine structure, functional properties and chalkiness degree of rice[5−7]. Transcriptome and proteome analysis in rice endosperm have also been used to demonstrate the differences in high-temperature environments at gene and protein expression levels[8−10]. In addition, as an important post-translational modification, protein phosphorylation has proven to be involved in the regulation of starch metabolism in response to high-temperature stress[11]. However, little is known about whether protein ubiquitination regulates seed development under high-temperature stress.

    Ubiquitination is another form of post-translational modification that plays key roles in diverse cellular processes[12]. Several reports have described the functions of ubiquitination in rice defense responses based on ubiquitome analysis. Liu et al.[13] investigated relationships between ubiquitination and salt-stress responses in rice seedlings using a gel-based shotgun proteomic analysis and revealed the potential important role of protein ubiquitination in salt tolerance in rice. Xie et al.[14] identified 861 peptides with ubiquitinated lysines in 464 proteins in rice leaf cells by combining highly sensitive immune affinity purification and high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). These ubiquitinated proteins regulated a wide range of processes, including response to stress stimuli. A later study revealed the relationships between ubiquitination status and activation of rice defense responses, and generated an in-depth quantitative proteomic catalog of ubiquitination in rice seedlings after chitin and flg22 treatments, providing useful information for understanding how the ubiquitination system regulates the defense responses upon pathogen attack[15]. Although many studies have shown that ubiquitination plays improtant roles in the heat response of plant[16,17], there has been little systematic discussion on the ubiquitome of rice endosperm in the context of global climate change.

    In this study, we examine the high-temperature induced ubiquitination change in two rice varieties with different starch qualities, through a label-free quantitative ubiquitome analysis. This study provides a comprehensive view of the function of ubiquitination in high-temperature response of rice developing seed, which will shed new light on the improvement of rice grain quality under heat stress.

    Materials and methods

    Plant materials

    Two indica rice varieties with different starch quality, 9311 and Guangluai4 (GLA4), were used as materials. 9311 is a heat-sensitive variety, which displays low amylose content with good starch quality; while GLA4 is known to be the parental variety of HT54, an indica breeding line with heat tolerance, and thus GLA4 is possibly heat tolerant, which shows high amylose content with poor starch quality[18,19]. Rice growth conditions, sample treatment and collection were conducted as previously described[11].

    Protein extraction

    Husk, pericarp and embryo were detached from immature rice grains on ice[20]. Rice endosperm was then ground with liquid nitrogen, and the cell powder was sonicated 10 rounds of 10 s sonication and 15 s off-sonication on ice in lysis buffer (6 M Guanidine hydrochloride, pH 7.8−8.0, 0.1% Protease Inhibitor Cocktail) using a high intensity ultrasonic processor. Following lysis, the suspension was centrifuged at 14,000 g for 40 min at 4 °C to remove the debris. The supernatant was collected, and the protein concentration was estimated using BCA assay (Pierce BCA Protein assay kit, Thermo Fisher Scientific, Waltham, MA, USA) before further analysis.

    Trypsin digestion

    The protein mixture was reduced by DTT with the final concentration of 10 mM at 37 °C for 1 h, alkylated by iodoacetamide with a final concentration of 50 mM at room temperature in the dark for 0.5 h, and digested by trypsin (1:50) at 37 °C for 16 h. Then the sample was diluted by adding trifluoroacetic acid (TFA) to the final concentration of 0.1%. The enzymatic peptides were desalted on a Sep-Pak C18 cartridge (Waters, Milford, MA, USA), concentrated by lyophilization and reconstituted in precooled IAP buffer (50 mM MOPS-NaOH PH 7.2, 10 mM Na2HPO4, 50 mM NaCl) for further analysis.

    Affinity enrichment of ubiquitinated peptides

    The peptides solution was incubated with prewashed K-ε-GG antibody beads (PTMScan Ubiquitin Remnant Motif (K-ε-GG) Kit), and gently shaken at 4 °C for 1.5 h. The suspension was centrifuged at 2,000 g for 30 s, and the supernatant was removed. The Anti-K-ε-GG antibody beads were washed with IAP Buffer three times and with ddH2O three times. The peptides were eluted from the beads with 0.15% trifluoroacetic acid (TFA). Finally, the eluted fractions were combined and desalted with C18 Stage Tips.

    LC-MS/MS and data analysis

    LC-MS/MS analysis were performed using the methods of Pang et al.[11]. Raw mass spectrometric data were analyzed with MaxQuant software (version 1.3.0.5) and were compared with the indica rice protein sequence database (Oryza sativa subsp. indica-ASM465v1). Parameters were set according to Pang et al.[11]. All measurements were obtained from three separate biological replicates.

    Bioinformatics methods

    Quantification of the modified peptides was performed using the label-free quantification (LFQ) algorithm[11]. Differentially ubiquitinated sites (proteins) in response to high-temperature were identified by Student's t-test (p < 0.05, log2(fold-change) > 1) with at least two valid values in any condition or the ubiquitination sites that exhibited valid values in one condition (at least two of three replicates) and none in the other.

    Subcellular localization was performed using CELLO database (http://cello.life.nctu.edu.tw). Gene Ontology (GO) annotation proteome was derived from the AgriGO (http://bioinfo.cau.edu.cn/agriGO/). The differential metabolic profiles were visualized with MapMan software (version 3.6.0RC1). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation was performed by using KEGG Automatic Annotation Server (KAAS) software. A p-value of < 0.05 was used as the threshold of significant enrichment. SWISS-MODEL was used to generate the tertiary structure of GBSSI (SWISS-MODEL, http://swissmodel.expasy.org/). The figures were annotated with Adobe Illustrator (Adobe Systems, San Jose, CA, USA).

    Results

    Overview of the ubiquitomic analysis

    To elucidate how high-temperature stress influences rice developing endosperm at the ubiquitination level, a label-free analysis was performed to quantify ubiquitome from two indica rice varieties under normal (9311-C and GLA4-C) and high-temperature conditions (9311-H and GLA4-H). The distribution of mass error of all the identified peptides was near zero and most of them (71.5%) were between -1 and 1 ppm, suggesting that the mass accuracy of the MS data fits the requirement (Fig. 1a). Meanwhile, the length of most peptides distributed between 8 and 42, ensuring that sample preparation reached standard conditions (Fig. 1b).

    Figure 1.  Characteristics of the ubiquitinated proteome of rice endosperm and QC validation of MS data. (a) Mass error distribution of all identified ubiquitinated peptides. (b) Peptide length distribution. (c) Frequency distribution of ubiquitinated proteins according to the number of ubiquitination sites identified.
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    In all endosperm samples, a total of 437 ubiquitinated peptides were identified from 246 ubiquitinated proteins, covering 488 quantifiable ubiquitinated sites (Supplemental Table S1). Among the ubiquitinated proteins, 60.6% had only one ubiquitinated lysine site, and 18.7%, 8.1%, 5.3%, or 7.3% had two, three, four, or five and more ubiquitinated sites, respectively. In addition, four proteins (1.6%, BGIOSGA004052, BGIOSGA006533, BGIOSGA006780, BGIOSGA022241) were ubiquitinated at 10 or more lysine sites (Fig. 1c, Supplemental Table S1). The proteins BGIOSGA008317 had the most ubiquitination sites with the number of 16. It was noted that besides ubiquitin, two related ubiquitin-like proteins NEDD8 and ISG15 also contain C-terminal di-Gly motifs generated by trypsin cleavage, and the modifications of these three proteins cannot be distinguished by MS[21]. Here, the di-Gly-modified proteome therefore represents a composite of proteins modified by these three proteins. However, the sites from NEDD8 or ISG15 modifications were limited because they mediate only a few reactions in cells[21].

    Properties of ubiquitinated proteins and motifs

    To better understand the lysine ubiquitome changes in rice endosperm induced by high-temperature, we performed a Gene Ontology (GO) functional annotation analysis on all identified ubiquitinated proteins (Fig. 2a). In the biological process GO category, 'metabolic process' and 'cellular process' were mainly enriched, accounting for 75.1% and 74.1% of ubiquitinated proteins, respectively. In addition, 34.6% proteins were associated with 'response to stimulu', emphasizing the regulatory role of ubiquitination modification in response to high-temperature stress. From the cellular component perspective, ubiquitinated proteins were mainly associated with 'cellular anatomical entity' (99.4%), 'intracellular' (84.4%) and 'protein-containing complex' (29.9%). The molecular function category result suggested that these proteins were largely involved in 'binding' (62.7%), 'catalytic activity' (43.4%) and 'structural molecule activity' (16.5%). Furthermore, subcellular location annotation information indicated that 34.7%−39.4% proteins were located in the cytoplasm, and other were mostly located in the nucleus (23.5%−27.7%), plasma membrane (9.4%−11.4%), and chloroplast (9.6%−12.8%) (Fig. 2b). It is noteworthy that the ubiquitinated proteins located in the cytoplasm were decreased in high-temperature environments in both varieties.

    Figure 2.  Analysis of ubiquitinated proteins and motifs. (a) Gene ontology (GO) functional characterization of ubiquitinated proteins. (b) Subcellular localization of ubiquitinated proteins. From the inside out, the ring represents 9311-C, 9311-H, GLA4-C and GLA4-H, respectively. (c) Motif enrichment analysis of ubiquitinated proteins.
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    The following two significantly enriched motifs from all of the identified ubiquitinated sites were identified using MoDL analysis: [A/S]xKub and Kubxx[E/Q/R/V]x[E/G/L/P/Q/R/Y], which covered 84 and 100 sequences, respectively (Fig. 2c). Further analysis showed that the conserved alanine (A) and glutamic acid (E) were included in upstream and downstream of the ubiquitinated lysine sites in rice endosperm. A similar phenomenon also occurred in rice leaf[14], wheat leaf[22], and petunia[23], indicating that alanine (A) and glutamic acid (E) were likely to be the specific amino acids in conserved ubiquitination motifs in plants. Additionally, serine (S) was enriched at the position -2 (upstream) of the ubiquitinated lysine, while various amino acids such as arginine (R), glutamic acid (E), glutamine (Q), valine (V) were found at positions +3 and +5 (downstream).

    A temperature-regulated rice endosperm ubiquitome

    To detect possible changes in rice endosperm ubiquitome attributable to high-temperature stress, we then performed LFQ analysis on all quantifiable ubiquitination sites within our dataset. As shown in Fig. 3a, more ubiquitinated proteins, peptides and sites were detected in the treatment groups (9311-H and GLA4-H), suggesting that exposure to high-temperature stress may increase the ubiquitination events in rice endosperm. Only 282 common ubiquitinated sites in 158 proteins were quantifiable for all sample groups due to reversible ubiquitination induced by high-temperature (Fig. 3b). Principal component analysis (PCA) showed that three repeats of each sample clustered together, and four groups were clearly separated (Fig. 3c). Furthermore, the differentially expression profiles of ubiquitination sites (proteins) in 9311 and GLA4 under high-temperature stress were depicted to further understand the possible changes (Fig. 3d). Where LFQ values were missing, the data were filtered to identify those ubiquitination sites with a consistent presence/absence expression pattern. These analyses yielded 89 ubiquitination sites that were only present in 9311-H and six that were only present in 9311-C (Fig. 3d, Supplemental Table S2). Similarly, 51 differentially expressed ubiquitination sites were present in GLA4-H and 13 ubiquitination sites only occurred in GLA4-C (Fig. 3d & Supplemental Table S3). Beyond that, a total of 113 and 50 significantly changed ubiquitination sites (p < 0.05, log2(fold-change) >1) were screened out in 9311 and GLA4, respectively (Fig. 3d, Supplemental Tables S4 & S5). For subsequent comparative analysis, the ubiquitination expression profiles with consistent presence/absence and ubiquitination sites with significant differences in statistical testing were combined and named as 9311-Up, 9311-Down, GLA4-Up, and GLA4-Down, respectively (Fig. 3d). The number of significantly up-regulated ubiquitination sites was far greater than down-regulated ubiquitination sites in both 9311 and GLA4 varieties. These findings indicated that high temperature not only induced the occurrence of ubiquitination sites, but also significantly upregulated the intensity of ubiquitination. Beyond that, the magnitude of the up-regulation in 9311 was higher than that in GLA4 (Fig. 3b & d), indicating that the ubiquitination modification of heat-sensitive varieties was more active than heat-resistant varieties in response to high-temperature stress.

    Figure 3.  A temperature regulated rice endosperm ubiquitome. (a) The number of ubiquitinated proteins, peptides and sites detected in four group samples. (b) Venn diagram of ubiquitination sites (proteins) detected in four group samples. (c) PCA based on ubiquitination intensity across all four sample groups with three biological repetitions. (d) Differentially expression profiles of ubiquitination sites (proteins) in 9311 and GLA4 under high-temperature stress. The expression profiles of selected ubiquitination sites (p < 0.05, log2(fold-change) >1) were normalized using the Z-score and presented in a heatmap.
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    To further investigate the ubiquitination regulatory pattern under high temperature stress in two varieties, four groups with significantly regulated sites were analyzed. There were 37 ubiquitination sites showed the same regulatory trend in 9311 and GLA4, accounting for 17.8% and 32.5% of the total differentially expressed sites in 9311 and GLA4, respectively. Among them, 36 ubiquitination sites were upregulated and one site was downregulated (Fig. 4a). In addition, 159 upregulated ubiquitination sites and three downregulated sites were only present in 9311, while 53 upregulated sites and 15 downregulated sites were only present in GLA4. Moreover, nine ubiquitination sites showed opposite regulatory trends in 9311 and GLA4. A similar regulatory trend of ubiquitination proteins is shown in Fig. 4b. It is noted that some proteins had both upregulated and downregulated ubiquitination sites (Supplemental Tables S6 & S7), indicating that significant differences in ubiquitination were, to some extent, independent of protein abundance.

    Figure 4.  Comparison of differentially ubiquitinated sites and proteins in 9311 and GLA4 under high-temperature stress.
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    Functions for differentially expressed ubiquitinated proteins

    To understand the function of ubiquitination in response to the high-temperature stress of rice endosperm, we conducted GO enrichment-based clustering analysis of the differentially ubiquitinated proteins in 9311 and GLA4 at high temperature, respectively (Fig. 5). In the biological process category of 9311, proteins were relatively enriched in the carbohydrate metabolic process, polysaccharide metabolic process, starch biosynthetic process, cellular macromolecule localization, protein localization, intracellular transport, and phosphorylation (Fig. 5). For the molecular function analysis, we found that the proteins related to kinase activity, nucleotidyltransferase activity, phosphotransferase activity, and nutrient reservoir activity were enriched (Fig. 5). The two principal cellular components were intrinsic component of membrane and integral component of membrane (Fig. 5). There was no significantly enriched GO term in the GLA4 group due to the dataset containing relatively few proteins, and thus, further enrichment analysis was conducted on the proteins that were common to both varieties. The results showed that proteins were over-represented in carbon metabolism, including starch biosynthesis and metabolism, glucan biosynthesis and metabolism, and polysaccharide biosynthesis and metabolism (Fig. 5), indicating the importance of carbohydrate synthesis and metabolism in the ubiquitination regulatory network.

    Figure 5.  Enrichment analysis of differentially expressed ubiquitinated proteins based on Gene Ontology (GO) terms.
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    To identify pathways which were differentially ubiquitinated under high-temperature stress, the KEGG pathway-based clustering analysis was conducted. The results showed that the differentially ubiquitinated proteins in both 9311 and GLA4 were mostly abundant in the pathways of carbohydrate metabolism, starch and sucrose metabolism, folding, sorting and degradation, translation, ribosome, and protein processing in endoplasmic reticulum (Fig. 6a). In the 9311 group, the pathways of carbohydrate metabolism, starch and sucrose metabolism, glycosyltransferases, glycolysis, and energy metabolism were enriched in the differentially ubiquitinated proteins (Fig. 6b); while there was no significantly enriched KEGG pathway in the GLA4 group. We further found the proteins that were common to both varieties were only significantly enriched in the starch and sucrose metabolism pathways (p = 0.04). The ubiquitination proteins involved in the starch and sucrose metabolism mainly include: sucrose hydrolysis (SUS, FK, UGPase), and starch synthesis (AGPase, GBSSI, BEI, BEIIb, PUL, PHO1), which are discussed below.

    Figure 6.  KEGG classification and enrichment analysis of differentially ubiquitinated proteins. (a) Number of differentially ubiquitinated proteins based on KEGG classification in 9311 and GLA4. (b) KEGG enrichment analysis of differentially ubiquitinated proteins in 9311.
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    Discussion

    Although many reports have described specific examples of ubiquitination in rice defense responses[13,15,16], our knowledge on global changes in the developing endosperm ubiquitome under high-temperature stress is still lacking. In this study, a label-free quantitative proteomic analysis of ubiquitination was applied to examine the high-temperature induced ubiquitination change of two indica rice varieties (9311 and GLA4) with distinct starch quality. We identified many new lysine modification sites on proteins involved in various pathways, highlighting the complexity of the ubiquitination-mediated regulatory system in high-temperature stress responses in rice.

    Ubiquitination of heat shock proteins and transcription factors under high-temperature stress

    Heat shock proteins accumulate under various stresses and play important roles in plant defenses against abiotic stresses[24,25]. Research has shown that a number of heat shock proteins were prominent in the rice ubiquitome network, of which OsHSP71.1, and OsHSP82A showed increased ubiquitination levels under chitin and flg22 treatment[15]. Here, seven lysine residues on five heat shock proteins possessed ubiquitination modification in rice endosperm. Three sites (BGIOSGA011420-K78, BGIOSGA026764-K99, BGIOSGA029594-K106) showed significant up-regulation in 9311 under high-temperature stress, while in GLA4, the ubiquitination level of BGIOSGA011420-K78 was down-regulated. This differential ubiquitination of heat-tolerant and heat-sensitive varieties provided a basis for studying the regulation of post-translational modification of heat shock proteins under high-temperature stress, despite the regulatory role of those heat shock proteins being still unclear.

    Transcription factors (TFs) play an essential role in the regulation of gene expression. A total of three transcription factors were identified in the ubiquitination dataset, of which two were NAC family members. As one of the largest plant-specific TF families, NAC is involved in the responses to abiotic and biotic stresses[26]. The ubiquitination modification of K173 in BGIOSGA018048 was specifically expressed in the 9311-H group, which may affect the stress resistance level in high-temperature environments. In addition, two sites K148 and K149 of ERF TF family member BGIOSGA024035 was downregulated in GLA4 under high-temperature stress. This differential ubiquitination was likely to affect the expression of related genes regulated by this transcription factor.

    Sucrose and starch metabolism are modified by ubiquitination under high-temperature stress

    Ubiquitination affects sucrose hydrolysis

    The results of GO and KEGG enrichment analysis of differential ubiquitination proteins indicated that the sucrose and starch metabolic pathway was largely affected by ubiquitination regulation under high-temperature stress (Figs 5 & 6). The ubiquitination sites involved in sucrose and starch metabolism are listed in Table 1. To assess how high-temperature stress affects the crucial pathway, the significantly differential ubiquitination sites in 9311 and GLA4 were displayed in the heatmap of specific proteins (Fig. 7).

    Table 1.  Ubiquitination sites related to sucrose and starch metabolism in rice endosperm.
    Gene nameAnnotationProtein entryModification site(s)
    SUS1Sucrose synthase 1BGIOSGA010570K172, K177
    SUS2Sucrose synthase 2BGIOSGA021739K160, K165, K176, K804
    SUS3Sucrose synthase 3BGIOSGA026140K172, K177, K541, K544, K588
    FKFructokinaseBGIOSGA027875K143
    UGPaseUDP-glucose pyrophosphorylaseBGIOSGA031231K27, K150, K303, K306
    AGPS1ADP-glucose pyrophosphorylase small subunit 1BGIOSGA030039K94, K464, K484
    AGPS2ADP-glucose pyrophosphorylase small subunit 2BGIOSGA027135K106, K132, K385, K403, K406, K476, K496
    AGPL2ADP-glucose pyrophosphorylase large subunit 2BGIOSGA004052K41, K78, K134, K191, K227, K254, K316, K338, K394, K396, K463, K508, K513
    AGPL3ADP-glucose pyrophosphorylase large subunit 3BGIOSGA017490K509
    GBSSIGranule bound starch synthase IBGIOSGA022241K130, K173, K177, K181, K192, K258, K371, K381, K385, K399, K462, K517, K530, K549, K571, K575
    BEIStarch branching enzyme IBGIOSGA020506K103, K108, K122
    BEIIbStarch branching enzyme IIbBGIOSGA006344K134
    PULStarch debranching enzyme:PullulanaseBGIOSGA015875K230, K330, K431, K736, K884
    PHO1Plastidial phosphorylaseBGIOSGA009780K277, K445, K941
     | Show Table
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    Figure 7.  Sucrose and starch pathway at the ubiquitination levels in rice endosperm under high-temperature stress.
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    In cereal endosperm, sucrose is the substrate for the biosynthesis of starch. The formation of glucose 1-phosphate (G1P, used in starch synthesis, see below) from sucrose requires a series of enzymes[27]. Here, we found that sucrose synthase 1 (SUS1), SUS2, SUS3, fructokinase (FK), and UDP-glucose pyrophosphorylase (UGPase) were ubiquitinated among all sample groups (Table 1, Fig. 7). In the ubiquitome of seedling and leaf in japonica rice, ubiquitination sites have been found in SUS1, SUS2, UGPase, and FK, which were related to sucrose hydrolysis[14,15]. SUS catalyzed the process of cleaving sucrose into UDP-glucose (UDPG) and fructose. Two ubiquitination sites, K172 and K177, were identified in SUS1 in rice endosperm, which were also found in rice leaves[14]. A total of four ubiquitination sites were identified in SUS2, two of which were also reported in rice seedling and leaf, indicating the conservation of the lysine residues in different rice tissues. It was noted that all four ubiquitination sites in SUS2 were upregulated in high-temperature environments, although the regulated sites of 9311 and GLA4 were different. In 9311, the ubiquitination levels of K160, K174, and K804 were increased, while GLA4 was only upregulated in K176. The ubiquitination sites K541, K544, and K588 in SUS3 were screened from developing rice seeds for the first time. In addition, SUS3 had two completely overlapping sites K172 and K177 with SUS1, and it was difficult to determine which enzymes the two sites belonged to. The ubiquitination levels of SUS3-K541 and SUS3-K544 in 9311 significantly increased in high-temperature environments, while there was no significant difference in the ubiquitination level of SUS3 in GLA4. Overall, the ubiquitination sites of SUS in rice endosperm were located in the functional domain except for SUS2-K804, reflecting the importance of ubiquitination regulation in SUS.

    UGPase catalyses the conversion of glucose 1-phosphate and UTP into UDPG[28]. Research has shown that the mutation of UGPase gene lead to chalky endosperm[29]. As shown in Table 1, four ubiquitination sites K27, K150, K303, and K306 were identified in rice endosperm, which were completely inconsistent with the seven ubiquitination sites in rice seedlings and two in leaves[14,15], reflecting the tissue specificity. We speculated that the UGPase with different modification sites may play different regulatory roles in metabolic pathways in different tissues. Under high-temperature stress, the ubiquitination level of UGPase-K27 was 8.1-fold up-regulated. Liao et al.[10] demonstrated that the expression of UDPase was down-regulated in both heat-tolerant and heat-sensitive rice lines under high temperature conditions, which could reasonably explain the significant up-regulation of UGPase-K27 ubiquitination level. The ubiquitination site K143 of FK was also reported in seedling tissues[15].

    Ubiquitination of ADP-glucose pyrophosphorylase (AGPase)

    The AGPase reaction represents the first committed step of starch biosynthesis[27]. A total of 22 lysine ubiquitination sites were identified in four AGPase subunits (AGPL2, AGPL3, AGPS1, AGPS2). AGPL2 had 13 ubiquitination sites, of which six were located in NTP_transferase domain, including K254, K338, K191, K134, K227, and K316. High-temperature stress resulted in an increase in the ubiquitination level of K254 in both 9311 and GLA4, and significant upregulation of K508 and K513 in 9311, as well as K191, K227, and K316 in GLA4. In contrast, AGPL2-K394 were significantly downregulated in GLA4. AGPL3 contained one ubiquitination site K509, and the modification level of AGPL3-K509 was up-regulated in high-temperature environments in 9311. AGPS1 had one specific ubiquitination site K464 and another two sites K94 and K484 that completely overlapped with AGPS2-K106 and AGPS2-K496, respectively. The modification levels of K464 and K484 significantly increased in high-temperature environments in 9311, and K94 was significantly up-regulated in both varieties. There were seven ubiquitination sites in AGPS2 in rice endosperm, which were different with the sites found in rice leaves[14]. In addition to the two sites that overlapped with AGPS1, AGPS2 had another two ubiquitination sites (K406 and K132) that upregulated in high-temperature environments.

    Ubiquitination regulates amylose biosynthesis

    Amylose content is one of the key determinants that strongly influence rice grain quality[30]. The biosynthesis of amylose requires the catalytic effect of granule-bound starch synthase I (GBSSI)[30,31]. Here, a total of 16 ubiquitination sites were identified in GBSSI (Table 1, Fig. 8a). Among these ubiquitination sites, six lysine residues (K130, K173, K177, K181, K192, K258) were located in glycosyltransferase 5 (GT5) domain, and three sites (K399, K462, K517) were located in GT1 domain (Fig. 6), indicating the important role of ubiquitination regulation of GBSSI. Under high-temperature stress, the ubiquitination levels of six sites (K130, K177, K399, K381, K385, K549) increased in two indica rice varieties, while one sites (K258) showed downregulation in 9311 (Fig. 8a). Numerous studies had described that the amylose content was reduced under high-temperature stress in rice[5,7], which might be due to the degradation of GBSSI proteins caused by the increased significantly up-regulated ubiquitination sites. These ubiquitination sites identified in rice GBSSI with significant differences under high-temperature stress were expected to become a new breakthrough point for the improvement of starch quality.

    Figure 8.  Structure of GBSSI. (a) Domain structure of GBSSI and ubiquitination sites with significant differences in response to high-temperature stress. (b) 3D model of GBSSI and the relationship between ubiquitination sites K462 and ADP, SO4 (salt bridge or hydrogen bond).
    DownLoad: Full-Size Img PowerPoint

    To further determine the regulatory role of the ubiquitination sites in GBSSI, SWISS-MODEL was used to predict 3D structural model. As shown in Fig. 8b, GBSSI had three SO4 (sulfate ions) and one ADP ligand. These ligands interact with GBSSI through hydrogen bonds and salt bridges. Three sites, K447, R458, and K462, were associated with SO4 through salt bridges, while G100, N265, Q412, K462, and Q493 interact with the hydrogen bonds of ADP in GBSSI[32,33]. Based on this finding, it can be reasonably inferred that the K462 site with ubiquitination modification located in the GT1 domain played an important role in the interaction between GBSSI, SO4, and ADP. An in-depth investigation was necessary to gain a more comprehensive understanding of the regulatory function of ubiquitination modification at GBSSI-K462, although there was no significant difference in the ubiquitination level under high-temperature stress.

    Ubiquitination regulates amylopectin biosynthesis

    Amylopectin, the major component of starch, is synthesized by the coordinated action of multiple enzymes including soluble starch synthase (SSs), starch branching enzyme (BEs), starch debranching enzyme (DBEs), and phosphorylases (PHOs or Phos) with ADPG as a substrate. In this study, ubiquitination sites were detected in BEs, DBEs, and Phos.

    BEs, covering two isoforms, BEI and BEII, are responsible for catalyzing the formation of α-1,6-glucosidic linkages of amylopectin[34]. There were three ubiquitination sites (K103, K108, and K122) identified in BEI (Fig. 9a). K122 was the first amino acid in the carbohydrate-binding module 48 (CBM48) domain. Sequence alignment analyses of BEs from eight plants revealed K122 was conserved among all plants' BEI (Fig. 9a), suggesting a high probability of the functional effects of ubiquitination modification at this site. In high-temperature environments, ubiquitination levels of K108 and K122 were significantly up-regulated in 9311, while no significantly regulated ubiquitination sites of BEI were observed in GLA4. Only one ubiquitination site, K134, was found in BEIIb (Fig. 9a). The ubiquitination levels showed a slightly upward trend with no significant differences in high-temperature environments in both varieties. These changes could be one of the reasons for increased gelatinization temperature and relative crystallinity of rice starch in response to high-temperature[5].

    Figure 9.  Domain structure of (a) BEs, (b) PUL and (c) Pho1 as well as their ubiquitination sites with significant differences in response to heat stress. Residues in red indicate the ubiquitination site. Non-ubiquitinated residues are shown in dark grey.
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    DBEs consists of isoamylase (ISA) and pullulanase (PUL) with catalytic function for hydrolyzing α-1,6-glucosic linkages[35]. In the present study, we found that only PUL was ubiquitinated in rice endosperm (Fig. 9b). Among five ubiquitination sites (K230, K330, K432, K736, and K884) identified in PUL, K230 was located in the PULN2 domain, while K330 was in the CBM48 domain. Under high-temperature stress, K330 showed completely opposite regulatory trends in two cultivars. In addition, the ubiquitination level of K884, located in the DUF3372 domain, was significantly up-regulated in 9311. Previous study has reported that the expression of PUL was significantly up-regulated in 9311 under high-temperature stress, while GLA4 showed down-regulation in PUL abundance[11]. Consequently, there might be two possible functions of these ubiquitination sites. One possibility is that ubiquitination sites were unrelated to protein degradation; instead, they regulated the biosynthesis of amylopectin by affecting other functions of the protein. Secondly, ubiquitination sites were associated with protein degradation, and the levels of ubiquitination modification were based on protein abundance, resulting in a completely consistent regulation of ubiquitination modification and protein abundance under high-temperature stress.

    PHOs, including two types, Pho1/PHO1 and Pho2/PHO2, are responsible for the transfer of glucosyl units from Glc-1-P to the non-reducing end of a-1,4-linked glucan chains[36]. Pho1 is a temperature-dependent enzyme and considered crucial not only during the maturation of amylopectin but also in the initiation process of starch synthesis[37,38]. The three ubiquitination sites (K277, K445, K941) identified in Pho1 were located in two phosphorylase domains. We found that two sites, Pho1-K277 and Pho1-K445, were only ubiquitinated in high-temperature environments in 9311 and GLA4, respectively. Pang et al.[11] has demonstrated that the protein abundance of Pho1 decreased under high-temperature stress, especially in GLA4. Satoh et al.[38] reported that the functional activity of Pho1 was weakened under conditions of high temperature and its function might be complement by one or more other factors. Hence, these ubiquitination modifications that specifically occurred in high-temperature environments might be related to the degradation of Pho1 proteins.

    Ubiquitination affects ribosomal systems under high-temperature stress

    As a factory for protein synthesis in cells, the ribosome is an extremely crucial structure in the cell[39]. It has been proven that multiple ribosomal subunits were abundantly ubiquitinated in Arabidopsis and wheat[22]. In the present study, 57 ubiquitination sites involving 33 ribosome subunits were identified in 40S and 60S ribosome complexes in rice. Under high-temperature stress, the ubiquitination levels of some sites were significantly upregulated or downregulated, implying that ubiquitination of ribosomal proteins is likely to be an important regulatory mechanism in high-temperature response in rice endosperm. The results of GO and KEGG enrichment analysis indicated that the ribosome system was one of the most active systems for ubiquitination regulation under high-temperature stress. We speculated that the ubiquitin-proteasome system might be involved in the removal of subunits or entire ribosomes that were improperly folded in high-temperature environments. As shown in Fig. 10, the S10e, L18Ae, S27Ae, L9e, S3e, S28e, S20e, and S2e subunits were significantly up-regulated in 9311, while L13e subunits showed a completely opposite regulatory trend at the ubiquitination sites K81 and K88. In GLA4, the ubiquitination levels of S10e, S27Ae, L10Ae, L9e, S3e, S2e, and L4e showed a significant increase, while the ubiquitination level of L17e was significantly down-regulated under high-temperature stress. A total of seven ubiquitination sites involving S10e, S27Ae, L9e, S3e, and S2e subunits were jointly up-regulated in both two varieties. These sites might be related to the degradation of improperly folded ribosome subunits under high-temperature stress, while other ubiquitination sites with variety specificity might be associated with ribosomal function.

    Figure 10.  Ribosome system at the ubiquitination levels in rice endosperm under high-temperature stress. Grey shadings represent ubiquitinated proteins with no significant differences under heat stress. Red and blue shadings indicate up-regulated and down-regulated ubiquitinated proteins, respectively. Orange shading displays a combination of up- and down-regulated ubiquitinated sites in the same ubiquitinated protein.
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    In conclusion, this study provides the first comprehensive view of the ubiquitome in rice developing endosperm, and demonstrated that ubiquitination has diverse functions in the high-temperature response of rice endosperm by modulating various cellular processes, especially the sucrose and starch metabolism. Comparative analysis of the temperature-induced ubiquitination status revealed some similarities and more interesting differences between 9311 and GLA4. These differences might be the reason for the different qualities formation of the two indica rice varieties, which could provide potential genetic resources for the improvement of the heat resistance in rice. Considering the diversity of ubiquitination modification, it is worthwhile to further validate and explore the function and regulatory mechanism of the key targets and key pathways. The findings provide valuable insights into the role of ubiquitination in response to high-temperature stress and lay a foundation for further functional analysis of lysine ubiquitination in rice.

    Author contributions

    The authors confirm contribution to the paper as follows: study conception and design: Bao J, Pang Y; data collection: Pang Y; analysis and interpretation of results: Pang Y; draft manuscript preparation: Ying Y; Revised manuscript preparation: Ying Y, Pang Y, Bao J. All authors reviewed the results and approved the final version of the manuscript.

    Data availability

    The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

    Acknowledgments

    This work was financially supported by the AgroST Project (NK2022050102) and Zhejiang Provincial Natural Science Foundation (LZ21C130003).

  • The authors declare that they have no conflict of interest.

  • Supplemental Table S1 AFLP adapter and primer sequences used in this study.
    Supplemental Table S2 Degenerate primers used in this study.
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  • Cite this article

    Wang X, Guo L, Zhou R, Liu Y, Hu H, et al. 2022. cDNA-AFLP analysis reveals altered gene expression profiles involved in juice sac granulation in pummelo (Citrus grandis). Fruit Research 2:16 doi: 10.48130/FruRes-2022-0016
    Wang X, Guo L, Zhou R, Liu Y, Hu H, et al. 2022. cDNA-AFLP analysis reveals altered gene expression profiles involved in juice sac granulation in pummelo (Citrus grandis). Fruit Research 2:16 doi: 10.48130/FruRes-2022-0016
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cDNA-AFLP analysis reveals altered gene expression profiles involved in juice sac granulation in pummelo (Citrus grandis)

  • 1.

    School of Horticulture Landscape Architecture, Henan Institute of Science and Technology, Henan 453003, China

  • 2.

    Henan Province Engineering Research Center of Horticultural Plant Resource Utilization and Germplasm Enhancement, Xinxiang 453003, China

  • 3.

    College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, China

  • Received: 27 April 2022
  • Accepted: 08 July 2022
  • Published online: 31 October 2022
Fruit Research  2,  Article number: 16  (2022)  |  Cite this article

Abstract: Citrus fruits produced in China are often affected by granulation. Granulation is an altered physiological state of citrus fruits occurring usually before harvest but whose underlying mechanisms remain elusive. In this study, cDNA-AFLP technology enabled the identification of 116 granulation-associated genes in pummelo (C. grandis) juice sacs. Differentially expressed transcript-derived fragments (TDFs) were shown to be mainly involved in biological regulation and signal transduction, carbohydrate and energy metabolism, nucleic acid, protein metabolism, stress responses, and cell metabolism. Therefore, granulation in pummelo juice sacs seems to involve the following alterations: (1) changes in hormone levels; (2) activation of metabolic pathways related to ATP and sugar synthesis to produce more energy; (3) nucleic acid accumulation and increased protein degradation; (4) activation of stress-responsive metabolic pathways; (5) accelerated juice sac senescence. Our findings provide an overview of differential responses occurring at the transcriptional level in granulated juice sacs, thus revealing new insights into the adaptive mechanisms underlying this altered physiological state in 'Guanximiyou' pummelo (C. grandis) juice sacs.

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    INTRODUCTION

    • Pummelo (C. grandis) is a prevalent plant of the family Rutaceae belonging to evergreen subtropical citrus trees. The 'Guanximiyou' pummelo variety has been widely cultivated in China for more than 400 years, and is known for being rich in carbohydrates, β-carotene, vitamin B1, vitamin B2, vitamin C, calcium, potassium, phosphorous, and other health-promoting compounds[1−4]. 'Guanximiyou' pummelo and its bud mutants 'Hongroumiyou' [Citrus maxima (Burm.) Merr. 'Hongroumiyou'] and 'Sanhongmiyou' [Citrus maxima (Burm.) Merr. 'Sanhongmiyou'] varities are highly affected by juice sac granulation[3].

      Citrus fruits are prone to a variety of physiological disorders during the harvest and storage periods. Granulation is an undesirable condition affecting juice sacs of citrus fruits, which become dry, enlarged, grayish, hardened, and less detachable[1]. Granulation was first reported in navel orange in 1934 by Bartholomew et al.[2] in California, being later reported in many fruits, such as pummelo, grapefruit, lemon, and lime[3, 4]. Granulation is often accompanied by enlarged, dried, stiffened, and inflated juice sacs[4−6]. Granulation eventually leads to decreased nutritional and commodity value, which represents significant economic loss[6, 7].

      In our previous works, granulated juice sacs showed lower contents of citrate and isocitrate, and consequently lower acidity, which could be attributed to increased juice sac degradation. Moreover, granulation was also associated with increased accumulation of mineral elements [i.e., phosphorus (P), copper (Cu), magnesium (Mg), sulphur (S), and zinc (Zn)] in juice sacs, which might be involved in the occurrence of the granulation phenomenon in pummelo[8]. In fact, previous studies suggested that accumulation of mineral elements in juice sacs may be one of the causes leading to granulation in citrus fruits[9, 10]. For instance, Xie et al. found that high levels of P in juice sacs were associated with higher incidence of granulation in C. grandis[6], an observation that was consistent with alterations described in 'Dancy' tangerine[9] and 'Valencia' orange fruits[10] in other studies. In addition, long-term utilization of phosphatic fertilizer in orchards might induce accumulation of P in fruits. In our previous work, Cu concentration was shown to be higher in granulated juice sacs than in normal ones[8], which is in agreement with previous findings that accumulation of Cu in leaves occurred as granulation progressed in two sweet orange cultivars[11]. Collectively, evidence suggests that granulation is likely associated with increased accumulation of mineral elements (especially P, Cu, Mg, S, and Zn) in pummelo juice sacs.

      A variety of complex factors contribute to the occurrence of granulation, such as higher application rate of nitrogen or phosphatic fertilizers, higher irrigation frequency, delayed fruit harvest, and abundant growth after heavy pruning or fertilization[4, 12, 13]. Wu et al. found that abnormal accumulation of lignin in juice sacs was associated with the occurrence of juice sac granulation in pummelo (C. grandis)[3]. Moreover, key genes involved in main lignin synthetic pathways were found to be expressed exclusively in granulated juice sacs[14]. Furthermore, Awasthi & Nauriyal reported that activity of peroxidase and superoxide dismutase was associated with higher incidence rate of granulation[15]. Sharma et al. also found that the activity of enzymes related to antioxidants, phenyl ammonia-lyase, and total phenolic compounds has a strong negative correlation in granulated juice sacs[16]. In contrast, senescence-related enzymes, such as pectin methyl esterase, lipoxygenase, as well as respiration rates or ethylene production were shown to have a strong positive relationship with the occurrence of granulation in 'Kinnow' mandarin[13, 16]. Collectively, previous studies suggest that granulation is a complex and recurrent phenomenon whose underlying molecular mechanisms are largely unknown. Therefore, it is highly important to elucidate the basis of granulation in citrus fruits.

      In this study, cDNA-amplified fragment length polymorphism (cDNA-AFLP) was applied to differentiate normal and granulated C. grandis juice sacs in order to understand differences in gene expression during pummelo juice sac granulation.

    RESULTS

      Granulation-associated genes revealed by cDNA-AFLP

    • Using a total of 256 primer combinations, differentially expressed TDFs were identified in normal and granulated C. grandis juice sacs (Fig. 1). Supplemental Table S1 shows cDNA-AFLP profiles using one EcoR I selective primer and eight Mes I selective primers. As shown in Table 1, 4,424 clear and legible TDFs were obtained in pummelo juice sacs. Interestingly, 116 granulation-associated genes showed significant homology to genes encoding known or putative proteins. Among these, 41 TDFs were detected in normal juice sacs, 61 TDFs were detected in granulated juice sacs, and seven TDFs were upregulated and seven TDFs were downregulated in granulated juice sacs. According to functional analysis, these TDFs were assigned to different biological processes, such as hormone and biological regulation (12 TDFs, 10.08%), carbohydrate and energy metabolism (16 TDFs, 13.45%), protein and nucleic acid metabolism (48 TDFs, 40.34%), lipid metabolism (five TDFs, 4.2%), stress response and defense (13 TDFs, 10.92%), cell metabolism (12 TDFs, 10.08%), and unknown biological processes (13 TDFs, 10.92%) (Fig. 2).

      Table 1.  Summary of transcript-derived fragments (TDFs) in normal and granulated juice sacs of C. grandis.

      Found only in normalFound only in granulatedFound in both juice sacsTotal
      Total TDFs detected5368743,0144,424
      Total differentially expressed TDFs detected688926183
      TDFs produced useable sequence data416114116
      TDFs encoding known or putative proteins385711106
      TDFs encoding predicted, uncharacterized89219
      TDFs without matches in the database1126441

      Figure 1. 

      cDNA-AFLP profiles using one EcoR I selective primer and eight Mes I selective primers. One EcoR I selective primer: EcoR I-AC; Eight Mes I selective primers: Mes I-AA, AG, AC, AT, CC, CG, CT, and CA; Lane 1: Normal juice sacs of C. grandis; Lane 2: Granulated juice sacs of C. grandis; Arrows indicate differentially expressed transcript-derived fragments.

      Figure 2. 

      Functional classification of differentially expressed transcript-derived fragments (TDFs) in normal and granulated juice sacs of C. grandis. Functional classification was performed based on information reported for each sequence in the NCBI database (https://blast.ncbi.nlm.nih.gov/Blast.cgi).

      Validation of expression patterns of differentially expressed TDFs using qRT-PCR

    • As shown in Fig. 3, 20 TDFs were selected for qRT-PCR analysis in order to confirm cDNA-AFLP expression patterns. These TDFs were selected based on significantly different expression patterns in C. grandis granulated juice sacs and a high degree of homology with genes that play very important roles in various metabolic pathways. Expression levels of selected TDFs corroborated cDNA-AFLP findings, except for TDF #246-4 (Fig. 3). This discrepancy might indicate a gene family with complex regulation, which can be identified exclusively by the cDNA-AFLP technique.

      Figure 3. 

      Relative expression levels of transcript-derived fragments (TDFs) in C. grandis normal and granulated juice sacs. (a) Relative expression levels of genes encoding β-amylase 4 (TDF #64-2); cytokinin-O-glucosyltransferase 1 (TDF #94-1); gibberellin 20 oxidase (TDF #13-2); galactose-1-phosphate guanylyltransferases (TDF #200-1); α-galactosidase precursor (TDF #160-1); cytochrome b5 (TDF #123-2); ADP-ribosylation factor 3 (TDF #246-4); 2-oxoglutarate-dependent dioxygenase (TDF #13-1); 1,4-alpha-glucan-maltohydrolase (TDF #20-3); ethylene insensitive 3-like protein (TDF #147-4). (b) Relative expression levels of genes encoding translation initiation factor 4A2 (TDF #14-3); cytochrome P450 (TDF #48-3); auxin down-regulated-like protein (TDF #5-3); cellulose synthase (TDF #249-3); transport protein SEC31 (TDF #34-2); Ca2+-transporting ATPase (TDF #252-3); heat shock protein (TDF #252-1); senescence-associated protein (TDF #5-1); dicer-like protein 4 (TDF #244-6); cell wall-associated hydrolase (TDF #216-3). Results are shown as the mean ± SD of three independent experiments. Different letters above bars indicate significant differences at P < 0.05.

      Concentrations of hormones in normal and granulated juice sacs

    • Four hormone-related genes were found to be potentially involved in the incidence of granulation in pummelo fruits: TDF #5-3 (auxin down-regulated-like protein); TDF #94-1 (cytokinin-O-glucosyltransferase 1); TDF #13-2 (gibberellin 20 oxidase); and TDF #147-4 (ethylene insensitive 3 like protein) (Table 2). Upregulation of hormone-related genes (i.e., TDFs #5-3, 94-1, and 147-4) observed in cDNA-AFLP analysis was further confirmed in qRT-PCR analysis (Fig. 3). To confirm discrepancies in hormone levels in normal and granulated juice sacs in pummelo, the contents of five hormones were determined using UPLC-MS. Contents of gibberellin 3 (GA3), gibberellin 20 (GA20), cytokinin (CK), and zeatin (ZT) were higher in normal juice sacs compared to granulated juice sacs, whereas the content of indole-3-acetic acid (IAA) was lower in normal juice sacs (Fig. 4).

      Table 2.  Homology of differentially expressed cDNA-AFLP fragments with known gene sequences in the database using BLASTX algorithm along with their expression patterns in granulation juice sacs of C. grandis.

      TDF numberSize
      (bp)      		Homologous proteinOrganism of originE-valueDegree of similarity (%)Genbank IDFold change
      Hormone and biological regulation
      48-2292CAAX amino terminal protease familyCucumis melo7E-1890ADN33781.1+
      5-3259Auxin down-regulated-like protein, partialPicea sitchensis5E-0555ADM77850.1+
      6-2158Protein embryo defective 2752Arabidopsis thaliana2E-1261NP_567830.10
      118-3290Expressed proteinOryza sativa5E-2763ABF95726.10
      94-1358Cytokinin-O-glucosyltransferase 1Aegilops tauschii9E-2548EMT28784.1+
      103-1211Nitrate reductaseCucumis sativus1E-3089ADK77877+
      219-5244ARF-GAP domain 2Arabidopsis lyrata subsp. lyrata5E-0943NP_176283.10
      13-2269Gibberellin 20 oxidaseMedicago truncatula4E-4281AES62614.2+
      147-4271EIN3-like (Ethylene insensitive 3) proteinC. melo8E-41100BAB64345+
      195-6197MATE efflux family proteinTheobroma cacao2E-1979EOX90702.10
      115-1355Transmembrane emp24 domain-containing protein p24delta9-likeCrocus sativus3E-6098XP_004143772.1+
      195-1455Multicatalytic endopeptidase complexA. thaliana8E-6984CAA74030.1+
      Carbohydrate and energy metabolism
      134-1192ATP-binding protein-likeA. thaliana2E-1075BAB09414.1+
      249-1311UDP-glucosyltransferase family 1 proteinCamellia sinensis2E-2593ACS87991.1+
      6-1214Fructose-bisphosphate aldolaseLemna minor1E-3394ACD10928.10
      5-4148ATP synthase subunit betaMedicago truncatula2E-1395XP_003627732.1+
      118-2304Glyceraldehyde-3-phosphate dehydrogenase, partialVernicia fordii4E-1194AFJ04516.10
      118-1441Glycosyltransferase, CAZy family GT8Populus trichocarpa5E-7590XP_002312381.1+
      64-2220β-amylase 4Citrus trifoliata2E-2269AFQ33616+
      249-3217Cellulose synthasePopulus tremula × Populus tremuloides5E-1291AAT09895.1+
      141-3499Mitochondrial benzaldehyde dehydrogenaseAntirrhinum majus8E-8980ACM89738.1+
      160-1174α-galactosidase precursorCoffea arabica2E-0462CAJ40777.1+
      13-12692-oxoglutarate-dependent dioxygenasePopulus trichocarpa8E-4889XP_002330269.17.07 ± 0.52
      200-1389Galactose-1-phosphate guanylyltransferasesT. cacao1E-6583EOY12255.1+
      20-32201,4-alpha-glucan-maltohydrolaseSolanum lycopersicum1E-1460NP_001234052.1+
      246-3192ABC transporter family proteinP. trichocarpa1E-1280XP_002310031.20
      221-3123Diacylglycerol kinase-like proteinA. thaliana6E-1169BAB09587.1+
      246-4172ADP-ribosylation factor 3A. lyrata subsp. lyrata4E-9896XP_002869315.10
      65-1363Methylenetetrahydrofolate reductase family protein isoform 3T. cacao7E-4972EOY04345.10
      Protein and nucleic acid metabolism
      228-1243Ribonucleoside-diphosphate reductase
      subunit M1      		A. thaliana2E-3389AEC07222.10
      251-1188BET1P/SFT1P-like protein 14AA. thaliana6E-0778NP_191376.10
      253-2306Class II aaRS and biotin synthetases
      superfamily protein      		A. thaliana5E-4183NP_186925.4+
      130-3193Ribosomal protein L5Citrullus lanatus1E-3096YP_003587255.10
      119-3254Nuclear transport factor 2 family proteinT. cacao1E-2262EOY06196.1+
      27-3224Glutathione S-transferase family proteinT. cacao1E-0762EOY27562.1+
      195-5268BRCA1-associated proteinM. truncatula8E-3973XP_003609376.20
      54-2169Pre-mRNA splicing factor PRP38 family proteinP.trichocarpa2E-2292ERP53525.10
      151-4347Ribonuclease II family proteinA. thaliana2E-5180NP_565418.1+
      127-1180Mitochondrial substrate carrier family protein isoform 2T. cacao2E-2861EOY07093.1+
      15-2349Nuclear transcription factor Y subunit B18M. truncatula1E-0968AFK49668.1+
      15-1392RRNA intron-encoded homing endonucleaseM. truncatula6E-1388XP_003614385.1+
      20-1280Solute carrier family 25 memberM. truncatula6E-2363XP_003615848.20
      221-1256TPA: heterogeneous nuclear ribonucleoprotein A3-like protein 2 isoform 1Zea mays1E-2982DAA58966.10.56 ± 0.06
      217-5194Adenine nucleotide alpha hydrolases-like superfamily proteinT. cacao2E-0696EOY06709.11.86 ± 0.34
      215-1363Transcription regulatorA. thaliana1E-0688NP_171710.4+
      195-4333PLP-dependent transferases superfamily proteinA. thaliana2E-3760NP_191772.1+
      21-221060S ribosomal protein L24-1T. cacao1E-3797EOY23121.1+
      155-3187Valyl-tRNA synthetase/valine-tRNA ligaseT. cacao3E-19
      		75
      		EOY31957.1
      		2.23 ± 0.11
      252-2299ACT domain-containing protein ACR8Ricinus communis2E-3086XP_002509632.10.79 ± 0.03
      151-5
      		347Exosome complex exonuclease RRP44
      homolog A      		R. communis5E-5382XP_002521738.1+
      217-2369Transcription initiation factor TFIID subunit AA. thaliana1E-2277NP_564023.1+
      218-1239Chaperonin 60 alpha subunitArachis diogoi1E-2086ACA23472.10
      31-1293Aspartyl protease family proteinA. thaliana3E-2357XP_002891474.1+
      236-3251Protein kinase domain-containing proteinA. thaliana3E-3080AEE27605.10
      247-1324Importin beta-2 subunit family proteinA. thaliana2E-1676XP_002867489.1+
      253-1263Serine/threonine protein kinase TNNI3KM. truncatula2E-0976XP_003601186.10
      5-2151Amino acid adenylation proteinCalothrix sp. PCC 63039.940YP_007137552.1+
      119-1290Ricin B-like lectin EULS3A. lyrata subsp. lyrata4E-3673XP_002862306.2+
      119-2190Spl1-Related 2 proteinA. thaliana2E-1876CAB56773.1+
      128-1286Chloroplast elongation factor TuB (EF-TuB)Nicotiana sylvestris7E-1290BAA01975.1+
      94-2242Clone 6F8 eukaryotic initiation factor 4A-14 geneNicotiana benthamiana2E-4789JN688263.1+
      34-2343Transport protein SEC31T. cacao2E-0681EOY23302.1+
      91-1199Phosphatase 2C family protein isoform 2T. cacao2E-8387EOY06499.1+
      160-6271Kinase superfamily protein isoform 1T. cacao3E-3478EOY06443.10
      209-3337Ser/Thr phosphatase-containing Kelch repeat domain protein, partialN. benthamiana1E-5090AFN44702.10
      220-3208Pentatricopeptide repeat (PPR) superfamily protein isoform 2T. cacao5E -0851EOY04957.12.25 ± 0.22
      197-1398Ubiquitin-specific protease family C19-related proteinA. thaliana9E-6879NP_564009.1+
      87-2220Tetratricopeptide repeat (TPR)-like superfamily protein isoform 1T. cacao3E-2786EOY33236.12.55 ± 0.06
      209-5319Serine/threonine-protein phosphatase, partialGenlisea aurea3E-5288EPS64063.10
      194-1474Proteasome subunit beta type-4Solanum nigrum6E-7391ADW66147.10
      150-9199Serine/threonine-protein kinase AtPK2/AtPK19R. communis2.851XP_002528702.1+
      123-4246IFA binding proteinLilium longiflorum2E-3774ABM68547.10
      123-3302Dual specificity kinase 1Arabidopsis thaliana3E-2793AEE276350
      26-2324Dephospho-CoA kinaseA. thaliana1E-4369NP_180318.10
      14-3222Translation initiation factor 4A2Z. mays7E-3797AAD20980.10.65 ± 0.01
      244-1302Translation elongation factor, partialAmmopiptanthus mongolicus1E-0588AFC01200.1+
      246-2165Eukaryotic translation initiation factor 5
      isoform 2      		T. cacao3E-0552EOX90767.10
      Lipid metabolism
      123-1278Patellin-5A. lyrata subsp. lyrata3E-1367XP_002872438.10
      141-4209Patellin-5Triticum urartu8E-2771EMS62735
      XP_003623      		0.27 ± 0.02
      195-3347Non-specific lipid-transfer proteinM. truncatula1E-0592596.3+
      197-3327Pleckstrin (PH) and lipid-binding START domains-containing protein isoform 2T. cacao1E-4778EOY34386.1+
      125-2278Glyoxylate/hydroxypyruvate reductase
      A HPR2      		A. lyrata subsp. lyrata1E-2970XP_002889322.1+
      Stress response and defense
      48-1263Trehalose 6-phosphate synthaseNicotiana tabacum3E-1891BAI99252.1+
      220-2208Transcription factor bHLH130M. truncatula4E-2275XP_003590427.11.41 ± 0.06
      123-2189Cytochrome b5N. tabacum9E-2680CAA50575 +
      48-3268Cytochrome P450Citrus sinensis2E-2895AAL24049.1+
      64-1297Cytochrome P450A. thaliana1E-2381NP_176086.1+
      221-2451Cytochrome oxidase subunit 1Curcuma longa1E-1056ABY83898.1+
      218-2341DNA damage-binding protein, partialM. truncatula3E-6467XP003638090.10
      252-1353Heat shock proteinM. truncatula6E-0745XP_003621962.10.36 ± 0.04
      115-2290Stress responsive proteinZ. mays5E-3264NP_001149550.1+
      5-1230Senescence-associated protein
      		Picea abies2E-4596ACA04850.1+
      154-5184Dehydration-induced 19-like proteinGossypium hirsutum8E-0556ADP30960.1+
      27-1271B-box zinc finger proteinBambusa oldhamii7E-0957ACF35275.10
      244-6248Dicer-like protein 4A. thaliana9E-0963NP_197532.3+
      Cell metabolism
      252-3355Ca2+-transporting ATPaseA. thaliana2E-0472NP_195479+
      130-1240Plasma membrane isoform 4T. cacao3E-2983EOY10146.10
      244-2287Cinnamyl-alcohol dehydrogenaseA. thaliana3E-0591AAA99511.1+
      40-1163Clathrin adaptor complexes medium subunit family proteinA. lyrata subsp. lyrata3E-2293XP_002886592.10
      154-3429RAB GTPase homolog A5AA. thaliana1E-1790NP_199563.10.67 ± 0.01
      217-6323Receptor-like kinase binding proteinP. trichocarpa4E-2858XP_002325092.10.87 ± 0.05
      147-3168Calreticulin-like protein
      		Solanum melongena6E-2288BAA85118.13.35 ± 0.12
      16-3238Ycf2 (chloroplast)Gossypium raimondii3E-3796YP_005087735.1+
      143-4350Tetraspanin8T. cacao9E-2469EOY31574.1+
      216-3443Cell wall-associated hydrolaseVibrio cholerae5E-3976ACX81677.10
      200-2283Nucleic acid binding proteinZ. mays5E-4389NP_001152488.1+
      Unknown biological processes
      217-3323Hypothetical protein AT5G07270A. thaliana4E-0959NP_1963440
      236-1256Choline/ethanolamine kinase, putativeRicinus communis4E-3583XP_002525542.1+
      236-2322Uncharacterized protein LOC8268581R. communis3E-3182XP_002530954.10
      249-2196Amino acid transporter, putativeR. communis3E-0339XP_002531860.1+
      8-2168Predicted: monoacylglycerol lipase abhd6-B-likeFragaria vesca subsp. vesca1E-1880XP_004303453.10
      119-4310Domain of uncharacterized protein function 724 6, putative isoform 1T. cacao2E-2268EOX95351.10
      57-1205Predicted: Vitis vinifera peroxidase 3-like mRNAVitis vinifera2E-2191XM_002280238.4+
      100-1318Hypothetical protein CICLE_v10006049mgCitrus clementina6E-14100ESR32793.10
      17-3206Hypothetical protein MTR_2g077840M. truncatula2E-376XP_003596462.10
      197-2335Mitochondrial protein, putativeM. truncatula3E-0488XP_003588355.10
      217-4261Putative ATP synthetase alpha chainOryza sativa subsp. japonica3E-1363AAO72570.10
      154-1202Hypothetical protein CICLE_v10022616mgCitrus clementina7E-2295ESR54213.10
      89-3215Hypothetical protein CICLE_v10033239mgC. clementina3E-19100ESR51519.1+
      TDFs: Transcript-derived fragments. Results are shown as the mean ± SD of at least three independent experiments. Fold change: 0 indicates TDFs only detected in normal juice sacs; + indicates TDFs only detected in granulated juice sacs. Relative expression ratio was obtained by analyzing gel images using PDQuest version 8.0.1 (Bio-Rad, Hercules, CA, USA).

      Figure 4. 

      Granulation led to alterations in hormone content in C. grandis juice sacs. The content of five hormones were measured by ultra-performance liquid chromatography mass-spectrometry (UPLC-MS). Normal juice sacs were considered as negative control. GA3: gibberellin 3; GA20: gibberellin 20, CK: cytokinins; ZT: zeatin; and IAA: indole-3-acetic acid. Error bars represent standard deviations calculated from three biological replicates. Different letters above bars indicate significant differences at P < 0.05.

    DISCUSSION

      Hormone and biological regulation

    • Plant hormones are involved in the growth, development, ripening, and senescence of fruits. As an important regulator, hormones play a very critical role in the regulation of physiological disorders, defense, and stress responses, among other processes[17, 18]. Herein, using cDNA-AFLP technology, four hormone-related genes were found to be involved in the incidence of granulation in pummelo. qRT-PCR (Fig. 3) and UPLC-MS (Fig. 4) analyses further confirmed that the occurrence of granulation might induce changes in the hormone level in pummelo. Higher levels of GA3, GA20, CK, and ZT found in C. grandis normal juice sacs might induce increased cell division rate, and lead to granulation, whereas IAA might alter physiology of juice sacs. Taken together, these results indicated that alterations in hormone contents in C. grandis juice sacs might determine the occurrence of granulation. Our findings provide useful information about the mechanisms underlying the granulation phenomenon in C. grandis juice sacs.

      As shown in Table 2, four TDFs (i.e., TDFs #48-2, 103-1, 115-1, and 195-1) in normal juice sacs and four TDFs (i.e., TDFs #6-2, 118-3, 219-5, and 195-6) in granulated juice sacs related to nutrients transformation and were identified by cDNA-AFLP. CAAX (Carboxyl-terminal three amino acids) protein is involved in the regulation of Rce1 (Ras converting enzyme) activity in cell signaling processes[19]. Nitrate reductase plays a central role in plant nitrogen acquisition by controlling nitric oxide levels[20]. Changes in the expression of genes coding for CAAX amino terminal protease (TDF #48-2) and nitrate reductase (TDF #103-1) in granulated juice sacs might be related to disrupted nitrogen absorption and utilization.

      Carbohydrate and energy metabolism

    • In total, 17 differentially expressed TDFs related to carbohydrate and energy metabolism were found in pummelo juice sacs, among which five TDFs (TDFs #6-1, 65-1, 246-3, 246-4, and 118-2) were found exclusively in normal juice sacs and 12 TDFs (TDFs #221-3, 249-1, 249-3, 5-4, 118-1, 64-2, 244-2, 141-3, 160-1, 200-1, 20-3, and 134-1) were identified exclusively in granulated juice sacs (Table 2, Fig. 3). ATP synthase plays a key role in the cell by providing energy for ATP synthesis[21, 22]. In granulated juice sacs, the gene coding for ATP synthase subunit beta was upregulated, therefore energy levels are likely to be increased in granulated juice sacs. Deposition of both lignin and cellulose accompanied by juice sac granulation is widespread in harvested citrus fruit[23]. This hypothesis is further supported by the observation that ATP-binding protein-like (TDF #134-1), cellulose synthase (TDF #249-3), UDP-glucosyltransferase protein (TDF #249-1), glycosyltransferase, CAZy protein (TDF #118-1), 1, 4-alpha-glucan-maltohydrolase (TDF #20-3), β-amylase 4 (TDF #64-2), and galactose-1-phosphate guanylyltransferases (TDF #200-1) were upregulated in granulated juice sacs (Table 2, Fig. 3). Cellulose synthase belongs to the glycosyl hydrolase family which comprise enzymes that degrade complex sugars into mono- and disaccharides (glucose and cellobiose)[24]. Amylases hydrolyze starch and glycogen, and β-amylase specifically degrades amylose into maltose[25]. Researchers recently found that complex networks of pectin might be promoted by the granulation process[26]. Taken together, it is likely that major metabolic pathways related to ATP synthesis are activated in granulated juice sacs to produce more energy to meet the high demand of stressed juice sacs.

      However, the observed higher mRNA levels of fructose-bisphosphate aldolase (TDF #6-1), glyceraldehyde-3-phosphate dehydrogenase (TDF #118-2), ADP-ribosylation factor 3 (TDF #246-4), and methylenetetrahydrofolate reductase protein gene (TDF #65-1) might enable higher tolerance to stressful conditions in granulation of juice sacs.

      Protein and nucleic acid metabolism

    • Plants have evolved various sophisticated mechanisms for adapting to hostile environments during growth and development. Abiotic stresses demonstrably affect protein and nucleic acid metabolism in plants[27]. Studies with mutants in genes related nucleic acid metabolism revealed that nucleic acid processing, decay, and stability play a significant role in regulating gene expression at a post-transcriptional level in response to abiotic stresses in plants[28]. In plants, transcription and translation are the key steps for fine-tuning gene expression. In particular, during protein metabolism, modulation of global transcription and translation rates allows control over the production of specific proteins[29]. Differentially expressed TDFs found exclusively in granulated juice sacs included nuclear transcription factor Y subunit B18 (TDFs #15-2), transcription regulator (TDFs #215-1), transcription initiation factors TFIID (TDFs #217-2), 4A-14 (TDFs #94-2), chloroplast elongation factor TuB (TDFs #128-1), and translation elongation factor (TDFs #244-1) (Table 2), which might be related to nucleic acid accumulation. Moreover, differentially expressed mitochondrial substrate carrier family protein (TDFs #127-1), importin beta-2 subunit protein (TDFs #247-1), and transport protein SEC31 (TDFs #34-2) in granulated juice sacs suggest that protein transport might be impaired (Table 2, Fig. 3), which strengthens the hypothesis of nucleic acid accumulation in granulated juice sacs. Interestingly, all differentially expressed TDFs found exclusively in granulated juice sacs [i.e., ribonuclease II family protein (TDFs #154-4), 60S ribosomal protein L24-1 (TDFs #21-2), eukaryotic initiation factor (TDFs #94-2), translation elongation factor (TDFs #244-1), eukaryotic translation initiation factor (TDFs #246-2), and chloroplast elongation factor (TDFs #128-1)] (Table 2) could be associated with protein translation, which further indicates that protein translation might be impaired in granulated juice sacs.

      Similarly, differentially expressed TDFs [i.e., phosphatase 2C family protein (TDFs #91-1), ubiquitin-specific protease family C19-related protein (TDFs #197-1), serine/threonine-protein kinase AtPK2/AtPK19 (TDFs #150-9)] related to protein phosphorylation and ubiquitination were upregulated in granulated juice sacs (Table 2), indicating that protein degradation might be increased in granulated juice sacs. Therefore, nucleic acid accumulation and protein degradation might have accelerated granulation in C. grandis juice sacs. Collectively, these findings indicate that impaired nucleic acid and protein metabolism in C. grandis juice sacs can be associated with the granulation phenotype.

      Stress responses

    • Cytochromes P450s and b5 play a key role in the response to biotic and abiotic stresses in plants. Chen et al.[30] found that loss of function of the cytochrome P450 gene CYP78B5 causes giant embryos in rice. Herein, expression levels of genes encoding cytochrome P450 (TDF #48-3, 64-1), b5 (TDF #123-2), and cytochrome oxidase subunit 1 (TDF #221-2) were increased in C. grandis granulated juice sacs (Table 2, Fig. 3), which is in agreement with findings of previous studies reporting that certain cytochrome P450 genes in Arabidopsis were upregulated during biotic stresses, i.e., drought, hormone, high salinity, mechanical wounding, low temperature, herbicide (paraquat), and heavy metal (CuSO4) stress[31]. Thus, differential expression of genes coding for cytochrome P450s, b5, and cytochrome oxidase in C. grandis juice sacs might indicate an adaptation to physiological disorders.

      In plants, double-stranded RNA (dsRNA) is recognized and cleaved by dsRNA-specific RNases named DCL (Dicer-like) enzymes, primarily by DCL4 and then by DCL2, producing 21- to 24-nucleotide double-stranded siRNA duplexes. Then, the antiviral silencing pathway is triggered by the presence of siRNAs, and 21-, 22-, or 24-nucleotide siRNA species mediate cleavage of mRNAs and DNA methylation in plants[32]. Expression of Dicer-like protein-coding genes might indicate that the plant's immune system was activated by biotic or abiotic stress response[33]. Herein, the gene encoding Dicer-like protein 4 was differentially and exclusively expressed in granulated juice sacs (TDF #244-6) (Table 2, Fig. 3), thus suggesting activating the immune defense system of C. grandis likely against granulation in juice sacs.

      Plants under field conditions often encounter a variety of stresses, at times occurring simultaneously. Therefore, stress-responsive proteins are important effectors in plants during response to biotic or abiotic stresses[34, 35]. Under adverse conditions, many proteins have been previously found as differentially expressed in plants in response to bacterial, fungal, or viral infection, as well as to physiological disorders. Heat-shock proteins (HSPs) or the chaperone network are a major component of multiple stress-responses, and are controlled by diverse heat-shock factors which are recruited under stress conditions[34]. In the present study, differential expression of stress-responsive (TDF #115-2) and HSP (TDF #252-1) genes in granulated juice sacs may be related to a response against physiological disorders (Table 2, Fig. 3). Senescence is the final developmental stage of every plant organ, which eventually culminates in cell death. In granulated juice sacs, expression of the senescence-associated protein gene (TDF #5-1) might indicate that this altered physiological state is accompanied by accelerated senescence, dryness, hardness, and degeneration. Taken together, granulation activates stress-responsive metabolic pathways in C. grandis juice sacs, consequently increasing the expression of related genes.

      Cell metabolism

    • In recent research, pectin methylesterase catalyzes the de-methylesterification of homogalacturonans and plays crucial roles in cell wall modification during plant development and fruit ripening[36]. The genes Ca2+-transporting ATPase (TDF #252-3), Ycf2 (chloroplast) (TDF #16-3), and tetraspanin 8 (TDF #143-4) (Table 2) involved in cell wall metabolism were specifically expressed in granulated juice sacs (Table 2, Fig. 3). In addition, mRNA levels of genes encoding plasma membrane isoform 4 protein (TDF #130-1), clathrin adaptor complexes medium subunit family protein (TDF #40-1), receptor-like kinase binding protein (TDF #217-6), and cell wall-associated hydrolase protein (TDF #216-3) were downregulated in granulated juice sacs. Therefore, cell wall formation or biosynthesis might be impaired in granulated juice sacs.

      Conclusions

    • This work reports the first comparative investigation of normal and granulated juice sacs in pummelo (C. grandis) using the cDNA-AFLP technology. In total, 116 granulation-associated cDNA-AFLP products were identified in pummelo juice sacs. Differentially expressed TDFs were shown to be mainly involved in biological regulation and signal transduction, carbohydrate and energy metabolism, nucleic acid, protein metabolism, stress responses, and cell metabolism. Collectively, granulation in pummelo juice sacs seems to be associated with the following alterations: (1) changes in hormone levels; (2) activation of metabolic pathways related to ATP and sugar synthesis; (3) nucleic acid accumulation and increased protein degradation; (4) activation of stress-responsive metabolic pathways; (5) accelerated juice sac senescence (Fig. 5). Therefore, granulation is a complex process. The present study provides a comprehensive view into the differential responses occurring in granulated juice sacs, thus offering new insights into the adaptive mechanisms of 'Guanximiyou' pummelo (C. grandis) juice sacs at the transcriptional level during physiological distress.

      Figure 5. 

      Proposed regulatory network for the granulation phenomenon in C. grandis juice sacs. Red arrows indicate upregulated genes. HSP: heat-shock protein.

    MATERIALS AND METHODS

      Samples

    • Pummelo (C. grandis) 'Guanximiyou' cultivar was used in this study. Fruits were collected from 25-year-old sour orange rootstocks in a pummelo orchard at grown at Yanban village pummelo orchard, Xiaoxi town, Pinghe county, Fujian province, China (E 24°35', N 117°31'), on single-tree replicates for all measurements on 1 October 2020. Fully mature pummelo fruits were harvested until granulation was visible. The degree of granulation was assessed according to the method of previous studies[3, 8, 14]. Normal and granulated juice sacs were collected from the same pummelo tree, a total of nine trees were sampled in the pummelo orchard. Five to ten fruit per tree were chosen from the outer of the mid-upper canopy. All the samples were immediately frozen in liquid nitrogen and stored at −80 °C until RNA isolation.

      RNA extraction and cDNA synthesis

    • Normal and granulated juice sacs were ground in liquid nitrogen, and total RNA was independently isolated from samples using the RNeasy Plant Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. Equal amounts of normal or granulated frozen juice sacs obtained from three pummelo units were mixed as one biological replicate, respectively. Each assay was repeated as three independent experiments, each with three biological replicates. Double-stranded cDNA synthesis was performed following the method proposed by Lu et al.[35].

      cDNA-AFLP analysis

    • cDNA-AFLP analysis was performed according to the methods proposed by Xiao et al.[37]. Double-stranded cDNA was purified using an equal volume of phenol : chloroform : isoamyl alcohol (25:24:1, v/v/v). Subsequently, 500 ng of the resulting double-stranded cDNA was digested using the restriction enzymes EcoR I (10U; TaKaRa Biotechnology, China) at 37 °C for 3 h, and following Mse I (10U; TaKaRa) at 65 °C for 3 h. The resulting restricted products were ligated to AFLP adaptors (EcoR I: 5'-CTCGTAGACTGCGTACC-3', 5'-CATCTGACGCATGGTTAAP-3' and Mse I: 5'-GACGATGAGTCCTGAG-3', 5'-TACTCAGGACTCATP-3') with T4-DNA ligase (TaKaRa) and incubated overnight at 16 °C. Obtained products were pre-amplified with the corresponding pre-amplification primers: EcoR I: 5'- GACTGCGATCCAATTC-3' and Mse I: 5'-GATGAGTCCTGAGTAA-3'. A 100-fold dilution of pre-amplified products was used for the selective amplification using 256 combinations of the primers EcoR I 5'-GACTGCGATCCAATTC+MM-3' and Mse I 5'-GATGAGTCCTGAGTAA+NN-3', where MM and NN represent the following combination of nucleotides: AA, AT, AC, AG, GA, GC, GT, GG, CA, CT, CG, CC, TA, TC, TT, and TG. Final products were mixed with bromophenol blue and separated on 6% (w/v) polyacrylamide gel electrophoresis at 60 W for 3 h. Gels were silver stained to enable visualization of cDNA products. All samples in cDNA-AFLP analysis were submitted to electrophoresis at least three times independently.

      Differential cDNA bands were excised, incubated in 100 µL of double-distilled H2O (ddH2O) for 10 min in a boiling water bath, then centrifuged at 10,000 rpm for 5 min. The supernatant used as template was re-amplified by PCR using the 256 combinations of the selective amplification primers. All positive amplicons were sequenced or ligated into the vector pMD18-T (TaKaRa) and further sequenced to confirm the identity of transcript-derived fragments (TDFs). Finally, differential cDNA sequences were analyzed using BLASTX and BLASTN searching engines (https://blast.ncbi.nlm.nih.gov/Blast.cgi).

      Quantitative real-time RT-PCR (qRT-PCR)

    • qRT-PCR was performed with SYBR PrimeScript RT-PCR Kit (TaKaRa) according to the manufacturer's instructions. cDNA synthesis was performed with a mix of random primers and oligo(dT) primers provided in the kit using 500 ng of total RNA. β-actin gene served as an internal control. All qRT-PCR primers used are given in Supplemental Table S2. qPCR analysis was conducted in an ABI 7500 thermocycler (Applied Biosystems, Foster City, CA, USA). qPCR mixture consisted of 10 μL of 2× SYBR Premix Ex Taq DNA polymerase, 0.2 μL (200 nM) each of specific primer pairs, 2 μL of diluted reverse-transcribed cDNA, and 0.4 μL of ROX Dye II, in a 20 μL total reaction volume as per manufacturer's instructions. Quantification was conducted according to a previously described method[38]. Experiments were repeated at least three times independently using biological replicates.

      Ultra-performance liquid chromatography mass-spectrometry (UPLC-MS) analysis

    • Hormone content in normal or granulated C. grandis juice sacs was analyzed using UPLC-MS. Approximately 100 mg of juice sac powder was weighed and transferred to a 1.5-mL centrifuge tube. Then, 500 μL of extracting solution (isopropyl alcohol : ddH2O : hydrochloric acid at a ratio of 2:1:0.002, v/v/v) and 50 μL of four standard samples were added, and tubes were slowly inverted to allow sufficient mixing at 4 °C for 30 min. Subsequently, 1,000 μL of trichloromethane was added to the mixture, and tubes were incubated at 4 °C for 30 min, followed by centrifugation at 14,000 rpm for 5 min. Supernatants were transferred to new tubes and blow-dried with nitrogen. Dried samples were redissolved in 100 μL of MeOH : H2O (1:1, v/v), filtered through a 0.1-μm membrane, and transferred to sample vials for LC-MS analysis. UPLC separation was performed using a BEH C18 column (2.1 mm × 100 mm, 1.7 μm, Waters Corporation, USA) at a flow rate of 0.3 mL min−1. The experiments were performed three times independently with biological replicates.

      Statistical analysis

    • All experiments were performed with at least three replicates. Statistical analysis of data were carried out by two-way analysis of variance (ANOVA) using SPSS version 17.0 (SPSS Inc., Chicago, Illinois, US) with storage time and coating as factors. Comparison of means was performed using Duncan's multiple range test. The value of P < 0.05 or P < 0.01 represented statistical significance.

      Acknowledgments

      • This work was supported by the National Natural Science Foundation of China (NSFC, 32002022) and Modern Agro-Industry Technology Research System (CARS-26).

      Conflict of interest

      • The authors declare that they have no conflict of interest.

      Supplementary information
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      • Copyright: © 2022 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (5)  Table (2) References (38)
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    Cite this article
    Wang X, Guo L, Zhou R, Liu Y, Hu H, et al. 2022. cDNA-AFLP analysis reveals altered gene expression profiles involved in juice sac granulation in pummelo (Citrus grandis). Fruit Research 2:16 doi: 10.48130/FruRes-2022-0016
    Wang X, Guo L, Zhou R, Liu Y, Hu H, et al. 2022. cDNA-AFLP analysis reveals altered gene expression profiles involved in juice sac granulation in pummelo (Citrus grandis). Fruit Research 2:16 doi: 10.48130/FruRes-2022-0016
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Catalog

  • Html

  • Introduction
  • Results

  • Granulation-associated genes revealed by cdna-aflp

  • Validation of expression patterns of differentially expressed tdfs using qrt-pcr

  • Concentrations of hormones in normal and granulated juice sacs

  • Discussion

  • Hormone and biological regulation

  • Carbohydrate and energy metabolism

  • Protein and nucleic acid metabolism

  • Stress responses

  • Cell metabolism

  • Conclusions

  • Materials and methods

  • Samples

  • Rna extraction and cdna synthesis

  • Cdna-aflp analysis

  • Quantitative real-time rt-pcr (qrt-pcr)

  • Ultra-performance liquid chromatography mass-spectrometry (uplc-ms) analysis

  • Statistical analysis

  • Acknowledgments
  • Conflict of interest
  • Supplementary information
  • Rights and permissions
  • About this article
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