Introduction
As an endemic species, Cupressus gigantea W. C. Cheng & L. K. Fu, commonly known as the ‘God tree’, is a rare tree species endemic to China (Liyuan et al., Reference Liyuan, Zengxian, Li, Zhen and Yujun2009). It has a narrow distribution because it is restricted to the dry valleys of Yarlung Tsangpo River and Nyang River (Fumei et al., Reference Fumei, Shiqiang and Ciren2017). It has high ecological and economic value because of its contribution to afforestation and timber production and also because it is the source of Tibetan incense (Yunxing and Xing, Reference Yunxing and Xing1999). C. gigantea has been listed as a threatened species in the International Union for Conservation of Nature's Red List. The lifespan of C. gigantea is approximately 1000 years. However, this species is currently on the verge of extinction due to extreme climatic conditions, its dispersed distribution and slow natural renewal (Guo et al., Reference Guo, Yang, Zhang, Zhang and Liu2020). Accordingly, the mechanisms involved in C. gigantea reproduction must be investigated in-depth to allow the development of efficient conservation strategies (Lei et al., Reference Lei, Liu, Li, Jin, Xu, Ji, Zhao, Tao and Meng2022). Previous studies on seed germination and seed viability in C. gigantea have shown that mature C. gigantea are poor reproducers (Wang et al., Reference Wang, Zheng and Pan2005), with only 20–30% of trees bearing fruit, and their seed germination and survival rates are low. Moreover, the seeds are severely affected by disease, birds and mice. To date, relatively few studies have reported on the viability of C. gigantea seeds, and further research on the characteristics of seed germination in C. gigantea is needed to better understand and conserve this endangered species.
Seed germination initiates with the absorption of water by dry seeds, followed by embryonic expansion and rupture of the covering layer and the emergence of part of the embryo, the protrusion of the radicle is typically regarded as the completion of the germination process (Wang et al., Reference Wang, Zheng and Pan2005; Smolikova et al., Reference Smolikova, Strygina, Krylova, Vikhorev, Bilova, Frolov, Khlestkina and Medvedev2022). Germination can be broadly divided into three phases, an initial period of rapid water uptake, a plateau period and a period of further increased water uptake (Bewley, Reference Bewley1997; Santo Pereira et al., Reference Santo Pereira, Oliveira, Fraceto and Santaella2021). In the early phase of seed germination, seed dormancy is broken by the activation of physiological processes, seed respiration and various metabolic pathways (Han and Yang, Reference Han and Yang2015). During the stabilization phase, seed metabolism gradually intensifies and the embryo begins to grow (Oracz and Stawska, Reference Oracz and Stawska2016). Gibberellic acid (GA), a key hormone in seed germination, is also synthesized and released during this phase, and promotes the decomposition of the endosperm (Ye-Hong and Hai-Ming, Reference Ye-Hong and Hai-Ming2009; Miura et al., Reference Miura, Furui, Yamamoto, Kanno, Honjo, Yamaguchi, Suetsugu, Yagame, Seo, Shigenobu, Yamato and Kaminaka2023). In the third stage, the seed coat ruptures and the radicle begins to elongate. At this stage, the seed rapidly absorbs water to meet the water requirements for germination and seedling growth (Srivastava et al., Reference Srivastava, Kumar and Suprasanna2021). Studies have shown that the different stages of seed germination are regulated by distinct sets of proteins (Zaynab et al., Reference Zaynab, Pan, Fatima, Noman, Chen and Chen2019). For instance, during seed germination, storage proteins are degraded and functional proteins are synthesized, and processes such as starch hydrolysis, sucrose transport and lipid metabolism are activated (Nonogaki et al., Reference Nonogaki, Bassel and Bewley2010). Accordingly, it is necessary to explore in-depth the expression patterns of proteins that affect seed germination through proteomics. In addition, the vitality of germinating seeds and germination conditions are critical parameters for the development of practical production ecology as well as for forestry applications, as they determine the seed germination rate and the survival rate of emerging trees under complex environmental conditions, respectively (Galland et al., Reference Galland, Huguet, Arc, Cue Ff, Job and Rajjou2014). A comparative analysis of the germination rate and germination potential of C. gigantea under different treatment conditions showed that, under optimal conditions, the germination rate of cypress seeds reached 44%, whereas, under non-optimized conditions, it was less than 30%. Therefore, understanding the seed germination characteristics of C. gigantea in Tibet can also contribute to solving the problems of seed germination in other forest trees.
The genetic and molecular mechanisms involved in seed germination have been extensively studied in a wide range of plants (Osama et al., Reference Osama, Kerr, Yousif, Phung, Kelly, Fox and Schulz2021); however, little is known about these mechanisms of in C. gigantea. Seed development from dormancy to germination results in complex physiological and biochemical changes, including the synthesis of reserve proteins and the production of antioxidant and other stress-related proteins (Sghaier-Hammami et al., Reference Sghaier-Hammami, Hammami, Baazaoui, Gómez-Díaz and Jorrin-Novo2020). Proteomics is an effective method for studying the mechanisms underlying seed germination, and many studies have employed this technique for large-scale protein expression analyses during this process (Li et al., Reference Li, Wang, Xiong, Wei, Zhou, Huang, Zhang, Fan and Liu2018), especially in model species such as Arabidopsis thaliana or important crops (Xu et al., Reference Xu, Liu, Song, Wang, Wang and Song2016; Sanit, Reference Sanit2021). Two -dimensional gel electrophoresis (2-DE) and gel-free liquid chromatography–tandem mass spectrometry (LC–MS/MS) are the most frequently used proteomics platforms in plant biological research. It has been reported that, although 2-DE and LC–MS/MS can identify similar numbers of proteins, experimental conditions (IPG strips, pH range and size and staining methods) can significantly influence outcomes; accordingly, 2-DE and LC–MS/MS have been proposed to be complementary methods for analysing samples with complex protein profiles (Sghaier-Hammami et al., Reference Sghaier-Hammami, Castillejo, Baazaoui, Jorrin-Novo and Escandón2021). 2-DE combines two different electrophoresis methods and separates molecules according to the isoelectric point and molecular mass (Meleady, Reference Meleady2018), achieving sensitive and accurate protein quantification. This technique has been used to characterize the proteins involved in metabolic, redox homeostasis and phytohormone regulation during seed germination (He et al., Reference He, Han, Yao, Shen and Yang2011; Ren et al., Reference Ren, Xue, Wang, Xue, Zhang, Jiang and Zhang2017). 2-DE and MS have been employed for protein identification in several plant species (Stergaard et al., Reference Stergaard, Finnie, Laugesen, Roepstorff and Svennson2004; Nakamoto et al., Reference Nakamoto, Sato, Hirosawa, Nakamoto, Enoki, Chida, Usui, Takeda, Nagai and Sasaki2014). Proteomics combined with 2-DE technology is more effective at directly targeting differentially expressed proteins (DEPs), which not only reduces costs but also improves protein detection accuracy.
Relevant transcriptomic and proteomic analyses in many species have previously provided an overview of mRNA and protein accumulation patterns during seed germination, such as Arabidopsis thaliana (Bai et al., Reference Bai, Peviani, van der Horst, Gamm, Snel, Bentsink and Hanson2017; Sajeev et al. Reference Sajeev, Baral, America, Willems, Merret and Bentsink2022), rice (He et al., Reference He, Han, Yao, Shen and Yang2011; Sano et al., Reference Sano, Lounifi, Cueff, Collet, Clément, Balzergue, Huguet, Valot, Galland and Rajjou2022), maize (Dinkova et al., Reference Dinkova, Márquez-Velázquez, Aguilar, Lázaro-Mixteco and de Jiménez2011), etc. Nevertheless, little is known about the mRNA and protein expression profiles in C. gigantea during this process. In this study, a 2-DE-based proteomic analysis was undertaken on the seeds of C. gigantea to identify DEPs during different stages of seed germination. Our findings provide relevant and reliable proteomic data on C. gigantea seed germination.
Materials and methods
Seed germination
C. gigantea seeds were collected from the coastal areas of the Brahmaputra River in Tibet, China in November 2018. After drying, the seeds were sealed and stored at 0–8°C for 1 year. In this study, 200 seeds of average fullness and size were selected as experimental materials. The seeds were placed on moistened gauze in Petri dishes (8 cm diameter), stratified at 4°C for 2 days and then placed in a lighting incubator and rinsed with water three times a day. During stratification, the seeds were treated with different concentrations of GA3 (0 [control], 1, 1.5, 2 and 2.5 mg/ml). Seeds were transferred to a lighting incubator with the light duration set to 0, 8 and 16 h and the incubation temperature set to 10, 15, 20, 25 and 30°C. Three biological replicates were set up and 100–150 seeds were cultured each time. Seeds were photographed at four different stages according to days after germination. The germination time was divided into four stages, namely, Stage A: day 1, the initiation stage of seed germination; Stage B: day 5, visible cracks in the seed coat; Stage C: day 9, completely broken seed coat; and Stage D: day 13, change in embryo colour.
Determination of seed length, protein content and fresh/dry weight
A Vernier calliper was used to determine seed length. Fresh and dry weights of the seeds were determined in 10 replicates. Fresh weight was measured immediately after harvest, and dry weight was measured after drying at 70°C for 24 h. Protein content was calculated using the Bradford method. Seeds were stored at −80°C for protein and RNA extraction.
Protein extraction
Two grams of seed were ground into a fine powder in liquid nitrogen and thoroughly mixed with TCA/acetone in 5 ml centrifuge tubes for 2 h. The homogenate was centrifuged at 13,500 rpm for 20 min at 4°C, and the precipitate was washed three times with 80% acetone. After discarding the supernatant, the precipitate was lyophilized dry, yielding crude protein. 0.1 g crude protein powder was extracted with 1 ml of water-saturated phenol containing 1 μl of 1 M DL-dithiothreitol (DTT) at room temperature for 1 h. After centrifugation at 13,500 rpm for 30 min at 4°C, the supernatant was transferred into a new tube. 4 ml of 1 M ammonium acetate in methanol containing 4 μl 1 M DTT were added to the supernatant overnight at −20°C. After centrifuging at 13,500 rpm for 5 min at 4°C, the precipitate was washed twice with 80 and 100% acetone, respectively, by centrifugation, and the sediment was dried to obtain the protein sample. The protein precipitate was dissolved in a buffer containing 0.1 M DTT, 10 mM EDTA and 1 M Tris-HCl (pH 7.5) for 1 h and centrifuged at 13,500 rpm for 30 min at 4°C. The resulting supernatant was the protein sample.
2-DE and image analysis
The total protein load from C. gigantea was 1.5 mg. First-dimension isoelectric focusing (IEF) separation was carried out on an IPGphor apparatus under the following conditions: 30 V for 13 h, 100 V for 1 h, 500 V for 1 h, 1,000 V for 1 h, 3,100 V for 1 h, 8,000 V for 1 h and finally, 8,000 V for 6 h. Subsequently, the IPG strips were equilibrated in 10 ml Buffer I, containing 0.1 g of DTT and 10 ml Buffer II, containing 0.15 g of iodoacetamide, respectively, for 15 min. Then, second-dimension separation of proteins was performed using 12.5% SDS–PAGE. After electrophoresis, the gels were stained with Coomassie brilliant blue (CBB). The samples were visualized using a GE Image Scanner III and analysed by Melanie 7.0 2-D gel analysis software. Protein spots showing 1.5-fold changes (P < 0.05) between samples were selected for further MS/MS analysis.
MALDI-TOF/TOF-MS and protein identification
The selected protein spots were excised and destained in 100 mM NH4HCO3 and acetonitrile, sequentially. The proteins were equilibrated in 10 ml buffer containing 25 mM NH4HCO3 at 37°C overnight. The next day, protein digestion was performed by adding 40 μl of trypsin solution (4 μg of trypsin in 40 μl of buffer) to the solution, the solution was shaken at 600 rpm for 1 min and then allowed to stand at 37°C for 16–18 h. The solution was transferred to a new collection tube and centrifuged at 14,000 × g for 15 min. Then, 40 μl of 10-fold diluted dissolution buffer was added, followed by centrifugation at 14,000 × g for 15 min, the addition of 40 μl of 10-fold diluted dissolution uffer and centrifugation at 14,000 × g for 15 min. Finally, the peptides were desalted using C18 ZipTips (Millipore, USA), lyophilized, redissolved in 40 μl of dissolution buffer and quantified (OD280). All samples were analysed in positive ion reflection mode on a 5800 MALDI-TOF/TOF mass spectrometer. The acquired mass spectra (m/z range: 700–4,000; resolution: 15,000–20,000) were processed using Flex Analysis v.2.4 software. To identify proteins, the mass signals were searched against the Swiss-Prot, NCBI and MSDB databases using the MASCOT search engine. The MS/MS fragment tolerance was set to ±0.5 Da. Cysteine aminomethylation was set as a fixed modification and methionine oxidation was set as a variable modification. Trypsin cleavage and K/R-P cleavage had a misidentification tolerance of 3. Confidence in matched peptide mass fingerprints (P < 0.05) was based on the MOWSE score. Sequences with more than two overlapping peptide fragments for a given feature were identified in the MOWSE score, which is considered homogeneous. The intensity values for the identified proteins were log10-transformed and compared based on the mean values of the groups. Hierarchical clustering of samples and proteins was performed using MeV 4.8 (http://www.tm4.org/mev.html). Proteins were functionally annotated and classified using the TargetP prediction tool.
Quantitative real-time polymerase chain reaction (qRT-PCR)
Seed samples were ground to powder in liquid nitrogen and total RNA was isolated using the Omega Plant RNA Kit (Omega Genetics, Beijing, China) following the manufacturer's instructions. cDNA was prepared with the PrimeScript Reverse Transcriptase Kit (Takara, Japan). qPCR was performed in a LightCycler 480 System (Roche, USA) with LightCycler 480 SYBR Green I Master Mix and specific primers (Supplementary Table S1). The reactions were carried out in a 20 μl volume containing 2 μl of cDNA (50 ng/μl), 1 μl of primers (10 pmol), 10 μl of SYBR Green I Master Mix, and 6 μl of ddH2O. Three biological replicates were used for each sample. The 18S rRNA gene was used as a control. Relative gene expression levels were calculated using the ΔΔCt method.
Data submission
MS data (identified spots) were translated to PRIDE XML using the PRIDE Submission Tool Version-2.7.3. A total of 34 PRIDE XML files were submitted to the ProteomeXchange repository following the ProteomeXchange submission guidelines (Simova-Stoilova et al. Reference Simova-Stoilova, Romero-Rodríguez, Sánchez-Lucas, Navarro-Cerrillo, Medina-Aunon and Jorrín-Novo2015). The data were deposited under the identifier PXD047123.
Statistical analysis
All data were analysed using SPSS 25 software. One-way analyses of variance (ANOVAs) with Duncan's multiple range tests (P < 0.05) and Tukey–Kramer Test were conducted in at least three independent experiments. Graphs were generated using GraphPad Prism 8.4 software.
Results
Optimization of seed germination conditions for C. gigantea
We first tested the effect of different incubation temperatures (10, 15, 20, 25 and 30°C) on seed germination under a uniform 16-h light/8-h dark photoperiod. Incubation at 20 and 25°C significantly accelerated the seed germination rate at early germination time compared to 10°C incubation, resulting in the seed germination rate reaching 93.51, 96.44 and 84.14% at 20, 25 and 10°C respectively at day 8 (Fig. 1A). Additionally, the germination speed and final germination rate were significantly inhibited in the 30°C incubation, suggesting that the optimum germination temperature for C. gigantea seeds is approximately 20°C. Next, the effects of incubation under different lighting conditions (0, 8 and 16 h light) on seed germination were tested when the temperature was kept constant at 20°C. The results indicated that the seed germination rate was most significantly enhanced under the 16-h/8-h light/dark photoperiod (Fig. 1B). During stratification at 4°C, seeds were treated with various concentrations of exogenous GA3 (0, 1, 1.5, 2 and 2.5 mg/ml) followed by 16 h light/8 h dark incubation at 30°C to determine the optimal GA3 concentration to break the germination inhibition caused by high temperature at 30°C. The seed treatment with 1.5 mg/mL GA3 began to exert an inhibitory effect on seed germination after 14 days of incubation, with a germination rate of only 15.29% compared with 20.38% for non-treated control seeds. In contrast, seeds treated with 1 mg/ml GA3 displayed the highest germination rate, reaching 38.69% at 14 days of incubation (Fig. 1C). In conclusion, in addition to altering the photoperiod to 16 h of light and 8 h of darkness, as well as maintaining a temperature of 20°C, the application of exogenous GA3 (1 mg/ml, about 2.9 mM) was found to enhance the germination of C. gigantea seeds.
Figure 1. Effects of seed culture temperature, light duration and exogenous GA3 application on seed germination rate of C. gigantea. (A) Germination rate of C. gigantea seeds at different temperatures (10, 15, 20, 25 and 30°C) for different incubation times (2, 4, 6, 8, 10, 12 and 14 days). (B) Effect of light duration on seed germination of C. gigantea. (C) Impact of exogenous application of different concentrations of GA3 on germination rate of C. gigantea seeds. Data represent the mean ± SD of three independent biological replicates. Different letters indicate significant differences (P < 0.05, Tukey–Kramer tests).
Morphological changes and biomass accumulation during seed germination
The morphological characteristics of seeds at the four stages of germination (Stage A–D) are shown in Fig. 2. In the early period (Stage A, swelling absorption, day 1) (Fig. 2A), seeds were transitioning from a dry to a swelling state due to rapid water uptake, indicating that they would soon sprout. In Stage B (seed coat dehiscence, day 5), cracks were visible on the seed coat surface, but the shape of the embryo and endosperm did not differ from that at Stage A (Fig. 2B). In Stage C (radicle emergence, day 9), seeds showed significant changes in morphology, with radicles breaking through the endosperm and cracking the seed coat (Fig. 2C). Elongated radicles showed red and embryonic axis showed green from bottom to top in Stage D (beginning of radicle elongation, day 13) (Fig. 2D). Radicle elongation indicated the completion of seed germination. The protein content decreased during germination, while seeds absorbed water and swelled, increasing in both volume and length (Figs. 3A, B). The fresh weight of the seeds increased whereas the dry weight of the seeds showed little change (Figs. 3C, D).
Figure 2. Morphological characteristic of C. gigantea seeds during the four germination stages. (A) Seeds absorb water for 1 d (Stage A) (B) Seeds absorb water for 5 days (Stage B); (C) Seeds absorb water for 9 days (Stage C); (D) Seeds absorb water for 13 days (Stage D). Bar, 1 mm.
Figure 3. The changes of protein content (A), seed length (B), dry weight (C) and fresh weight (D) of seeds during seeds germination. The error bars represent ± SD of three biological replicates. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.
Identification of DEPs during seed germination
Sample collection is a critical step in the proteomic analysis of C. gigantea seeds. Because protein expression is time and space-dependent, collected tissue samples must be stored in a fresh, undamaged state to ensure the validity of the subsequent experimental data (Jolli and Ekbote, Reference Jolli and Ekbote2010). We compared two methods of protein precipitation (Supplementary Fig. S1). Phenol precipitation resulted in a marked loss in molecular mass, especially among the alkaline fragments, along with the presence of strong low-molecular-mass bands and poor separation of some protein spots (Supplementary Fig. S1A). The optimized TCA/acetone precipitation method was more effective in suppressing protease activity and diminishing sugar and salt interference (Supplementary Fig. S1B). Compared with phenol precipitation, TCA/acetone precipitation resulted in a significant increase in the number of protein spots on the protein map and more precise separation between protein spots, thereby providing images that were more suitable for the subsequent comparative analysis. This was consistent with the approaches used for Cucumis sativus L (He et al., Reference He, Lu, Tian, Yang, Li, Li and Guo2012), Elaeis guineensis (Wang et al., Reference Wang, Li, Wu, Zhang and Lei2014) and Alexandrium (Wang et al., Reference Wang, Lin, Chan and Hong2009).
The results of 2-DE showed that the sample had a clear background and precise contours, and the protein spots were generally circular or elliptical, indicating that the 2-DE conditions were suitable for the separation of C. gigantea proteins (Fig. 4). The 2-DE images of all the protein spots were then compared, and spots with at least a 1.5-fold (P < 0.05) abundance difference were selected for analysis. The details of all the DEPs are shown in Supplementary Table S2. The molecular mass (Mr) of protein spots from seeds at the four germination stages ranged from 25 to 116 kDa and most had an isoelectric point at pH 4–7. Images of the distribution of all the protein spots are shown in Fig. 4. A total of 34 DEP spots were identified by 2-DE and were analysed by MALDI-TOF/TOF-MS. Among them, compared to Stage A, 31 DEPs were present at all four germination periods and three DEPs were only specific during germination, Of the 34 DEP spots, 21 were upregulated and 11 were downregulated.
Figure 4. Proteome maps of C. gigantea seeds during four seeds germination periods by 2-DE. Protein 2-DE gel showing the accumulation of differential proteins in four periods of seed swelling (1 days) (A), germination (5 days) (B), emergence (9 days) (C) and radicle elongation (13 days) (D), respectively. All red markings are differential proteins by period, and the size of the circle markers is positively correlated with protein accumulation.
Cluster analysis and functional distribution of the DEPs
Stage A as the starting expression level, the DEPs were found to group into three main expression stages (Stage B–D) as shown in Fig. 5A. Stage B contained 11 protein spots, all of which showed a trend towards upregulation of expression during the seed coat dehiscence stage. Stage C consisted of 13 protein spots that were downregulated during the radicle emergence stage. In Stage D (10 protein spots), proteins showed a trend toward s upregulation of expression during the radicle elongation stage.
Figure 5. Classification of C. gigantea seed proteins. Hierarchical clustering analysis of the expression patterns of DEP spots (A) and functional classifications of DEPs identified (B) in C. gigantea during seed germination. Clustering was based on the protein expression levels during seed germination. Stage A was used as a control, and Stage B (seed coat dehiscence), Stage C (radicle emergence) and Stage D (radicle elongation) were included. Red colour indicates a positive abundance in protein spots and blue indicates a negative abundance in protein spots.
Based on the analysis of the MS data using the NCBI database and the results of MS identification, we classified the 34 DEP spots into 8 functional categories, including the cytoskeleton (10, 29.41%), energy metabolism (5, 14.71%), transport (5, 14.71%), stress response (5, 14.71%), molecular chaperones (3, 8.82%), amino acid metabolism (3, 8.82%), antioxidative enzymes (2, 5.88%) and ABA signalling pathway (1, 2.94%) (Fig. 5B).
Transcription patterns of nine key proteins at the seed germination stages
The transcriptional levels of nine DEPs during seed germination are shown in Fig. 6 and Supplementary Fig. S2. These nine key proteins were ATP synthase subunit beta (Spot 15), RuBisCO large subunit-binding protein subunit beta (Spot 17), enolase1 (Spot 18), heat shock protein 70 kDa family (Spot 22), heat shock protein 70 kDa family (Spot 33), RuBisCO large subunit-binding protein subunit alpha (Spot 32), thioredoxin, nucleoredoxin2 (Spot 36), 20 kDa chaperone protein, chloroplastic-like (Spot 58) and 11S-globulin (Spot 65). Two of them (Spots 17 and 38) showed transcription patterns corresponding to their protein expression trends (Fig. 6).
Figure 6. The relative gene expression changes of 9 DEPs during seed germination revealed by quantitative real-time PCR in C. gigantea. Expression of nine major differential protein sites at the bud stage (5 days), germination stage (9 days) and radicle elongation (13 days) of seeds, respectively. Spot 15 (ATP synthase subunit beta), Spot 18 (Enolase1), Spot 33 (Heat shock protein 70 family), Spot 22 (Heat shock protein 70 family), Spot 36 (Thioredoxin, nucleoredoxin2), Spot 32 (ruBisCO large subunit-binding protein subunit alpha), Spot 17 (ruBisCO large subunit-binding protein subunit beta), Spot 27 (11S-globulin) and Spot 58 (20 kDa chaperonin, chloroplastic-like). Data represent the mean ± SD of three independent biological replicates. Asterisks indicate significant differences (*P ≤ 0.05, **P ≤ 0.01, Tukey–Kramer tests).
Discussion
Seed germination necessitates coordination among multiple signal transduction pathways and physiological and biochemical processes, including responses to growth factors and activation of seed vigour-related properties. These events ultimately lead to seed growth, beginning with water uptake and ending with radicle elongation (Ma et al., Reference Ma, Wang, Hu, Dai, Liang, Zou, Pan, Lubberstedt and Shen2022). GAs are positive regulators of seed germination (Moraes et al., Reference Moraes, Andrade, Gomes and Santos2021). We found that three factors were important for improving and accelerating the germination of C. gigantea seeds, namely, the photoperiod (hours of light), incubation temperature, and exogenous application of GA3. The application of GA3 (1 mg/ml, about 2.9 mM) during stratification effectively accelerated the seed germination rate. The concentration of exogenous GA3 used varied among different plants, which may be influenced by the thickness of the seed coat. For A. communis par., the optimal concentration to promote seed germination was found to be 1 mg/l (Hou et al., Reference Hou, Karim and Gao2005). In the case of populus seeds, a concentration of 10 mg/l GA3 significantly increased the germination rate (Ji et al., Reference Ji, Huang, Men and Wang2003). Furthermore, the concentration of GA3 used also depended on the duration of seed soaking in the experiment. For Santalum album seeds, the optimal concentration was determined to be 0.8 mg/ml (2.3 mM), with a soaking time of 6–24 h (Liu et al. Reference Liu, Xu, Zhang, Xie and Chen2010). On the other hand, the highest germination rate for F. chinensis seeds was achieved by soaking them in 0.2 mg/ml of GA3 for 60 h (Li et al., Reference Li, Mao and Jiang2012). In this study, seeds of C. gigantea were soaked for 48 h. Additionally, a constant incubation temperature of 20°C and a photoperiod of 16 h of light and 8 h of darkness were found to be optimal conditions for the promotion of seed germination under our experimental setup (Fig. 1).
The expression patterns of the identified DEPs were also analysed at the transcriptional level, and Spots 17 and 38 showed the same expression pattern at both the protein and mRNA levels, indicating that the regulation of these proteins begins at the transcriptional stage. Most other proteins, such as Spot 22, Spot 18, had different mRNA and protein expression patterns, possibly because they are regulated post-transcriptionally or post-translationally (Kuhlemeier, Reference Kuhlemeier1992) (Fig. 6). Differences between transcript levels and protein abundance can also be due to the presence of several proteins under a single spot, which can happen when spots are particularly large.
Many of the DEPs detected in this study are involved in amino acid metabolism (Supplementary Fig. S2). Two proteins ferredoxin-dependent glutamate synthase (Spot 41) and glutamine synthetase cytosolic isoenzyme-like (Spot 47) have been implicated in glutamate metabolism. Enolase (Spots 18, 30 and 68) is known to play an important role in the glycolytic metabolic pathway, while thioredoxin (Spot 0 and Spot 36) is involved in the activation of enzymes in the pentose phosphate pathway. Furthermore, many of the identified DEPs act in the endoplasmic reticulum and are involved in transport, processing and splicing processes (Spots 1, 24 and 53) (Fig. S3). Luminal-binding protein (Spot 13) recognises mismatched RNA, which is then degraded by the degrading enzyme complex. The components of the degrading enzyme complex are related to stress response proteins (Spots 9, 26, 22, 33 and 37). DTM1 (Spot 60) is a signal peptidase complex-like protein located within the membrane of the endoplasmic reticulum (Supplementary Fig. S3).
In higher plants, the cytoskeleton plays fundamental roles in cell division, cell growth, cellular organization, intracellular transport and cell shape dynamics (Hasezawa and Kumagai, Reference Hasezawa and Kumagai2002). In our study, the expression of cytoskeletal proteins first decreased, and then increased during the process of seed germination (Supplementary Table S3). This suggested that the cytoskeleton is involved both at the early and late stages of seed germination in C. gigantea seeds. It has been reported that the cytoskeleton regulates cellular responses to biotic or abiotic stresses during germination under a variety of unfavourable external environments (Yemets et al., Reference Yemets, Krasylenko, Lytvyn, Sheremet and Blume2011). The functions of cytoskeletal proteins in higher plants under stress conditions have been comprehensively investigated (Rongqiu et al., Reference Rongqiu, Yingjun, Min, Gaoneng and Weili2011). For example, Protein blotting and immunocytochemical analyses revealed an increasing accumulation of microtubule proteins and microtubule cytoskeleton in Jatropha curcas seeds soaked in water for more than 48 h (de Brito et al., Reference de Brito, Loureiro, Santos Teles, Schuck, Fernandez and de Castro2015). Additionally, under drought stress, a subset of genes associated with cytoskeleton organization was found to be dysregulated in developing wheat seeds, coincident with reduced seed size and delayed endosperm development (Begcy and Walia, Reference Begcy and Walia2015; Sanit, Reference Sanit2021).
Energy consumption is high throughout the seed germination process (Miladinov et al., Reference Miladinov, Radic, Miklic, Crnobarac and Mrdja2014; Koo et al., Reference Koo, Park, Kim, Mi, Mi, Lee, Xia and Hon2015). In this work, two proteins involved in energy metabolism (ATP synthase subunit beta [Spots 14 and 15]) were identified among the DEPs. These two proteins, which were upregulated, are subunits of an enzyme that provides energy for C. gigantea seeds during germination (Supplementary Table S3). ATP synthase is required for energy production in the tricarboxylic acid (TCA) cycle (Chen et al., Reference Chen, Alonso, Allen, Reed and Shachar-Hill2011). However, at the seed coat dehiscence stage, we found that the protein level of ATP synthase subunit beta was significantly decreased compared to Stage A. This result suggested that energy supply occurred late in seed germination. Notably, the glycolysis pathway generates most of the energy required for seed germination (Abokassem, Reference Abokassem2005; Kadri et al., Reference Kadri, Ayed, Kadri, Limam and Mokni2021). During germination, some proteins related to glycolysis (ferredoxin-dependent glutamate synthase [Spot 41] and glutamine synthetase cytosolic isozyme-like [Spot 47], which are involved in glutamate metabolism, and enolase [Spots 18, 30 and 68]) were the most prominently expressed. Taken together, these findings indicate that the TCA cycle and glycolysis are the primary energy sources for C. gigantea seed germination.
Most proteins involved in seed germination are membrane transport proteins. When seeds begin to germinate, they require the transportation of large amounts of compounds, such as water and nutrients, which are needed for the synthesis of numerous components. Transporters allow higher plants to uptake an abundance of compounds necessary for cellular component synthesis across specific cell membranes during germination (Routray et al., Reference Routray, Masalkar, Roberts and de Bruijn2015). ABC transporters, for example, are critical for plant development, as they are involved in seed development, seed germination and secondary growth (Bruhn et al., Reference Bruhn, Lindsay, Wiebel, Kaehler, Nagel, Böhm, Röder and Cascorbi2020; Cai et al., Reference Cai, Wang, Kim, Li, Zhou and Wang2021). In this study, several DEPs were associated with transport (Spots 13, 24, 42 and 53) and Spot 62 was an ABC transporter ATP-binding protein (Supplementary Table S2). Luminal-binding protein (Spot 13) participates in seed development, germination and early seedling growth (Forward, Reference Forward2001). In our study, this protein was upregulated at radicle emergence and radicle elongation stages compared to Stage A (Table S3).
Conclusion
Preliminary studies can contribute to the understanding of the expression patterns of proteins essential for seed germination in higher plants, including C. gigantea. In this study, in addition to altering the photoperiod to 16 h of light and 8 h of darkness, as well as maintaining a temperature of 20°C, the application of exogenous GA3 (1 mg/ml, about 2.9 mM) was found to enhance the germination of C. gigantea seeds. Then, using a combination of 2-DE-based protein identification and proteomics, we identified 34 proteins that were differentially expressed, 13 at the radicle pre-emergence stage, and 17 at the radicle elongation stage. Many of the identified DEP spots are closely related to amino acid metabolism. Additionally, the DEPs were found to be primarily involved in endoplasmic reticulum function. The TCA cycle and glycolysis were the primary energy sources for C. gigantea seed germination. Our study demonstrated that proteomics can provide reference information relating to multiple processes of seed germination and lays the foundation for understanding the characteristics of DEPs during C. gigantea seed germination.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0960258524000126.
Author contributions
All authors have read and agreed to the published version of the manuscript.
Funding statement
This work was funded by the Fundamental Research Funds for the Central Universities (2572018CG05); the National Natural Science Foundation of China (No.31760548); Guangxi Natural Science Foundation under Grant No. 2022JIA130042: Molecular regulation of flower development and nervonic acid synthesis in Malania oleifera; Science and Technology Development Funds (BS2022002): Identification and Conservation of endangered medicinal plant resources. The Fundamental Research Funds for the Central Universities (No. 2572022DS13).
Data availability statement
All data supporting the findings of this study are available within the paper and within its supplementary materials published online.
Competing interest
The authors declare that they have no conflict of interest. The present research did not involve human participants and/or animals. Informed consent was obtained from all individual participants included in the study.
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