Integrated metabolomics and transcriptomics reveal the role of calcium sugar alcohol in the regulation of phenolic acid biosynthesis in Torreya grandis nuts

Integrated metabolomics and transcriptomics reveal the role of calcium sugar alcohol in the regulation of phenolic acid biosynthesis in Torreya grandis nuts | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integrated metabolomics and transcriptomics reveal the role of calcium sugar alcohol in the regulation of phenolic acid biosynthesis in Torreya grandis nuts Qiandan Xie, Zhengchu Jiang, Chenliang Yu, Qi Wang, Wensheng Dai, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4608684/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Jan, 2025 Read the published version in BMC Plant Biology → Version 1 posted 11 You are reading this latest preprint version Abstract Background： Torreya grandis , a prominent tree species of the autochthonous subtropical region of China, possesses a drupe-like fruit containing a nut that is rich in nutrients and bioactive compounds. However, the effect of calcium (Ca 2+ ) sugar alcohol (CSA), a newly developed chelated Ca 2+ -fertilizer, on the secondary metabolism of phenolics in T. grandis nuts is largely unknown, for which transcriptomic and metabolomic analysis was carried out. Results: Transcriptome sequencing detected 47,064 transcripts, and several phenolic acid biosynthesis pathway-related genes were identified. Correlation analysis showed that the four transcription factors, WRKY12, AP2-1, AP2-3, and AP2-4, were positively associated with the accumulation of phenolic acids. Furthermore, the binding of AP2-1 to the HCT promoter was confirmed using yeast one hybrid and dual-luciferase assays. Furthermore, the expression of HCT in Nicotiana enhanced the total flavonoid content. Conclusions: Our results indicated that a new regulatory module, Ca 2+ –AP2–HCT, involved in the regulation of phenolic acid biosynthesis was revealed, expanding the understanding of the role of Ca 2+ fertilizers in plant secondary metabolism. Phenolic acids calcium sugar alcohol transcriptome sequencing untargeted metabolome transcription regulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Plant growth and development are influenced by various genetic and environmental factors, including transcription factors and nutrients [ 1 ]. Although the extensive application of chemical fertilizers can increase crop yield, it poses a considerable threat to the environment [ 2 ]. Biofortification is a process of adding essential nutrients and growth-promoting chemicals to improve the nutritional value of plants [ 3 ]. With an improvement in the living standards of people, organic agriculture has recieved more attention recently. Foliar fertilizers sprayed on the leaves of plants can provide essential nutrients and mitigate the accumulation of heavy metals in the aboveground parts [ 4 ]. As an environmentally friendly fertilizer, foliar fertilizer mainly consists of growth regulators, organic acids, and various mineral elements [ 5 ]. For example, the foliar application of Zn 2+ increased the production and quality of fruit crops [ 6 ]. The foliar application of silicon enhanced the growth of crops and improved the efficiency of carbon and phosphorus (P) utilization [ 7 ]. Foliar-applied iron oxide nanoparticles increased the plant biomass, chlorophyll contents, and other growth parameters of maize seedlings [ 8 ]. More experiments confirmed that the contents of nitrogen, P, and magnesium can be increased by applying corresponding foliar fertilizers [ 9 ]. Calcium (Ca 2+ ) is an essential component of the cell structure and also serves as a crucial secondary messenger in various signal transduction pathways [ 10 ]. The application of Ca 2+ improved the tolerance of plants to stresses by activating the antioxidant system [ 11 ]. CaCl 2 can alleviate the negative effects of drought-triggered and-related stresses [ 11 – 13 ]. Considering the impeded translocation of Ca 2+ fertilizers from the underground parts to leaves, the spraying of Ca 2+ on developing leaves is reported [ 14 ]. The primary Ca 2+ -based fertilizers, including calcium chloride, calcium acetate, and calcium nitrate, are limited by their solubility and relatively low utilization rates [ 15 ]. Recently, calcium sugar alcohol (CSA), a newly developed chelated Ca 2+ fertilizer with good water solubility, has been widely applied in agriculture [ 16 ]. Torreya grandis is a notable tree species indigenous to the subtropical region of China [ 17 ]. An evergreen coniferous tree, T. grandis possesses a drupe-like fruit containing a nut that is a rich source of nutrients and bioactive ingredients, such as alkaloids, flavonoids, and tannins [ 18 ]. T. grandis nuts are often used as food supplements to promote cardiovascular health. Due to increasing demand, the production of nuts has expanded significantly [ 19 ]. Since T. grandis trees mainly grow in subtropical mountainous regions, they face severe nutrient deficiencies [ 20 ]. Chemical fertilizers at high doses have severe adverse impacts, such as water pollution and soil acidification [ 21 ]. Although foliar fertilizers have been widely applied, their roles in the secondary metabolism of T. grandis are mainly unknown. Utilizing large-scale identification technology has enabled investigations of the metabolic pathways responsive to foliar fertilizers [ 22 , 23 ]. In this study, nuts from the control and CSA-treated T. grandis trees were harvested for an integrated metabolomic and transcriptomic analysis. The results can provide a scientific basis for cultivating and managing T. grandis nuts by investigating the effects of CSA on the metabolism of phenolics in them. Materials and methods Plant material and growth conditions Thirty 15-year old Torreya grandis 'Merrilli' trees with the same site condition, growth and fruit quantity were selected as the research objects in Panmugang Chinese Torreya base(119°57′ E,30°30′ N), and their plant height and fruit quantity were recorded. The voucher specimens were identified by Prof. Wensheng Dai and deposited in the Zhejiang A&F University Intelligent Experimental Building Plant Specimen Room N205.Foliar fertilizer was applied from March to April 2022. The different leaf surface fertilizer treatments were CK (control group; pure water) and CSA (calcium sugar alcohol; high strength, water-soluble calcium fertilizer). Leaf fertilizer was purchased from Shenzhen Dugao Biological New Technology Co., Ltd. The fertilizer was diluted 1000-fold, once every 20 days, a total of three times. The CK and CSA treatment groups included five trees each. A 10 L electric spray bottle was employed to spray 1 L of fertilizer per tree at a time. The samples were taken once during May, June, July, August, and September 2022. They were named 5M, 6M, 7M, 8M, and 9M, respectively.All materials were stored in the refrigerator of -80 ℃ in the State Key Laboratory of Subtropical Forest Cultivation of Zhejiang Agriculture and Forestry University. Determination of the physiological and nutritional parameters Mature fresh T. grandis nuts were randomly collected from independent trees with different treatments. Then, the seed traits were determined based on our previous work. The longitudinal and transverse diameters of the seed nucleus and kernel were measured using Vernier calipers with an accuracy of 0.01 cm. The single nucleus and kernel masses were calculated by employing a 1000th-range electronic balance. Soluble sugar and starch contents in seeds were determined using commercial kits from Solarbio Life Science Co, Ltd (codes: BC0030 and BC0700). The kernel oil content was ascertained by the national standard GB/T 14772 − 2008 Soxhlet extraction method. The extracted oil was methylated, and the fatty acid components were estimated by the peak area normalization method. Metabolite extraction The seed kernel samples (80 mg each) were flash-frozen in liquid N 2 and powdered. For metabolite extraction, 1000 µL of methanol–acetonitrile–H 2 O solution (2:2:1, v/v/v) was added to the sample. The extract was centrifuged at 12,000 g for 20 min at 4°C. The supernatant was vacuum-dried and redissolved in 100 µL of acetonitrile–H 2 O (1:1, v/v) solution. The resulting solution was used for LC-MS/MS analysis. For each time point and each treatment, three biological replicates were collected. LC-MS/MS analysis An LC-MS/MS analysis was carried out using a TripleTOF 6600 quadrupole time-of-flight (AB Sciex) coupled to a 290 Infinity LC ultrahigh performance liquid chromatography (Agilent Technologies). The column temperature was 40°C, the flow rate was 0.4 mL/min, and the injection volume was 2 µL. Following were the ESI source conditions: the ion source gas1 (Gas1) was set to 60, the ion source gas2 (Gas2) to 60, and the curtain gas (CUR) to 30. The source temperature was 600°C, and IonSpray Voltage Floating (ISVF) was 5500 V. During auto MS/MS acquisition, the instrument was set to collect within the m/z range of 25–1000 Da, and the accumulation time for product ion scan was set at 0.05 s/spectra. Metabolite ion scanning was performed in an Information Based Acquisition (IDA) mode with high sensitivity. The parameters settings were: the collision energy (CE) at 35 V ± 15 eV; declustering potential (DP) at ± 60 V; excluded isotopes were < 4 Da; and candidate ions to be monitored per cycle were set at 10. Untargeted metabolomics The original MS scanning data was converted into MzXML files by employing the ProteoWizard MSConvert software. The following parameters were used when selecting peaks: center wave m/z set to 10 ppm, peak width to c (10, 60), and prefilter to c (10, 100). When grouping peaks, bw was set to 5, mz wid to 0.025, and min frac to 0.5. Isotopes and adducts were annotated utilizing the Metabolite pProfile Annotation software algorithm. Metabolites were identified by comparing the accurate m/z values (< 10 ppm) with the MS/MS spectra established from an internal database of available standards. Metabolites were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database by matching the precise molecular weight data (m/z). An internal metabolite fragment spectral library was applied to validate metabolite identification. The Wilcoxon test was employed to detect the variations in metabolite concentrations between two groups of samples. The P-values of multiple tests were adjusted using the FDR (Benjamin Hochberg) method. RNA isolation and sequencing RNA was isolated from the T. grandis nuts using TRIzol reagent (Invitrogen, Shanghai, China) by following the instructions. The high-quality RNAs (integrity number > 7.0) were selected to construct the cDNA library. They were fragmented and reverse-transcribed to cDNA. RNA was sequenced on an Illumina HiSeq™ 6000 platform at LC-Bio, Hangzhou, China, to produce 50- or 100-bp single- or paired-end small reads. Transcriptomics Reads containing unknown nucleotides (N < 5%) and low-quality bases (Q value < 19) were removed. The HISAT2 (ver.2.0.5) program with default parameters aligned all clean reads to the T. grandis genome [ 24 ]. By calculating FPKM (Fragments Per Kilobase of transcript Per Million mapped reads), the FeatureCounts (ver.1.5.0) software tallied the location reads of each gene. The DESeq R (ver.4.0.4) software distinguished the differentially expressed genes (DEGs) in each compared group with a P value < 0.05 and a multiple change ≥ 2-fold. Gene cloning and promoter analysis The complete coding sequences (CDSs) of WRKY2, AP2-1, AP2-3, and AP2-4 were isolated from the T. grandis genome and PCR-amplified. The sequences of the primers used are presented in Table S2. The genomic DNAs from the T. grandis tissues were isolated using a kit. The 2000-bp sequence of the HCT promoter was extracted from the T. grandis genome. Subcellular localization The CDS was cloned into the pCAMBIA1300-GFP vector and fused with the c-terminus of the artificial green fluorescent protein (GFP). All gene sequences obtained in this study are listed in (Table S3). The empty GFP vector was used as a control. All vectors were transiently expressed in tobacco epidermal cells through Agrobacterium tumefaciens (GV3101)-mediated transformation. The fluorescence of the GFP fusion protein was detected employing an LSM710 confocal microscope (Carl Zeiss AG, Oberkochen, Germany). Dual-luciferase assay The WRKY2, AP2-1, AP2-3, and AP2-4 cDNAs were inserted into pGreenII62-SK vectors as the effectors, and the HCT promoter was inserted into the pGreenII0800-LUC vector as the reporter. The constructed vectors were co-expressed in tobacco leaves by utilizing a transient transformation system mediated by Mycobacterium-induced root cancer (GV3101). The binding activities of the TFs with their specific promoters were calculated based on the LUC–REN ratio using a dual-LUC assay kit (Promega, Beijing, China). Yeast one-hybrid (Y1-H) assay In this study, Y1-H was conducted per the Yeast Protocols Handbook (Clontech) [ 25 ]. The promoters were amplified, and the cis-acting element was truncated using the website- http://bioinformatics.psb.ugent.be/webtools/plantcare/html/ and then cloned into the pLacZi vector. The pLacZi + HCT was constructed by PCR-based insertion of the TF sequences into PB42AD. Yeast cells were then co-transformed using pLacZi + HCT with pB42AD + AP2-1 or pB42AD + AP2-3 vectors. Next, six yeast cells were randomly selected for the detection of positive clones after coating the transformation products with SD/-Trp-Ura medium at 30°C for three days. For observing the color reaction, the PCR-confirmed bacteria were identified by detecting the appropriate yeast cells by spreading them on SD/-Trp-Ura/Gal/Raf/X-Gal agar color plates. Results Effect of CSA treatment on the quality parameters of T. grandis nuts To analyze the effects of CSA treatment on the quality of T. grandis nuts, a series of quality parameters, including protein, starch, soluble sugar, and oil contents, were determined. These contents were significantly increased by CSA (Fig. 1 a-d). Considering the complexity of oil composition, the levels of ten individual oil components were determined. CSA slightly down-regulated the levels of linoleic acid and unsaturated fatty acids (Figure.1e). These results indicated a marked impact of CSA treatment on the contents of total protein, starch, and soluble sugars in T. grandis nuts. Overview of the untargeted metabolomes Nuts harvested at different time points were subjected to LC-MS/MS analysis to reveal the differences in metabolites between the control and CSA-treated groups. A total of 20,006 ion features were identified, which were grouped into 1394 annotated metabolites (Table S1 ). All these metabolites were categorized into 326 lipids, 272 phenylpropanoids and polyketides, 153 benzenoids, 131 organoheterocyclic compounds, and 122 organic oxygen compounds (Fig. 2 a). Clustering of metabolites under CSA treatment at different time points The metabolomic profiling revealed remarkable variations in the metabolomes of the CK and CSA treatment groups (Fig. 2 b). All metabolites were grouped into eight different clusters to identify the accumulation of metabolites in a time-dependent manner. In detail, Cluster I contained 2,915 5M-, Cluster II contained 2,569 8M-, and Cluster III contained 4,480 9M-specifically accumulated metabolites. Clusters VII and VIII contained 1,583 and 1,535 metabolites that CSA significantly induced at time points 7M and 5M, respectively (Fig. 2 c). Interestingly, the impact of harvest time on metabolite accumulation levels was more remarkable than that of CSA treatment. Variations in the contents of phenolic acids under CSA treatment A variety of phenolic acids, including 94 flavonoids, 24 iso-flavonoids, and 25 coumarins, were identified by untargeted metabolomics. A heatmap showed the accumulation pattern of all identified phenolic acids under CSA treatment at various time points (Fig. 3 a). Quercetin and eriocitrin, as well as naringenin, were mainly accumulated at 9M and 5M, respectively, in both the CK(control kind) and CSA groups. Moreover, CSA markedly enhanced the contents of Ginkgetin at 5M, Glabrone at 9M, and Glycitin at 7M (Fig. 3 b). Analysis of the differentially expressed genes (DEGs) under CSA treatment Transcriptome sequencing revealed the differences in gene expression between CK and CSA-treated groups. In the T. grandis genome, 47,064 transcripts were detected. In PCA, PC1 and PC2 explained 21.6% and 31.8% of the explained values, respectively (Fig. S1 ). PCA clearly separated the samples into various groups, suggesting major differences between the two treatments. CSA groups at the transcriptional level. A number of DEGs were identified at multiple time points, including 1,028 at 5M; 731 at 6M; 1,307 at 7M; 1,542 at 8M; and 1,274 at 9M (Fig. 4 a). At 7M–9M, most of the DEGs were up-regulated by CSA. The numbers of overlapping DEGs are shown as a Venn diagram (Fig. 4 b). Enrichment analysis of the DEGs responsive to CSA treatment KEGG enrichment analysis classified all DEGs into various metabolism-related categories, including ‘amino acid‘, ‘secondary metabolites’, ‘carbohydrate metabolism’, ‘energy’, ‘lipid’, ‘cofactors and vitamins’, and ‘terpenoids’. For the ‘secondary metabolites’ category, the DEGs were enriched in three KEGG pathways, including flavonoid; tropane, piperidine, and pyridine; alkaloid; and isoquinoline alkaloid biosynthesis. For the ‘carbohydrate metabolism’ category, the DEGs exhibited a high level of enrichment in the KEGG pathways related to pyruvate metabolism; starch and sucrose metabolism; and galactose metabolism. For the terpenoids category, the DEGs demonstrated a high level of enrichment in the KEGG terms brassinosteroid biosynthesis; zeatin biosynthesis; and ‘carotenoid biosynthesis’ (Fig. 4 c). The number of DEGs in each enriched KEGG pathway was counted. Our data showed that most of the secondary metabolites-related DEGs were elevated by CSA. Interestingly, most of the starch and sucrose metabolism- and zeatin biosynthesis-related genes were suppressed by CSA (Fig. 4 d). Analysis of the phenolic acid biosynthesis pathway-related genes A schematic diagram of the phenolic acid biosynthesis pathway is shown in Fig. 5 a. In the present study, five critical intermediates involved in phenolic acid biosynthesis, including cinnamic acid, p-coumaroyl shikimic acid, naringenin chalcone, naringenin, and caffeoyl-CoA, were detected by untargeted metabolomics. A number of crucial enzyme-encoding genes, such as 4CL (two transcripts), C4H (one transcript), COMT (12 transcripts), HCT (four transcripts), CHS (six transcripts), CHI (five transcripts), F3H (two transcripts), and FLS (one transcript), were detected by transcriptomics. The caffeoyl-CoA contents were significantly increased at 9M. The naringenin and naringenin chalcone levels were markedly reduced at 5M (Fig. 5 b). Most of the 4CL-, C4H-, and F5H-encoding genes were remarkably elevated at 8M. Several COMT- and CHS-encoding genes were conspicuously enhanced at 8M and 9M. The expression of CHI- and FLS-encoding genes was significantly suppressed by CSA (Fig. 5 c). Analysis of the transcription factors (TFs) responsive to CSA treatment Promoter analysis indicated several binding sites for WRKY and AP2 TFs in the promoters of phenolic acid biosynthesis pathway-related genes. Thus, the expression patterns of the WRKY and AP2 families are shown in Fig. 6 a. The correlation analysis revealed a close positive association between the differentially expressed TFs and DAMs. Our data identified four key TFs, including WRKY12, AP2-1, AP2-3, and AP2-4, positively correlated with the accumulation of phenolic acids (Fig. 6 b). In subsequent experiments, we focused on HCT to investigate the regulation of phenolic acid biosynthesis in T. grandis . Verification of the potential binding of TFs to their targets The promoters of several phenolic acid biosynthesis-related genes were extracted from the T. grandis genome and screened. Interestingly, the HCT promoter contains a number of WKRY and AP2 binding sites, suggesting that HCT is a potential target of CSA-responsive TFs. The in vivo transcription activation abilities of WRKY12, AP2-1, AP2-3, and AP2-4 were determined by a dual-LUC experiment carried out in Nicotiana benthamiana leaves (Fig. 7 a). Dual-LUC image analysis showed that AP2-1 and AP2-3 significantly activated HCT expression (Fig. 7 b). The full-length CDS of HCT was cloned. Enhanced GFP-tagged HCT was transiently expressed in tobacco epidermal cells to identify the subcellular localization. Our data showed that HCT was localized to the cell membrane (Fig. 7 c). Furthermore, the binding activities of AP2-1 to the HCT promoter were confirmed using a yeast one-hybrid assay (Fig. 7 d). In addition, the heterologous overexpression of HCT enhanced the flavonoid content of tobacco (Fig. 8 ). Discussion With the development of the economy, the demand for high-nutrient nut-based complementary foods is increasing daily. Nuts of T. grandis are considered an important source of nutrients and bioactive ingredients and are frequently employed as food supplements [ 18 ]. T. grandis trees are widely cultivated in China’s subtropical mountainous areas, where the soil is very barren [ 26 ]. Although a large amount of chemical fertilizers has been applied, the effective fertilizer utilization rate is meager [ 27 ]. The excessive use of chemical fertilizers causes massive damage to the environment [ 28 ]. More importantly, chemical fertilizers are quickly fixed in the soil and converted into an insoluble form [ 29 ]. Previous studies have reported the remarkable effects of foliar spray application on the quality of crops. However, the understanding of the impact of foliar fertilizers on the cultivation of T. grandis trees is still limited [ 30 ]. As an essential element, Ca 2+ is the third most abundant in plants [ 31 ]. Clear evidence confirmed the significance of Ca 2+ in various biological processes, such as signal transduction, secondary metabolism, growth, and development [ 32 ]. In our study, CSA, a newly developed chelated calcium fertilizer, was applied to provide soluble Ca 2+ to T. grandis trees. Proteins from T. grandis nuts are valuable nutritional sources in the food industry [ 33 ]. T. grandis kernels are enriched in unsaturated fatty acids, which are essential bioactive components for human health [ 34 ]. Analysis of quality parameters showed that CSA significantly up-regulated the contents of total protein and unsaturated fatty acids, suggesting the positive effects of CSA on the quality of T. grandis nuts. Recently, integrated transcriptomic and metabolomic analyses revealed the regulatory mechanism underlying the secondary metabolism of T. grandis . A multi-omic analysis revealed the responses of terpenoid- and flavonoid-biosynthesis pathways to nanoplastic pollutants [ 35 ]. An integrated omic analysis investigated the involvement of WRKY21 in the regulation of age-induced amino acid biosynthesis in T. grandis nuts [ 19 ]. By referring to the newly published genome of T. grandis , our multi-omic analysis detected 47,064 transcripts, providing sufficient genetic information for uncovering the role of CSA in the activation of the phenolic acid biosynthesis pathway of T. grandis nuts. KEGG enrichment analysis revealed that most of the CSA-responsive genes were enriched in ‘secondary metabolism’, ‘energy metabolism’, and ‘hormone signaling’, indicating that CSA has a comprehensive impact on T. grandis nuts. In plants, calcium sensors might participate in the regulation of secondary metabolite biosynthesis, such as stilbenes, phenolic precursors, and hormones [ 36 ]. Our data showed that most of the secondary metabolism-related DEGs were up-regulated by CSA, suggesting an active role of CSA in the secondary metabolism of T. grandis nuts. A previous study reported that starch and sucrose metabolism participated in the modulation of seed development in T. grandis [ 37 ]. Interestingly, most starch and sucrose metabolism-related genes were down-regulated by CSA. Thus, CSA treatment may modulate the processes involved in seed development in T. grandis by inhibiting energy metabolism. In T. grandis , phytohormones play an essential role in regulating the biosynthesis of squalene and β-sitosterol during the post-ripening process [ 38 ]. In our study, the zeatin biosynthesis pathway was inhibited by CSA, indicating an influence of CSA on the hormone signaling pathway. In plants, flavonoids are classical phenolics containing a 15-C skeleton [ 39 ]. Although most of the phenolic acid biosynthesis-related genes have been identified in T. grandis , the impacts of CSA on the regulation of phenolic acid biosynthesis are largely unknown [ 40 ]. Recently, a number of TFs involved in the regulation of phenolic acid biosynthesis have been recognized in various plants. For example, several Salvia miltiorrhiza TFs, such as SPL7, MYB1, and NPR1-TGA2/NPR4 modules, are involved in phenolic acid biosynthesis [ 41 – 43 ]. In our study, two members of the AP2/ERF family, AP2-1 and AP2-3, were identified as regulators of phenolic acid biosynthesis in T. grandis. In S . miltiorrhiza , overexpression of the two AP2/ERF family TFs, ERF1L1, and ERF115, markedly elevated tanshinone production by regulating the expression of DXR , PAL3, 4CL5, TAT3 , and RAS4 , respectively [ 44 , 45 ]. We identified HCT as a new downstream target of the AP2 subfamily members in T. grandis . The HCT enzyme, a significant regulator of phenolic acid biosynthesis, has been extensively investigated as a prominent member of the BAHD acyltransferase family [ 46 ]. In T. grandis , AP2-1/AP2-3 participated in phenolic acid biosynthesis by inducing HCT expression. The roles of exogenous Ca 2+ in the regulation of phenolic accumulation have been well-investigated in various plants. For example, exogenous Ca 2+ regulates phenolic metabolism and physiological responses of wheat seedlings to UV-B radiation [ 47 ]. CaCl 2 remarkably elevated phenolic acid contents by up-regulating the activities of C4H, PAL, and F5H [ 48 ]. The application of CSA could induce a higher direct entry of Ca 2+ through the leaf vascular system [ 49 ]. We revealed a new regulatory module, Ca 2+ -AP2-HCT, that participated in the regulation of phenolic acid biosynthesis in T. grandis . Our data provides a theoretical basis for the application of Ca 2+ fertilizer for the management of daily fertilizer application in T. grandis trees. Conclusions A transcriptomic and metabolomic analysis was performed to reveal the effects of CSA application on the secondary metabolism in T. grandis nuts. CSA significantly altered the levels of various phenolic acids. We elucidated the role of AP2-HCT in the transcriptional regulation of phenolic acid biosynthesis-related genes and expanded the understanding of the role of calcium fertilizers on plant secondary metabolism. Declarations Ethics approval and consent to participate All samples of T. grandis were collected from Panmugang Chinese torreya base, the Taihu Lake Yuan Town, Lin'an District, Hangzhou City, Zhejiang Province, and stored in Zhejiang Agriculture and Forestry University. All plant materials of T. grandis are consistently used and comply with national and international standards as well as local laws and regulations. The use of all plant materials does not pose any risk to other species in nature. All samples collected in this study do not require specific permission. Consent for publication Not applicable. Competing interests The authors declare that they have no conflicts of interest to report regarding the present study. Funding This work was supported by the cooperative forestry science and technology project of Zhejiang Provincial Academy (2022SY14); the Breeding of New Varieties of Torreya grandis Program (2021C02066-11); the “Pioneer” and “Leading Goose” R&D Program of Zhejiang(2022C02061); The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contribution C.Y.was responsible for the Conceptualization; Q.X.was responsible for the methodology; C.Y. was responsible for software; Q.X., Z.J.and Q.W.were responsible for the validation;Q.X.was responsible for the formal analysis; Z.J.was responsible for the investigation;Q.W. was responsible for the data curation;Q.X.was responsible for the writing—original draft preparation, Z.J.was responsible for the writing—review and editing, C.Y.was responsible for the visualization;W.D.was responsible for the supervision;J.W.was responsible for the project administration;W.Y.was responsible for the funding acquisition. All authors have read and agreed to the published version of the manuscript. Acknowledgement We are grateful to ANOROAD and APT Biotech company for transcriptomic and Metabolomic analysis，respectively. Data Availability Sequence data that support the findings of this study have been deposited in the NCBI database (BioProject ID PRJNA1126763). 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The Effect of Stress Hormones, Ultraviolet C, and Stilbene Precursors on Expression of Calcineurin B-like Protein (CBL) and CBL-Interacting Protein Kinase (CIPK) Genes in Cell Cultures and Leaves of Vitis amurensis Rupr. Plants (Basel). 2023; 12. Zhu R, Gao N, Luo J, Shi W, Basel.). 2024;15. Hu Y, Suo J, Jiang G, Shen J, Cheng H, Lou H, Yu W, Wu J, Song L. The effect of ethylene on squalene and β-sitosterol biosynthesis and its key gene network analysis in Torreya grandis nuts during post-ripening process. Food Chem. 2022;368:130819. Vue B, Zhang S, Chen QH. Flavonoids with Therapeutic Potential in Prostate Cancer. Anticancer Agents Med Chem. 2016;16:1205–29. Zhang F, Ma Z, Qiao Y, Wang Z, Chen W, Zheng S, Yu C, Song L, Lou H, Wu J. Transcriptome sequencing and metabolomics analyses provide insights into the flavonoid biosynthesis in Torreya grandis kernels. Food Chem. 2022;374:131558. Chen R, Cao Y, Wang W, Li Y, Wang D, Wang S, Cao X. Transcription factor SmSPL7 promotes anthocyanin accumulation and negatively regulates phenolic acid biosynthesis in Salvia miltiorrhiza. Plant Sci. 2021;310:110993. Ding M, Xie Y, Zhang Y, Cai X, Zhang B, Ma P, Dong J. Salicylic acid regulates phenolic acid biosynthesis via SmNPR1-SmTGA2/SmNPR4 modules in Salvia miltiorrhiza. J Exp Bot. 2023;74:5736–51. Zhou W, Shi M, Deng C, Lu S, Huang F, Wang Y, Kai G. The methyl jasmonate-responsive transcription factor SmMYB1 promotes phenolic acid biosynthesis in Salvia miltiorrhiza. Hortic Res. 2021;8:10. Sun M, Shi M, Wang Y, Huang Q, Yuan T, Wang Q, Wang C, Zhou W, Kai G. The biosynthesis of phenolic acids is positively regulated by the JA-responsive transcription factor ERF115 in Salvia miltiorrhiza. J Exp Bot. 2019;70:243–54. Huang Q, Sun M, Yuan T, Wang Y, Shi M, Lu S, Tang B, Pan J, Wang Y, Kai G. The AP2/ERF transcription factor SmERF1L1 regulates the biosynthesis of tanshinones and phenolic acids in Salvia miltiorrhiza. Food Chem. 2019;274:368–75. Dixon RA, Barros J. Lignin biosynthesis: old roads revisited and new roads explored. Open Biol. 2019;9:190215. Chen Z, Ma Y, Yang R, Gu Z, Wang P. Effects of exogenous Ca( 2+ ) on phenolic accumulation and physiological changes in germinated wheat (Triticum aestivum L.) under UV-B radiation. Food Chem. 2019;288:368–76. Tian X, He X, Xu J, Yang Z, Fang W, Yin Y. Mechanism of calcium in melatonin enhancement of functional substance-phenolic acid in germinated hulless barley. RSC Adv. 2022;12:29214–22. Giridhar M, Meier B, Imani J, Kogel KH, Peiter E, Vothknecht UC, Chigri F. Comparative analysis of stress-induced calcium signals in the crop species barley and the model plant Arabidopsis thaliana. BMC Plant Biol. 2022;22:447. Additional. material. Additional Declarations No competing interests reported. Supplementary Files file.zip Cite Share Download PDF Status: Published Journal Publication published 23 Jan, 2025 Read the published version in BMC Plant Biology → Version 1 posted Editorial decision: Revision requested 26 Dec, 2024 Reviews received at journal 25 Dec, 2024 Reviewers agreed at journal 19 Dec, 2024 Reviewers agreed at journal 02 Aug, 2024 Reviews received at journal 02 Aug, 2024 Reviewers agreed at journal 15 Jul, 2024 Reviewers invited by journal 11 Jul, 2024 Editor invited by journal 10 Jul, 2024 Editor assigned by journal 10 Jul, 2024 Submission checks completed at journal 10 Jul, 2024 First submitted to journal 19 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4608684","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":335741614,"identity":"49a4bdb4-82cd-4a79-9427-2720c4573c37","order_by":0,"name":"Qiandan Xie","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Qiandan","middleName":"","lastName":"Xie","suffix":""},{"id":335741615,"identity":"9b91eef3-44c8-4b7c-b0ae-b1e3b90a55b2","order_by":1,"name":"Zhengchu Jiang","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Zhengchu","middleName":"","lastName":"Jiang","suffix":""},{"id":335741616,"identity":"3633b24d-976c-433f-bee0-c2e57637bc82","order_by":2,"name":"Chenliang Yu","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Chenliang","middleName":"","lastName":"Yu","suffix":""},{"id":335741617,"identity":"ee5ea3a3-569f-4c8e-bf76-ade761e5cbad","order_by":3,"name":"Qi Wang","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Wang","suffix":""},{"id":335741618,"identity":"372e2173-0f4f-46a9-a337-6180fc9b4fe7","order_by":4,"name":"Wensheng Dai","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Wensheng","middleName":"","lastName":"Dai","suffix":""},{"id":335741619,"identity":"cc11e22a-b8b3-4dd7-b1f9-15dee6572f86","order_by":5,"name":"Jiasheng Wu","email":"","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":false,"prefix":"","firstName":"Jiasheng","middleName":"","lastName":"Wu","suffix":""},{"id":335741620,"identity":"2c981be2-f707-4ecb-877b-49df92dd73d3","order_by":6,"name":"Weiwu Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACNvbmAwcSDCTk+IGcD0DM2EBICx/PscQDHypsjCUbGBhnEKVFTiLH+OCMM2mJGw4Qq4VNIsfgMG/bYcbN5w8/bOZhsJHdcID52QO8WnieFYC0MJsdOGYI1JJmvOEAm7kBXi3syRtAWtjMDjaYP+ZhOAx0IQ+bBF4tDAlgh/EYN7N/BNrynwgtHCkGIO9LGLDxgBx2gAgtPMcSQIFsIHGGp7BxjkGy8UygI/FqkW9vPvwBGJX1/f3HNza8qbCT7Tve/AyvFjQACipmEtSPglEwCkbBKMAOAJAuTu1+uLhMAAAAAElFTkSuQmCC","orcid":"","institution":"Zhejiang A \u0026 F University","correspondingAuthor":true,"prefix":"","firstName":"Weiwu","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2024-06-20 02:51:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4608684/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4608684/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-025-06113-9","type":"published","date":"2025-01-23T15:58:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61763166,"identity":"bcff5800-fef9-4162-b023-b67355dc87b1","added_by":"auto","created_at":"2024-08-05 09:51:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":326991,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of CSA treatment on the quality parameters of\u003cem\u003eT. grandis\u003c/em\u003e,\u003cem\u003e \u003c/em\u003eincluding the contents of soluble proteins (a), starch (b), soluble sugars (c), oils (d), and fatty acid components (e) in\u003cem\u003e T. grandis \u003c/em\u003eseeds. Error bars represent mean ± SD (n = 5). Student’s t test: *, P \u0026lt; 0.05, **, P \u0026lt; 0.01, or ***, P \u0026lt; 0.001\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/92b07fd5ae88926e3b52dc16.png"},{"id":61763164,"identity":"be3f5e10-b970-4910-adeb-ada8fa86558a","added_by":"auto","created_at":"2024-08-05 09:51:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1637732,"visible":true,"origin":"","legend":"\u003cp\u003eUntargeted metabolomic analysis reveals the differences in the metabolite levels under CSA treatment. (a) The numbers of metabolites grouped into various categories are shown in pies. (b) A heatmap of the abundance of metabolites in the different sample groups; the scale ranged from -2 to +2 on a Log\u003csub\u003e2\u003c/sub\u003e scale. (c) MeV clustering of the temporally accumulated metabolites indicated by red ovals.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/e08563441b77659cb2437ba2.png"},{"id":61763171,"identity":"12dffc0c-60c2-4144-ae96-1ed308824841","added_by":"auto","created_at":"2024-08-05 09:51:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1965523,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential accumulation of phenolic acids under CSA treatment. (a) Heatmap of the abundance of three types of phenolic acids, including flavonoids, iso-flavonoids, and coumarins. The heatmap scale ranged from -2 (green) to +2 (red) on a Log\u003csub\u003e2\u003c/sub\u003e scale. (b) Quantification of 11 common phenolic acids. *indicates significant differences in the levels of each phenolic acid within each comparison (P \u0026lt; 0.05). Error bars represent mean ± SD (n = 3).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/913a6d704a0c2140db335013.png"},{"id":61763167,"identity":"e65f40f4-5cef-4036-b04b-d8dd075ad097","added_by":"auto","created_at":"2024-08-05 09:51:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1784023,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the differentially expressed genes (DEGs) under CSA treatment. (a) The number of DEGs at different periods of CSA treatment. (b) Venn diagrams of the DEGs at varying durations of CSA treatment. (c) Enrichment analysis of metabolism-related KEGG terms. *indicates significant differences in each KEGG term. Blue color denotes significant enrichment (p \u0026lt;0.05), with a darker blue shade indicating greater significance. (d) The number of DEGs identified in the different metabolic pathways. A: flavonoid biosynthesis; B: tropane, piperidine, and pyridine alkaloid biosynthesis; C: isoquinoline alkaloid biosynthesis; D: pyruvate metabolism; E: starch and sucrose metabolism; F: galactose metabolism.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/e57a57ce02d4422b04808ed9.png"},{"id":61763168,"identity":"c86c5d77-57d5-4b85-a853-4b0339bcb2c8","added_by":"auto","created_at":"2024-08-05 09:51:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":903578,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated metabolomic and transcriptomic analysis of the phenolic acid biosynthesis pathway. (a) Schematic diagram of the pathway. The number in the bracket indicates the gene copy number. (b) Quantification of six common phenolic acids. *indicates significant differences in the contents of each phenolic acid within each comparison (P \u0026lt;0.05). Error bars represent mean ± SD (n = 3). (c) Expression analysis of genes encoding enzymes related to the pathway. The heatmap scale ranged from -1 to +1 on a Log2 scale.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/a64a36789b1a8e8346a953c8.png"},{"id":61763835,"identity":"5ec2696e-00fa-4f39-b042-d2bedc04f8ce","added_by":"auto","created_at":"2024-08-05 09:59:24","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3177900,"visible":true,"origin":"","legend":"\u003cp\u003eScreening of key transcription factors involved in the phenolic acid biosynthesis pathway. (a) Expression pattern of WRKY and AP2 family members under CK and CSA treatments. (b) Correlation analysis of crucial transcription factors involved in the phenolic acid biosynthesis pathway.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/c118e89f15a7f4b22d7234f0.png"},{"id":61763834,"identity":"ca3fb33e-76ce-4182-b32f-37d25efb5c8f","added_by":"auto","created_at":"2024-08-05 09:59:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2658117,"visible":true,"origin":"","legend":"\u003cp\u003eTranscriptional regulation of the phenolic acid biosynthesis pathway genes in \u003cem\u003eT. grandis\u003c/em\u003e nuts. (a) The dual luciferase (LUC) assays revealed the transcription activation function of AP2-1 and AP2-3 on \u003cem\u003eHCT\u003c/em\u003e expression. CK: The \u003cem\u003eHCT\u003c/em\u003e promoter was cloned into the empty 62SK vector. (b) Quantitative data of the dual-LUC assay. *indicates significant changes at P value \u0026lt;0.05. (c) Subcellular localization of the \u003cem\u003eHCT\u003c/em\u003e enzyme. (d) The binding activities of AP2-1 and AP2-3 to the \u003cem\u003eHCT\u003c/em\u003e promoter were confirmed using yeast one-hybrid assay.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/e16d7df32a755e044d08f264.png"},{"id":61763169,"identity":"d0bd88f5-7b99-4666-b814-5600355b6ac1","added_by":"auto","created_at":"2024-08-05 09:51:23","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":41137,"visible":true,"origin":"","legend":"\u003cp\u003eTransient overexpression of \u003cem\u003eHCT\u003c/em\u003e increased total flavonoid content in tobacco leaves. **indicates significant changes at P value \u0026lt;0.01. Error bars represent mean ± SD (n = 5).\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/3d13a48f58bb5607c83e2abf.png"},{"id":74858641,"identity":"199c29b4-47c2-4149-8448-1b1f917cda1a","added_by":"auto","created_at":"2025-01-27 16:12:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15614032,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/4ee54bb1-a200-4c27-9b0f-6aedeff4b957.pdf"},{"id":61764239,"identity":"c0a22f6b-f43d-4e98-9cb4-f291b71fcd72","added_by":"auto","created_at":"2024-08-05 10:07:24","extension":"zip","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1150028,"visible":true,"origin":"","legend":"","description":"","filename":"file.zip","url":"https://assets-eu.researchsquare.com/files/rs-4608684/v1/7691ebfe67a29b34fd767595.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated metabolomics and transcriptomics reveal the role of calcium sugar alcohol in the regulation of phenolic acid biosynthesis in Torreya grandis nuts","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlant growth and development are influenced by various genetic and environmental factors, including transcription factors and nutrients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although the extensive application of chemical fertilizers can increase crop yield, it poses a considerable threat to the environment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Biofortification is a process of adding essential nutrients and growth-promoting chemicals to improve the nutritional value of plants [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With an improvement in the living standards of people, organic agriculture has recieved more attention recently.\u003c/p\u003e \u003cp\u003eFoliar fertilizers sprayed on the leaves of plants can provide essential nutrients and mitigate the accumulation of heavy metals in the aboveground parts [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As an environmentally friendly fertilizer, foliar fertilizer mainly consists of growth regulators, organic acids, and various mineral elements [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For example, the foliar application of Zn\u003csup\u003e2+\u003c/sup\u003e increased the production and quality of fruit crops [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The foliar application of silicon enhanced the growth of crops and improved the efficiency of carbon and phosphorus (P) utilization [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Foliar-applied iron oxide nanoparticles increased the plant biomass, chlorophyll contents, and other growth parameters of maize seedlings [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. More experiments confirmed that the contents of nitrogen, P, and magnesium can be increased by applying corresponding foliar fertilizers [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCalcium (Ca\u003csup\u003e2+\u003c/sup\u003e) is an essential component of the cell structure and also serves as a crucial secondary messenger in various signal transduction pathways [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The application of Ca\u003csup\u003e2+\u003c/sup\u003e improved the tolerance of plants to stresses by activating the antioxidant system [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. CaCl\u003csub\u003e2\u003c/sub\u003e can alleviate the negative effects of drought-triggered and-related stresses [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Considering the impeded translocation of Ca\u003csup\u003e2+\u003c/sup\u003e fertilizers from the underground parts to leaves, the spraying of Ca\u003csup\u003e2+\u003c/sup\u003e on developing leaves is reported [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The primary Ca\u003csup\u003e2+\u003c/sup\u003e-based fertilizers, including calcium chloride, calcium acetate, and calcium nitrate, are limited by their solubility and relatively low utilization rates [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recently, calcium sugar alcohol (CSA), a newly developed chelated Ca\u003csup\u003e2+\u003c/sup\u003e fertilizer with good water solubility, has been widely applied in agriculture [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eTorreya grandis\u003c/em\u003e is a notable tree species indigenous to the subtropical region of China [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. An evergreen coniferous tree, \u003cem\u003eT. grandis\u003c/em\u003e possesses a drupe-like fruit containing a nut that is a rich source of nutrients and bioactive ingredients, such as alkaloids, flavonoids, and tannins [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. \u003cem\u003eT. grandis\u003c/em\u003e nuts are often used as food supplements to promote cardiovascular health. Due to increasing demand, the production of nuts has expanded significantly [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Since \u003cem\u003eT. grandis\u003c/em\u003e trees mainly grow in subtropical mountainous regions, they face severe nutrient deficiencies [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Chemical fertilizers at high doses have severe adverse impacts, such as water pollution and soil acidification [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Although foliar fertilizers have been widely applied, their roles in the secondary metabolism of \u003cem\u003eT. grandis\u003c/em\u003e are mainly unknown.\u003c/p\u003e \u003cp\u003eUtilizing large-scale identification technology has enabled investigations of the metabolic pathways responsive to foliar fertilizers [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this study, nuts from the control and CSA-treated \u003cem\u003eT. grandis\u003c/em\u003e trees were harvested for an integrated metabolomic and transcriptomic analysis. The results can provide a scientific basis for cultivating and managing \u003cem\u003eT. grandis\u003c/em\u003e nuts by investigating the effects of CSA on the metabolism of phenolics in them.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant material and growth conditions\u003c/h2\u003e \u003cp\u003eThirty 15-year old \u003cem\u003eTorreya grandis 'Merrilli'\u003c/em\u003e trees with the same site condition, growth and fruit quantity were selected as the research objects in Panmugang Chinese Torreya base(119\u0026deg;57\u0026prime; E,30\u0026deg;30\u0026prime; N), and their plant height and fruit quantity were recorded. The voucher specimens were identified by Prof. Wensheng Dai and deposited in the Zhejiang A\u0026amp;F University Intelligent Experimental Building Plant Specimen Room N205.Foliar fertilizer was applied from March to April 2022. The different leaf surface fertilizer treatments were CK (control group; pure water) and CSA (calcium sugar alcohol; high strength, water-soluble calcium fertilizer). Leaf fertilizer was purchased from Shenzhen Dugao Biological New Technology Co., Ltd. The fertilizer was diluted 1000-fold, once every 20 days, a total of three times. The CK and CSA treatment groups included five trees each. A 10 L electric spray bottle was employed to spray 1 L of fertilizer per tree at a time. The samples were taken once during May, June, July, August, and September 2022. They were named 5M, 6M, 7M, 8M, and 9M, respectively.All materials were stored in the refrigerator of -80 ℃ in the State Key Laboratory of Subtropical Forest Cultivation of Zhejiang Agriculture and Forestry University.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of the physiological and nutritional parameters\u003c/h2\u003e \u003cp\u003eMature fresh \u003cem\u003eT. grandis\u003c/em\u003e nuts were randomly collected from independent trees with different treatments. Then, the seed traits were determined based on our previous work. The longitudinal and transverse diameters of the seed nucleus and kernel were measured using Vernier calipers with an accuracy of 0.01 cm. The single nucleus and kernel masses were calculated by employing a 1000th-range electronic balance. Soluble sugar and starch contents in seeds were determined using commercial kits from Solarbio Life Science Co, Ltd (codes: BC0030 and BC0700). The kernel oil content was ascertained by the national standard GB/T 14772\u0026thinsp;\u0026minus;\u0026thinsp;2008 Soxhlet extraction method. The extracted oil was methylated, and the fatty acid components were estimated by the peak area normalization method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMetabolite extraction\u003c/h2\u003e \u003cp\u003eThe seed kernel samples (80 mg each) were flash-frozen in liquid N\u003csub\u003e2\u003c/sub\u003e and powdered. For metabolite extraction, 1000 \u0026micro;L of methanol\u0026ndash;acetonitrile\u0026ndash;H\u003csub\u003e2\u003c/sub\u003eO solution (2:2:1, v/v/v) was added to the sample. The extract was centrifuged at 12,000 g for 20 min at 4\u0026deg;C. The supernatant was vacuum-dried and redissolved in 100 \u0026micro;L of acetonitrile\u0026ndash;H\u003csub\u003e2\u003c/sub\u003eO (1:1, v/v) solution. The resulting solution was used for LC-MS/MS analysis. For each time point and each treatment, three biological replicates were collected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eLC-MS/MS analysis\u003c/h2\u003e \u003cp\u003eAn LC-MS/MS analysis was carried out using a TripleTOF 6600 quadrupole time-of-flight (AB Sciex) coupled to a 290 Infinity LC ultrahigh performance liquid chromatography (Agilent Technologies). The column temperature was 40\u0026deg;C, the flow rate was 0.4 mL/min, and the injection volume was 2 \u0026micro;L. Following were the ESI source conditions: the ion source gas1 (Gas1) was set to 60, the ion source gas2 (Gas2) to 60, and the curtain gas (CUR) to 30. The source temperature was 600\u0026deg;C, and IonSpray Voltage Floating (ISVF) was 5500 V. During auto MS/MS acquisition, the instrument was set to collect within the m/z range of 25\u0026ndash;1000 Da, and the accumulation time for product ion scan was set at 0.05 s/spectra. Metabolite ion scanning was performed in an Information Based Acquisition (IDA) mode with high sensitivity. The parameters settings were: the collision energy (CE) at 35 V\u0026thinsp;\u0026plusmn;\u0026thinsp;15 eV; declustering potential (DP) at \u0026plusmn;\u0026thinsp;60 V; excluded isotopes were \u0026lt;\u0026thinsp;4 Da; and candidate ions to be monitored per cycle were set at 10.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eUntargeted metabolomics\u003c/h2\u003e \u003cp\u003eThe original MS scanning data was converted into MzXML files by employing the ProteoWizard MSConvert software. The following parameters were used when selecting peaks: center wave m/z set to 10 ppm, peak width to c (10, 60), and prefilter to c (10, 100). When grouping peaks, bw was set to 5, mz wid to 0.025, and min frac to 0.5. Isotopes and adducts were annotated utilizing the Metabolite pProfile Annotation software algorithm. Metabolites were identified by comparing the accurate m/z values (\u0026lt;\u0026thinsp;10 ppm) with the MS/MS spectra established from an internal database of available standards. Metabolites were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database by matching the precise molecular weight data (m/z). An internal metabolite fragment spectral library was applied to validate metabolite identification. The Wilcoxon test was employed to detect the variations in metabolite concentrations between two groups of samples. The P-values of multiple tests were adjusted using the FDR (Benjamin Hochberg) method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA isolation and sequencing\u003c/h2\u003e \u003cp\u003eRNA was isolated from the \u003cem\u003eT. grandis\u003c/em\u003e nuts using TRIzol reagent (Invitrogen, Shanghai, China) by following the instructions. The high-quality RNAs (integrity number\u0026thinsp;\u0026gt;\u0026thinsp;7.0) were selected to construct the cDNA library. They were fragmented and reverse-transcribed to cDNA. RNA was sequenced on an Illumina HiSeq\u0026trade; 6000 platform at LC-Bio, Hangzhou, China, to produce 50- or 100-bp single- or paired-end small reads.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eTranscriptomics\u003c/h2\u003e \u003cp\u003eReads containing unknown nucleotides (N\u0026thinsp;\u0026lt;\u0026thinsp;5%) and low-quality bases (Q value\u0026thinsp;\u0026lt;\u0026thinsp;19) were removed. The HISAT2 (ver.2.0.5) program with default parameters aligned all clean reads to the \u003cem\u003eT. grandis\u003c/em\u003e genome [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. By calculating FPKM (Fragments Per Kilobase of transcript Per Million mapped reads), the FeatureCounts (ver.1.5.0) software tallied the location reads of each gene. The DESeq R (ver.4.0.4) software distinguished the differentially expressed genes (DEGs) in each compared group with a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and a multiple change\u0026thinsp;\u0026ge;\u0026thinsp;2-fold.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eGene cloning and promoter analysis\u003c/h2\u003e \u003cp\u003eThe complete coding sequences (CDSs) of WRKY2, AP2-1, AP2-3, and AP2-4 were isolated from the \u003cem\u003eT. grandis\u003c/em\u003e genome and PCR-amplified. The sequences of the primers used are presented in Table S2. The genomic DNAs from the \u003cem\u003eT. grandis\u003c/em\u003e tissues were isolated using a kit. The 2000-bp sequence of the \u003cem\u003eHCT\u003c/em\u003e promoter was extracted from the \u003cem\u003eT. grandis\u003c/em\u003e genome.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubcellular localization\u003c/h2\u003e \u003cp\u003eThe CDS was cloned into the pCAMBIA1300-GFP vector and fused with the c-terminus of the artificial green fluorescent protein (GFP). All gene sequences obtained in this study are listed in (Table S3). The empty GFP vector was used as a control. All vectors were transiently expressed in tobacco epidermal cells through Agrobacterium tumefaciens (GV3101)-mediated transformation. The fluorescence of the GFP fusion protein was detected employing an LSM710 confocal microscope (Carl Zeiss AG, Oberkochen, Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDual-luciferase assay\u003c/h2\u003e \u003cp\u003eThe WRKY2, AP2-1, AP2-3, and AP2-4 cDNAs were inserted into pGreenII62-SK vectors as the effectors, and the \u003cem\u003eHCT\u003c/em\u003e promoter was inserted into the pGreenII0800-LUC vector as the reporter. The constructed vectors were co-expressed in tobacco leaves by utilizing a transient transformation system mediated by Mycobacterium-induced root cancer (GV3101). The binding activities of the TFs with their specific promoters were calculated based on the LUC\u0026ndash;REN ratio using a dual-LUC assay kit (Promega, Beijing, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eYeast one-hybrid (Y1-H) assay\u003c/h2\u003e \u003cp\u003eIn this study, Y1-H was conducted per the Yeast Protocols Handbook (Clontech) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The promoters were amplified, and the cis-acting element was truncated using the website- \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatics.psb.ugent.be/webtools/plantcare/html/\u003c/span\u003e\u003cspan address=\"http://bioinformatics.psb.ugent.be/webtools/plantcare/html/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e and then cloned into the pLacZi vector. The pLacZi\u0026thinsp;+\u0026thinsp;HCT was constructed by PCR-based insertion of the TF sequences into PB42AD. Yeast cells were then co-transformed using pLacZi\u0026thinsp;+\u0026thinsp;HCT with pB42AD\u0026thinsp;+\u0026thinsp;AP2-1 or pB42AD\u0026thinsp;+\u0026thinsp;AP2-3 vectors. Next, six yeast cells were randomly selected for the detection of positive clones after coating the transformation products with SD/-Trp-Ura medium at 30\u0026deg;C for three days. For observing the color reaction, the PCR-confirmed bacteria were identified by detecting the appropriate yeast cells by spreading them on SD/-Trp-Ura/Gal/Raf/X-Gal agar color plates.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eEffect of CSA treatment on the quality parameters of T. grandis nuts\u003c/h2\u003e \u003cp\u003eTo analyze the effects of CSA treatment on the quality of \u003cem\u003eT. grandis\u003c/em\u003e nuts, a series of quality parameters, including protein, starch, soluble sugar, and oil contents, were determined. These contents were significantly increased by CSA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea-d). Considering the complexity of oil composition, the levels of ten individual oil components were determined. CSA slightly down-regulated the levels of linoleic acid and unsaturated fatty acids (Figure.1e). These results indicated a marked impact of CSA treatment on the contents of total protein, starch, and soluble sugars in \u003cem\u003eT. grandis\u003c/em\u003e nuts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOverview of the untargeted metabolomes\u003c/h2\u003e \u003cp\u003eNuts harvested at different time points were subjected to LC-MS/MS analysis to reveal the differences in metabolites between the control and CSA-treated groups. A total of 20,006 ion features were identified, which were grouped into 1394 annotated metabolites (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All these metabolites were categorized into 326 lipids, 272 phenylpropanoids and polyketides, 153 benzenoids, 131 organoheterocyclic compounds, and 122 organic oxygen compounds (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eClustering of metabolites under CSA treatment at different time points\u003c/h2\u003e \u003cp\u003eThe metabolomic profiling revealed remarkable variations in the metabolomes of the CK and CSA treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). All metabolites were grouped into eight different clusters to identify the accumulation of metabolites in a time-dependent manner. In detail, Cluster I contained 2,915 5M-, Cluster II contained 2,569 8M-, and Cluster III contained 4,480 9M-specifically accumulated metabolites. Clusters VII and VIII contained 1,583 and 1,535 metabolites that CSA significantly induced at time points 7M and 5M, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Interestingly, the impact of harvest time on metabolite accumulation levels was more remarkable than that of CSA treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eVariations in the contents of phenolic acids under CSA treatment\u003c/h2\u003e \u003cp\u003eA variety of phenolic acids, including 94 flavonoids, 24 iso-flavonoids, and 25 coumarins, were identified by untargeted metabolomics. A heatmap showed the accumulation pattern of all identified phenolic acids under CSA treatment at various time points (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Quercetin and eriocitrin, as well as naringenin, were mainly accumulated at 9M and 5M, respectively, in both the CK(control kind) and CSA groups. Moreover, CSA markedly enhanced the contents of Ginkgetin at 5M, Glabrone at 9M, and Glycitin at 7M (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the differentially expressed genes (DEGs) under CSA treatment\u003c/h2\u003e \u003cp\u003eTranscriptome sequencing revealed the differences in gene expression between CK and CSA-treated groups. In the T. grandis genome, 47,064 transcripts were detected. In PCA, PC1 and PC2 explained 21.6% and 31.8% of the explained values, respectively (Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). PCA clearly separated the samples into various groups, suggesting major differences between the two treatments. CSA groups at the transcriptional level. A number of DEGs were identified at multiple time points, including 1,028 at 5M; 731 at 6M; 1,307 at 7M; 1,542 at 8M; and 1,274 at 9M (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). At 7M\u0026ndash;9M, most of the DEGs were up-regulated by CSA. The numbers of overlapping DEGs are shown as a Venn diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eEnrichment analysis of the DEGs responsive to CSA treatment\u003c/h2\u003e \u003cp\u003eKEGG enrichment analysis classified all DEGs into various metabolism-related categories, including \u0026lsquo;amino acid\u0026lsquo;, \u0026lsquo;secondary metabolites\u0026rsquo;, \u0026lsquo;carbohydrate metabolism\u0026rsquo;, \u0026lsquo;energy\u0026rsquo;, \u0026lsquo;lipid\u0026rsquo;, \u0026lsquo;cofactors and vitamins\u0026rsquo;, and \u0026lsquo;terpenoids\u0026rsquo;. For the \u0026lsquo;secondary metabolites\u0026rsquo; category, the DEGs were enriched in three KEGG pathways, including flavonoid; tropane, piperidine, and pyridine; alkaloid; and isoquinoline alkaloid biosynthesis. For the \u0026lsquo;carbohydrate metabolism\u0026rsquo; category, the DEGs exhibited a high level of enrichment in the KEGG pathways related to pyruvate metabolism; starch and sucrose metabolism; and galactose metabolism. For the terpenoids category, the DEGs demonstrated a high level of enrichment in the KEGG terms brassinosteroid biosynthesis; zeatin biosynthesis; and \u0026lsquo;carotenoid biosynthesis\u0026rsquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). The number of DEGs in each enriched KEGG pathway was counted. Our data showed that most of the secondary metabolites-related DEGs were elevated by CSA. Interestingly, most of the starch and sucrose metabolism- and zeatin biosynthesis-related genes were suppressed by CSA (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the phenolic acid biosynthesis pathway-related genes\u003c/h2\u003e \u003cp\u003eA schematic diagram of the phenolic acid biosynthesis pathway is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003ea. In the present study, five critical intermediates involved in phenolic acid biosynthesis, including cinnamic acid, p-coumaroyl shikimic acid, naringenin chalcone, naringenin, and caffeoyl-CoA, were detected by untargeted metabolomics. A number of crucial enzyme-encoding genes, such as \u003cem\u003e4CL\u003c/em\u003e (two transcripts), \u003cem\u003eC4H\u003c/em\u003e (one transcript), \u003cem\u003eCOMT\u003c/em\u003e (12 transcripts), \u003cem\u003eHCT\u003c/em\u003e (four transcripts), \u003cem\u003eCHS\u003c/em\u003e (six transcripts), \u003cem\u003eCHI\u003c/em\u003e (five transcripts), \u003cem\u003eF3H\u003c/em\u003e (two transcripts), and \u003cem\u003eFLS\u003c/em\u003e (one transcript), were detected by transcriptomics.\u003c/p\u003e \u003cp\u003eThe caffeoyl-CoA contents were significantly increased at 9M. The naringenin and naringenin chalcone levels were markedly reduced at 5M (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Most of the 4CL-, C4H-, and F5H-encoding genes were remarkably elevated at 8M. Several COMT- and CHS-encoding genes were conspicuously enhanced at 8M and 9M. The expression of CHI- and FLS-encoding genes was significantly suppressed by CSA (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the transcription factors (TFs) responsive to CSA treatment\u003c/h2\u003e \u003cp\u003ePromoter analysis indicated several binding sites for WRKY and AP2 TFs in the promoters of phenolic acid biosynthesis pathway-related genes. Thus, the expression patterns of the WRKY and AP2 families are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003ea. The correlation analysis revealed a close positive association between the differentially expressed TFs and DAMs. Our data identified four key TFs, including WRKY12, AP2-1, AP2-3, and AP2-4, positively correlated with the accumulation of phenolic acids (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). In subsequent experiments, we focused on \u003cem\u003eHCT\u003c/em\u003e to investigate the regulation of phenolic acid biosynthesis in \u003cem\u003eT. grandis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eVerification of the potential binding of TFs to their targets\u003c/h2\u003e \u003cp\u003eThe promoters of several phenolic acid biosynthesis-related genes were extracted from the \u003cem\u003eT. grandis\u003c/em\u003e genome and screened. Interestingly, the \u003cem\u003eHCT\u003c/em\u003e promoter contains a number of WKRY and AP2 binding sites, suggesting that \u003cem\u003eHCT\u003c/em\u003e is a potential target of CSA-responsive TFs. The in vivo transcription activation abilities of WRKY12, AP2-1, AP2-3, and AP2-4 were determined by a dual-LUC experiment carried out in Nicotiana benthamiana leaves (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). Dual-LUC image analysis showed that AP2-1 and AP2-3 significantly activated \u003cem\u003eHCT\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). The full-length CDS of \u003cem\u003eHCT\u003c/em\u003e was cloned. Enhanced GFP-tagged \u003cem\u003eHCT\u003c/em\u003e was transiently expressed in tobacco epidermal cells to identify the subcellular localization. Our data showed that \u003cem\u003eHCT\u003c/em\u003e was localized to the cell membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003ec). Furthermore, the binding activities of AP2-1 to the \u003cem\u003eHCT\u003c/em\u003e promoter were confirmed using a yeast one-hybrid assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). In addition, the heterologous overexpression of \u003cem\u003eHCT\u003c/em\u003e enhanced the flavonoid content of tobacco (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith the development of the economy, the demand for high-nutrient nut-based complementary foods is increasing daily. Nuts of \u003cem\u003eT. grandis\u003c/em\u003e are considered an important source of nutrients and bioactive ingredients and are frequently employed as food supplements [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. \u003cem\u003eT. grandis\u003c/em\u003e trees are widely cultivated in China\u0026rsquo;s subtropical mountainous areas, where the soil is very barren [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although a large amount of chemical fertilizers has been applied, the effective fertilizer utilization rate is meager [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The excessive use of chemical fertilizers causes massive damage to the environment [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. More importantly, chemical fertilizers are quickly fixed in the soil and converted into an insoluble form [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Previous studies have reported the remarkable effects of foliar spray application on the quality of crops. However, the understanding of the impact of foliar fertilizers on the cultivation of \u003cem\u003eT. grandis\u003c/em\u003e trees is still limited [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs an essential element, Ca\u003csup\u003e2+\u003c/sup\u003e is the third most abundant in plants [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Clear evidence confirmed the significance of Ca\u003csup\u003e2+\u003c/sup\u003e in various biological processes, such as signal transduction, secondary metabolism, growth, and development [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In our study, CSA, a newly developed chelated calcium fertilizer, was applied to provide soluble Ca\u003csup\u003e2+\u003c/sup\u003e to \u003cem\u003eT. grandis\u003c/em\u003e trees. Proteins from \u003cem\u003eT. grandis\u003c/em\u003e nuts are valuable nutritional sources in the food industry [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. \u003cem\u003eT. grandis\u003c/em\u003e kernels are enriched in unsaturated fatty acids, which are essential bioactive components for human health [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Analysis of quality parameters showed that CSA significantly up-regulated the contents of total protein and unsaturated fatty acids, suggesting the positive effects of CSA on the quality of \u003cem\u003eT. grandis\u003c/em\u003e nuts.\u003c/p\u003e \u003cp\u003eRecently, integrated transcriptomic and metabolomic analyses revealed the regulatory mechanism underlying the secondary metabolism of \u003cem\u003eT. grandis\u003c/em\u003e. A multi-omic analysis revealed the responses of terpenoid- and flavonoid-biosynthesis pathways to nanoplastic pollutants [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. An integrated omic analysis investigated the involvement of WRKY21 in the regulation of age-induced amino acid biosynthesis in \u003cem\u003eT. grandis\u003c/em\u003e nuts [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. By referring to the newly published genome of \u003cem\u003eT. grandis\u003c/em\u003e, our multi-omic analysis detected 47,064 transcripts, providing sufficient genetic information for uncovering the role of CSA in the activation of the phenolic acid biosynthesis pathway of \u003cem\u003eT. grandis\u003c/em\u003e nuts.\u003c/p\u003e \u003cp\u003eKEGG enrichment analysis revealed that most of the CSA-responsive genes were enriched in \u0026lsquo;secondary metabolism\u0026rsquo;, \u0026lsquo;energy metabolism\u0026rsquo;, and \u0026lsquo;hormone signaling\u0026rsquo;, indicating that CSA has a comprehensive impact on \u003cem\u003eT. grandis\u003c/em\u003e nuts. In plants, calcium sensors might participate in the regulation of secondary metabolite biosynthesis, such as stilbenes, phenolic precursors, and hormones [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Our data showed that most of the secondary metabolism-related DEGs were up-regulated by CSA, suggesting an active role of CSA in the secondary metabolism of \u003cem\u003eT. grandis\u003c/em\u003e nuts. A previous study reported that starch and sucrose metabolism participated in the modulation of seed development in \u003cem\u003eT. grandis\u003c/em\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Interestingly, most starch and sucrose metabolism-related genes were down-regulated by CSA. Thus, CSA treatment may modulate the processes involved in seed development in \u003cem\u003eT. grandis\u003c/em\u003e by inhibiting energy metabolism. In \u003cem\u003eT. grandis\u003c/em\u003e, phytohormones play an essential role in regulating the biosynthesis of squalene and β-sitosterol during the post-ripening process [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In our study, the zeatin biosynthesis pathway was inhibited by CSA, indicating an influence of CSA on the hormone signaling pathway.\u003c/p\u003e \u003cp\u003eIn plants, flavonoids are classical phenolics containing a 15-C skeleton [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Although most of the phenolic acid biosynthesis-related genes have been identified in \u003cem\u003eT. grandis\u003c/em\u003e, the impacts of CSA on the regulation of phenolic acid biosynthesis are largely unknown [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Recently, a number of TFs involved in the regulation of phenolic acid biosynthesis have been recognized in various plants. For example, several \u003cem\u003eSalvia miltiorrhiza\u003c/em\u003e TFs, such as SPL7, MYB1, and NPR1-TGA2/NPR4 modules, are involved in phenolic acid biosynthesis [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In our study, two members of the AP2/ERF family, AP2-1 and AP2-3, were identified as regulators of phenolic acid biosynthesis in \u003cem\u003eT. grandis.\u003c/em\u003e In \u003cem\u003eS\u003c/em\u003e. \u003cem\u003emiltiorrhiza\u003c/em\u003e, overexpression of the two AP2/ERF family TFs, ERF1L1, and ERF115, markedly elevated tanshinone production by regulating the expression of \u003cem\u003eDXR\u003c/em\u003e, \u003cem\u003ePAL3, 4CL5, TAT3\u003c/em\u003e, and \u003cem\u003eRAS4\u003c/em\u003e, respectively [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. We identified \u003cem\u003eHCT\u003c/em\u003e as a new downstream target of the AP2 subfamily members in \u003cem\u003eT. grandis\u003c/em\u003e. The HCT enzyme, a significant regulator of phenolic acid biosynthesis, has been extensively investigated as a prominent member of the BAHD acyltransferase family [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In \u003cem\u003eT. grandis\u003c/em\u003e, AP2-1/AP2-3 participated in phenolic acid biosynthesis by inducing \u003cem\u003eHCT\u003c/em\u003e expression.\u003c/p\u003e \u003cp\u003eThe roles of exogenous Ca\u003csup\u003e2+\u003c/sup\u003e in the regulation of phenolic accumulation have been well-investigated in various plants. For example, exogenous Ca\u003csup\u003e2+\u003c/sup\u003e regulates phenolic metabolism and physiological responses of wheat seedlings to UV-B radiation [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. CaCl\u003csub\u003e2\u003c/sub\u003e remarkably elevated phenolic acid contents by up-regulating the activities of C4H, PAL, and F5H [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The application of CSA could induce a higher direct entry of Ca\u003csup\u003e2+\u003c/sup\u003e through the leaf vascular system [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. We revealed a new regulatory module, Ca\u003csup\u003e2+\u003c/sup\u003e-AP2-HCT, that participated in the regulation of phenolic acid biosynthesis in \u003cem\u003eT. grandis\u003c/em\u003e. Our data provides a theoretical basis for the application of Ca\u003csup\u003e2+\u003c/sup\u003e fertilizer for the management of daily fertilizer application in \u003cem\u003eT. grandis\u003c/em\u003e trees.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA transcriptomic and metabolomic analysis was performed to reveal the effects of CSA application on the secondary metabolism in \u003cem\u003eT. grandis\u003c/em\u003e nuts. CSA significantly altered the levels of various phenolic acids. We elucidated the role of AP2-HCT in the transcriptional regulation of phenolic acid biosynthesis-related genes and expanded the understanding of the role of calcium fertilizers on plant secondary metabolism.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eAll samples of \u003cem\u003eT. grandis\u003c/em\u003e were collected from Panmugang Chinese torreya base, the Taihu Lake Yuan Town, Lin'an District, Hangzhou City, Zhejiang Province, and stored in Zhejiang Agriculture and Forestry University. All plant materials of \u003cem\u003eT. grandis\u003c/em\u003e are consistently used and comply with national and international standards as well as local laws and regulations. The use of all plant materials does not pose any risk to other species in nature. All samples collected in this study do not require specific permission.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflicts of interest to report regarding the present study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the cooperative forestry science and technology project of Zhejiang Provincial Academy (2022SY14); the Breeding of New Varieties of Torreya grandis Program (2021C02066-11); the \u0026ldquo;Pioneer\u0026rdquo; and \u0026ldquo;Leading Goose\u0026rdquo; R\u0026amp;D Program of Zhejiang(2022C02061); The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.Y.was responsible for the Conceptualization; Q.X.was responsible for the methodology; C.Y. was responsible for software; Q.X., Z.J.and Q.W.were responsible for the validation;Q.X.was responsible for the formal analysis; Z.J.was responsible for the investigation;Q.W. was responsible for the data curation;Q.X.was responsible for the writing\u0026mdash;original draft preparation, Z.J.was responsible for the writing\u0026mdash;review and editing, C.Y.was responsible for the visualization;W.D.was responsible for the supervision;J.W.was responsible for the project administration;W.Y.was responsible for the funding acquisition. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are grateful to ANOROAD and APT Biotech company for transcriptomic and Metabolomic analysis，respectively.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eSequence data that support the findings of this study have been deposited in the NCBI database (BioProject ID PRJNA1126763).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHan M, Xu M, Su T, Wang S, Wu L, Feng J, Ding C. Transcriptome Analysis Reveals Critical Genes and Pathways in Carbon Metabolism and Ribosome Biogenesis in Poplar Fertilized with Glutamine. Int J Mol Sci.2022; 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan B, Shen S, Yang F, Wang X, Gao W, Zhang K. 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J Hazard Mater. 2022;436:129181.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKiselev KV, Aleynova OA, Ogneva ZV, Suprun AR, Ananev AA, Nityagovsky NN, Dneprovskaya AA, Beresh AA, Dubrovina AS. The Effect of Stress Hormones, Ultraviolet C, and Stilbene Precursors on Expression of Calcineurin B-like Protein (CBL) and CBL-Interacting Protein Kinase (CIPK) Genes in Cell Cultures and Leaves of Vitis amurensis Rupr. Plants (Basel). 2023; 12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu R, Gao N, Luo J, Shi W, Basel.). 2024;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu Y, Suo J, Jiang G, Shen J, Cheng H, Lou H, Yu W, Wu J, Song L. The effect of ethylene on squalene and β-sitosterol biosynthesis and its key gene network analysis in Torreya grandis nuts during post-ripening process. Food Chem. 2022;368:130819.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVue B, Zhang S, Chen QH. 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Lignin biosynthesis: old roads revisited and new roads explored. Open Biol. 2019;9:190215.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Z, Ma Y, Yang R, Gu Z, Wang P. Effects of exogenous Ca(\u003csup\u003e2+\u003c/sup\u003e) on phenolic accumulation and physiological changes in germinated wheat (Triticum aestivum L.) under UV-B radiation. Food Chem. 2019;288:368\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian X, He X, Xu J, Yang Z, Fang W, Yin Y. Mechanism of calcium in melatonin enhancement of functional substance-phenolic acid in germinated hulless barley. RSC Adv. 2022;12:29214\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiridhar M, Meier B, Imani J, Kogel KH, Peiter E, Vothknecht UC, Chigri F. Comparative analysis of stress-induced calcium signals in the crop species barley and the model plant Arabidopsis thaliana. BMC Plant Biol. 2022;22:447.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdditional. material.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Phenolic acids, calcium sugar alcohol, transcriptome sequencing, untargeted metabolome, transcription regulation","lastPublishedDoi":"10.21203/rs.3.rs-4608684/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4608684/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground：\u003c/strong\u003e\u003cem\u003eTorreya grandis\u003c/em\u003e, a prominent tree species of the autochthonous subtropical region of China, possesses a drupe-like fruit containing a nut that is rich in nutrients and bioactive compounds. However, the effect of calcium (Ca\u003csup\u003e2+\u003c/sup\u003e) sugar alcohol (CSA), a newly developed chelated Ca\u003csup\u003e2+\u003c/sup\u003e-fertilizer, on the secondary metabolism of phenolics in \u003cem\u003eT. grandis\u003c/em\u003e nuts is largely unknown, for which transcriptomic and metabolomic analysis was carried out.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eTranscriptome sequencing detected 47,064 transcripts, and several phenolic acid biosynthesis pathway-related genes were identified. Correlation analysis showed that the four transcription factors, WRKY12, AP2-1, AP2-3, and AP2-4, were positively associated with the accumulation of phenolic acids. Furthermore, the binding of AP2-1 to the \u003cem\u003eHCT\u003c/em\u003e promoter was confirmed using yeast one hybrid and dual-luciferase assays. Furthermore, the expression of \u003cem\u003eHCT\u003c/em\u003e in Nicotiana enhanced the total flavonoid content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOur results indicated that a new regulatory module, Ca\u003csup\u003e2+\u003c/sup\u003e–AP2–HCT, involved in the regulation of phenolic acid biosynthesis was revealed, expanding the understanding of the role of Ca\u003csup\u003e2+\u003c/sup\u003e fertilizers in plant secondary metabolism.\u003c/p\u003e","manuscriptTitle":"Integrated metabolomics and transcriptomics reveal the role of calcium sugar alcohol in the regulation of phenolic acid biosynthesis in Torreya grandis nuts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-05 09:51:18","doi":"10.21203/rs.3.rs-4608684/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-26T23:33:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-25T11:54:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203823494001381858483297175781358626130","date":"2024-12-19T06:38:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137323299115600036495355040780920620598","date":"2024-08-02T07:42:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-02T04:27:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51979442632855930474278352592123738843","date":"2024-07-16T01:39:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-11T10:16:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-10T18:44:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-10T18:42:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-10T18:41:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2024-06-20T02:47:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"730ce2ae-1151-4ef4-9625-715e95340afe","owner":[],"postedDate":"August 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-27T16:07:39+00:00","versionOfRecord":{"articleIdentity":"rs-4608684","link":"https://doi.org/10.1186/s12870-025-06113-9","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2025-01-23 15:58:16","publishedOnDateReadable":"January 23rd, 2025"},"versionCreatedAt":"2024-08-05 09:51:18","video":"","vorDoi":"10.1186/s12870-025-06113-9","vorDoiUrl":"https://doi.org/10.1186/s12870-025-06113-9","workflowStages":[]},"version":"v1","identity":"rs-4608684","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4608684","identity":"rs-4608684","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}