{"paper_id":"23768687-8001-4f01-8fcd-04ef9e2dcb11","body_text":"Integrated Morphological, Transcriptomic, and Metabolomic Profiling Reveals Differential Development Mechanisms in Two Weeping Forsythia Genotypes during Tissue Culture | 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 Morphological, Transcriptomic, and Metabolomic Profiling Reveals Differential Development Mechanisms in Two Weeping Forsythia Genotypes during Tissue Culture Yanxia He, Yanping Zheng, Jiaqi Geng, Xu Lu, Xiaoxiao Wang, Xin Sun, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6833324/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Weeping forsythia ( Forsythia suspensa ) is an important medicinal and ornamental plant. To explore genotype-dependent growth variation under tissue culture, we compared two long-style genotypes, FLS-1 and FLS-2. FLS-1 exhibited reduced plant height, branching, internode length, and chlorophyll content, along with chlorosis and impaired chloroplast ultrastructure. Transcriptomic analysis identified 2,059 and 3,482 DEGs between FLS-1 and FLS-2 on days 25 and 35, respectively, with 46 DEGs related to photosynthesis. Metabolomic profiling revealed 563 DEMs, with 15 KEGG pathways significantly enriched. These results elucidate key molecular differences affecting growth and photosynthesis between F. suspensa genotypes in vitro. Weeping forsythia Tissue culture Metabolomics Transcriptome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Key Message Elucidating the molecular mechanisms underlying growth differences between Forsythia genotypes in tissue culture. 1. Introduction Weeping forsythia ( Forsythia suspensa (Thunb.) Vahl), a deciduous shrub belonging to the Oleaceae family, is renowned for its medicinal and ornamental value. The fruit of this species, commonly referred to as \"Forsythiae Fructus\" in Traditional C hinese Medicine (TCM), is extensively used for the treatment of various conditions, including gonorrhea, erysipelas, inflammation, pyrexia, and ulcers (Zhou et al. 2022 ; Liu et al. 2022 ). F. suspensa is naturally distributed across regions in China, such as Henan, Shanxi, Shaanxi, and Hebei (Gao et al. 2024 ). Its branches are characterized by their graceful, arching form, and the plant produces vibrant yellow flowers that bloom in early spring. These attributes make it a popular choice for urban greening and beautification initiatives (Li et al. 2021 ). Given its medicinal, ornamental, and economic significance, F. suspensa has garnered increasing attention in recent years. However, the growing market demand and diminishing natural resources have underscored the importance of cultivation, presenting substantial opportunities for its development in rural areas (Li et al. 2024 ). Micropropagation, a tissue culture technique, enables the production of millions of clonal individuals through the induction of morphogenesis from various plant tissues or organs. This approach is widely utilized for the large-scale propagation of medicinal and ornamental plant species, as well as for the conservation of valuable genetic resources, including Dendrobium (Teixeira et al. 2015), Saussurea involucrata (Kuo et al. 2015 ), and Cannabis sativa (Adhikary et al. 2021 ). Consequently, plant tissue culture serves as a highly effective platform for the large-scale cultivation and production of superior forsythia germplasm. It ensures a consistent and sustainable supply of raw materials for TCM without exerting pressure on natural habitats (Niazian 2019 ; Zhang et al. 2023 ). In the case of weeping forsythia, a comprehensive and efficient in vitro rapid propagation system has been successfully developed using tissue culture technology (Yuan et al. 2023 ). Notably, significant variations in growth and development have been observed among different weeping forsythia genotypes under optimal culture conditions, highlighting the influence of genetic diversity on in vitro propagation outcomes. In this study, an optimized tissue culture system was established for two distinct genotypes (FLS-1 and FLS-2) of weeping forsythia under laboratory conditions. Key growth indices, ultrastructural characteristics, and the chlorophyll a and chlorophyll b contents of subcultured seedlings were systematically evaluated. Comparative transcriptomic and metabolomic analyses were conducted to identify differentially expressed genes (DEGs) and differentially expressed metabolites (DEMs) between the two genotypes of FLS-1 and FLS-2. These findings provide valuable insights into the photosynthetic difference and underlying mechanisms driving growth differences among genotypes of weeping forsythia during tissue culture. 2. Materials and methods 2.1 Plant materials and samples Two elite weeping forsythia genotypes, FLS-1 and FLS-2, were used as experimental materials. The plants were cultivated in the field at Da Mei Lian Qiao Company, Sanmenxia, Henan Province, China. Tissue culture experiments were conducted in the laboratory of the School of Life Sciences, Henan University. Healthy stem segments of FLS-1 and FLS-2 were selected as explants and inoculated onto an optimized and sterilized Murashige and Skoog (MS) medium supplemented with 3.0 mg·L⁻¹ 6-benzylaminopurine (6-BA), 1.0 mg·L⁻¹ indole-3-butyric acid (IBA), 30 g·L⁻¹ sucrose, and 7 g·L⁻¹ agar, adjusted to pH 6.0 prior to sterilization. The cultures were maintained under optimal conditions: a temperature of 25°C, a light intensity of 2,000–2,500 lx, and a photoperiod of 12 hours light and 12 hours darkness. Subsequently, the seedlings were subcultured under the same conditions. 2.2 Determination of growth index and chlorophyll content during the tissue culture of F. suspensa Plant heights of FLS-1 and FLS-2 were measured every 5 days over 1-month period, beginning on the 10th day of subculture, with each measurement performed in triplicate. Fresh leaves were collected on the 25th and 35th day for chlorophyll determination. Chlorophyll was extracted using 80% acetone for 24 hours in darkness, and its content was quantified using a spectrophotometer following the method described as Mircea (Mircea et al. 2023 ). 2.3 Anatomical Structure Observation The transmission electron microscopy (TEM) protocol was adapted from the method of Zhou et al. with minor modifications (Zhou et al. 2023 ). The middle region of the third leaf from 35-day-old subcultured seedlings was harvested for analysis. Leaf samples were immediately fixed in a solution containing 5% glutaraldehyde and 4% paraformaldehyde, buffered with 0.1 M sodium phosphate (pH 7.2). Following rinsing in the same buffer, the samples were post-fixed in 1% osmium tetroxide, also in 0.1 M sodium phosphate (pH 7.2), for 3 hours at 4°C. The specimens were subsequently dehydrated through a graded ethanol series, transferred to acetone, and infiltrated with Epon812 epoxy resin for embedding. Ultra-thin sections were then prepared using a Leica EM UC7 ultramicrotome and stained with uranyl acetate and lead citrate. The prepared sections were examined using a FEI Talos F200C transmission electron microscope (Thermo Fisher Scientific, USA) for ultrastructural analysis. 2.4 RNA extraction, library construction and sequencing The whole tissue culture seedlings of FLS-1 and FLS-2 were harvested on the 25th day and 35th day at noon, immediately flash-frozen in liquid nitrogen, and stored at -80°C for subsequent transcriptome sequencing analysis. Each group consisted of three biological replicates.Total RNA was extracted from tissue samples using TRIzol® Reagent according to the manufacturer’s instructions. RNA quality was assessed using the 5,300 Bioanalyzer (Agilent) and quantified with the ND-2000 spectrophotometer (NanoDrop Technologies). Only high-quality RNA samples, meeting the criteria of OD260/280 = 1.8–2.2, OD260/230 ≥ 2.0, and a RNA Integrity Number (RIN) ≥ 6.5, were used for library construction. RNA purification, library construction, and sequencing were performed by Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd. (Shanghai, China). Raw sequencing data were processed for quality control and trimming using the fastp tool ( https://github.com/OpenGene/fastp ) (Chen et al. 2018 ), employing default parameters. Clean reads were then aligned to the reference genome in orientation mode using HISAT2 ( http://ccb.jhu.edu/software/hisat2/index.shtml ) (Kim et al. 2015 ;Li et al. 2023 ). The mapped reads for each sample were subsequently assembled as per the method outlined by Pertea et al (Pertea et al. 2015 ). 2.5 Differential expression analysis and functional enrichment To identify DEGs between the two samples, transcript expression levels were quantified using the Fragments Per Kilobase of exon model per Million mapped fragments (FPKM) method. Gene abundances were calculated using RSEM ( http://deweylab.github.io/RSEM/ ) (Li et al. 2011). Differential expression analysis was conducted with DESeq2 ( http://bioconductor.org/packages/stats/bioc/DESeq2 ) (Love et al. 2014 ). Genes with an absolute log₂ fold change (|log₂FC|) ≥ 2 and a false discovery rate (FDR) < 0.05 were considered significantly differentially expressed. Gene Ontology (GO) (Ashburner et al. 2000 ) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa and Goto 2000 ) enrichment analyses were performed to elucidate the functional roles and biological pathways associated with the DEGs. 2.6 qRTPCR validation Primers for the 10 selected DEGs were designed using Primer 5.0 software (Lalitha 2000 ). Quantitative Real-time polymerase chain reaction (qRT-PCR) was performed using a LightCycler® 480 Real-Time PCR System (Roche, Switzerland) with the Hieff qPCR SYBR Green Master Mix (Yisheng, Shanghai, China). The elongation factor-1α (EF-1α) gene served as an internal reference for normalization. Gene-specific primer sequences are provided in Table S1. Relative gene expression levels were calculated using the method as Qi et al (Qi et al. 2019 ). Each experiment included three biological replicates and three technical replicates to ensure accuracy and reproducibility. 2.7 Metabolomics analyses Samples of FLS-1 and FLS-2 were collected on the 35th day at noon of subculture for metabolomic analysis, with each group consisting of three biological replicates. The samples, along with grinding beads, were placed into centrifuge tubes for metabolite extraction. LC-MS/MS analysis was performed by Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) following standard protocols (Lu et al. 2008 ). Data analysis was conducted using the Majorbio Cloud Platform ( https://cloud.majorbio.com ) following database retrieval. Principal Component Analysis (PCA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed on the pre-processed data matrix using the ropls package (version 1.6.2) in R language. The model's stability and reliability were assessed through seven cycles of interactive cross-validation. Differential metabolites between the two groups were mapped to biochemical pathways using metabolic enrichment and pathway analysis based on the KEGG database ( http://www.genome.jp/kegg/ ) (Kanehisa et al. 2000). These metabolites were further classified according to their involvement in specific pathways or their functional roles. 3. Results 3.1 Growth of FLS-1 is significantly slower than FLS-2 during tissue culture The proliferation and growth of weeping forsythia seedlings became noticeable after the 10th day of subculture. Compared to FLS-2, the growth of FLS-1 was significantly slower, as evidenced by a reduced average plant height and the appearance of chlorosis, characterized by distinctly lighter green leaves (Fig. 1 ). Furthermore, FLS-1 exhibited significantly fewer total nodes, branches, and a shorter average internode length compared to FLS-2 (Table 1 ). These findings indicate that the period from the 25th to the 35th day represents a phase of rapid growth in weeping forsythia under tissue culture conditions. Table 1 Phenotypic data of FLS-1 and FLS-2 subcultured seedlings during growth Single Plant Height (mm) Total Number of Branches(pcs) Number of Branches (pcs) Average Internode Length(mm) FLS-1 FLS-2 FLS-1 FLS-2 FLS-1 FLS-2 FLS-1 FLS-2 10d 4.37 ± 0.25e 6.18 ± 0.28F 1.42 ± 0.12e 2.25 ± 0.11F 1.29 ± 0.09b 1.83 ± 0.08C 1.31 ± 0.13a 1.72 ± 0.09D 15d 4.87 ± 0.26e 8.96 ± 0.44F 1.54 ± 0.13e 3.08 ± 0.22E 1.38 ± 0.12ab 2.00 ± 0.10BC 1.34 ± 0.10a 1.76 ± 0.22D 20d 6.35 ± 0.4de 15.76 ± 0.64E 1.88 ± 0.19de 3.92 ± 0.19D 1.38 ± 0.12ab 2.00 ± 0.00BC 1.44 ± 0.10a 2.17 ± 0.16CD 25d 7.99 ± 0.59cd 20.05 ± 0.94D 2.54 ± 0.25cd 4.58 ± 0.23C 1.58 ± 0.12ab 2.04 ± 0.04BC 1.46 ± 0.16a 2.55 ± 0.19C 30d 9.18 ± 0.78bc 28.58 ± 1.37C 3.17 ± 0.27bc 5.96 ± 0.19B 1.63 ± 0.12ab 2.08 ± 0.06B 1.47 ± 0.17a 3.23 ± 0.23B 35d 10.66 ± 0.93b 40.1 ± 2.1B 3.63 ± 0.22ab 6.58 ± 0.22B 1.67 ± 0.12ab 2.08 ± 0.06B 1.50 ± 0.13a 4.89 ± 0.30A 40d 13.98 ± 1.24a 50.41 ± 2.54A 4.21 ± 0.39a 7.25 ± 0.35A 1.71 ± 0.14a 2.29 ± 0.09A 1.65 ± 0.18a 4.99 ± 0.31A Note: Different lowercase letters and uppercase letters within the same column indicate the significant differences between FLS-1 and FLS-2 in different time points, respectively ( p < 0.05). 3.2 Significant difference in chlorophyll content between the two genotypes In this study, the chlorophyll a content of FLS-1 was 0.51 mg∙g − 1 on the 25th day, whereas FLS-2 exhibited a content of 1.41 mg∙g − 1 . On the 35th day, the chlorophyll a content was 0.60 mg∙g − 1 in FLS-1 and 1.10 mg∙g − 1 in FLS-2. For chlorophyll b, the content was 0.161 mg∙g − 1 in FLS-1 and 0.409 mg∙g − 1 in FLS-2 on the 25th day, and 0.190 mg∙g − 1 in FLS-1 and 0.363 mg∙g − 1 in FLS-2 on the 35th day. Statistical analysis using a T-test demonstrated significant differences in both chlorophyll a and chlorophyll b contents between FLS-1 and FLS-2 (Fig. 2 ). 3.3 Difference of leaf ultrastructure between two genotypes At low magnification, the chloroplasts in mesophyll cells of FLS-1 and FLS-2 were in rings close to the cell wall. However, the palisade tissue cells of FLS-2 were small and neatly arranged, while that of FLS-1 were relatively large and loosely (Fig. 3 a,b,e). The chloroplast morphology of FLS-2 was smooth, the bilayer membrane structure was complete and clear, and the structure of the inner capsule was clearly visible (Fig. 3 d). Generally, 2–3 starch granules can be seen in a single chloroplast (Fig. 3 c). While the morphological edge of FLS-1 was fuzzy, the boundary of the bilayer membrane was unclear, and the texture of the inner capsule overlaps could not be identified. The number of starch granules in a single chloroplast was visibly reduced (Fig. 3 g,h). 3.4 Transcriptome analysis A total of 12 forsythia tissue culture seedling samples were sequenced using the Illumina NovaSeq 6,000 platform. After filtering out low-quality sequences, a total of 96.96 Gb of clean data were obtained. The effective data amount for each sample exceeded 6.04 Gb, with the average Q30 value of each sample being above 95.32%. The guanine-cytosine (GC) content ranged from 43.91–44.49%. Additionally, the overall alignment rate for the 12 samples ranged from 91.45–92.00%, with the unique mapping alignment rate ranging from 88.3–89.12% (Table 2 ). Table 2 Quality control assessment of sequencing data Sample Clean reads Q30(%) GC content(%) Total mapped Uniquely mapped 25_FLS-1_1 55721004 95.54 44.08 51000271(91.53%) 49280832(88.44%) 25_FLS-1_2 59287946 95.63 44.24 54419881(91.79%) 52696039(88.88%) 25_FLS-1_3 59848444 95.68 44.05 54805232(91.57%) 53037157(88.62%) 25_FLS-2_1 57892392 95.58 44.26 52941403(91.45%) 51218413(88.47%) 25_FLS-2_2 40396634 95.32 44.27 36941403(91.45%) 35820138(88.67%) 25_FLS-2_3 59809034 95.66 44.21 54698240(91.45%) 52866257(88.39%) 35_FLS-1_1 62139654 95.59 44.06 56916878(91.6%) 54869701(88.3%) 35_FLS-1_2 63134870 95.72 44.00 57909494(91.72%) 55986672(88.68%) 35_FLS-1_3 54772656 95.66 43.91 50173731(91.6%) 48418411(88.4%) 35_FLS-2_1 48363582 95.61 44.13 44284768(91.57%) 42836722(88.57%) 35_FLS-2_2 49923374 95.51 44.21 45713008(91.57%) 44302334(88.74%) 35_FLS-2_3 47782580 95.57 44.49 43958249(92.0%) 42583282(89.12%) Note: Sample: The name of the sample; Clean reads: The total number of items in the sequencing data after quality control; Q30 (%): Quality assessment of sequencing data after quality control, Q30 refer to the percentage of bases with sequencing quality above 99.9% in the total base; GC content (%): The percentage of the total sum of G and C bases corresponding to the quality control data in the total bases. A total of 33,062 unigenes were annotated, and correlation analysis as well as PCA were performed for all samples. The PCA results showed that the expression patterns of FLS-1 and FLS-2 were distinctly separated, classifying them as independent groups (Fig. 4 ). Compared to FLS-2, a total of 2,059 DEGs were identified in FLS-1 on the 25th day, of which 1,078 were up-regulated and 981 down-regulated. On the 35th day, 3,482 DEGs were identified, with 2,059 up-regulated and 1,423 down-regulated (Fig. 5 ). On the 25th day, up-regulated genes were primarily enriched in oxidoreductase activity, binding, secondary metabolic processes, and phenylpropanoid metabolism, while down-regulated genes were mainly associated with photosynthesis and chlorophyll binding. On the 35th day, up-regulated genes were enriched in defense responses to external stimuli and oxidoreductase activity processes, while the down-regulated genes were again enriched in photosynthesis and chlorophyll binding, consistent with findings from the 25th day (Table S2). On the 25th and 35th day, the DEGs of FLS-1 were mapped to 111 and 122 KEGG pathways, respectively, with 9 and 12 pathways significantly enriched. Notably, \"photosynthesis\" and \"photosynthesis-antenna proteins\" were among the significantly enriched pathways (Table 3 ). Based on GO and KEGG enrichment analyses, and considering the observed absence of chlorophyll in the FLS-1 samples, we focused on DEGs associated with the photosynthetic pathway. A total of 46 DEGs were identified, including 10 genes involved in photosystem I (PSI), 10 in photosystem II (PSII), 5 in F-type ATPase, 4 in the light-harvesting chlorophyll protein complex I (LHCI), and 13 in the light-harvesting chlorophyll protein complex II (LHCII). Notably, all of these genes showed down-regulated expression patterns, further indicating significant disruption of photosynthetic processes in FLS-1. Table 3 KEGG pathway enrichment analysis of differentially expressed genes in FLS-1_vs_FLS-2 on the 25th and 35th day Pathway ID Description Num Pvalue Qvalue 25d map00196 Photosynthesis-antenna proteins 10 1.00E-07 1.11E-05 map00052 Galactose metabolism 14 2.47E-04 9.14E-03 map00940 Phenylpropanoid biosynthesis 23 1.97E-04 1.09E-02 map00945 Stilbenoid, diarylheptanoid and gingerol biosynthesis 10 4.51E-04 1.25E-02 map00592 alpha-Linolenic acid metabolism 11 1.86E-03 2.96E-02 map04626 Plant-pathogen interaction 36 1.62E-03 2.99E-02 map00073 Cutin, suberine and wax biosynthesis 7 2.40E-03 3.33E-02 map00520 Amino sugar and nucleotide sugar metabolism 20 1.54E-03 3.41E-02 map00941 Flavonoid biosynthesis 9 2.84E-03 3.50E-02 35d map00196 Photosynthesis-antenna proteins 17 6.31E-14 7.70E-12 map00940 Phenylpropanoid biosynthesis 38 2.18E-06 1.33E-04 map04626 Plant-pathogen interaction 61 3.75E-05 1.52E-03 map00195 Photosynthesis 32 3.37E-04 5.87E-03 map00945 Stilbenoid, diarylheptanoid and gingerol biosynthesis 14 2.03E-04 6.20E-03 map00908 Zeatin biosynthesis 12 2.98E-04 7.28E-03 map00904 Diterpenoid biosynthesis 12 2.98E-04 7.28E-03 map00909 Sesquiterpenoid and triterpenoid biosynthesis 19 5.87E-04 8.95E-03 map00630 Glyoxylate and dicarboxylate metabolism 19 1.74E-03 2.36E-02 map00592 alpha-Linolenic acid metabolism 15 2.39E-03 2.91E-02 map04075 Plant hormone signal transduction 54 3.02E-03 3.35E-02 map00910 Nitrogen metabolism 11 3.85E-03 3.91E-02 Note: Pathway id: The pathway identifier; Description: The name of the pathway; Num: The number of genes or transcripts enriched in this pathway; Pvalue: Uncorrected P-value, with smaller values indicating higher statistical significance; Qvalue: Adjusted p-value after correction. 3.5 Metabolome profiles between FLS-1and FLS-2 To examine the differences in metabolites between tissue culture seedlings of two genotypes, metabolomics analysis was conducted using LC-MS. PCA was employed to analyze the metabolomic profiles and provide insights into distinct clustering patterns between the groups (Fig. 6 ). A total of 1,643 metabolites were identified, of which 1,595 had defined chemical formulas. The major classes of metabolites identified included terpenoids (16.18%), lipids (13.86%), carbohydrates and derivatives (9.53%), amino acids and derivatives (8.28%), and flavonoids (7.21%) (Fig. 7 ). DEMs were identified using both univariate and multivariate analyses. In comparison to the FLS-2 genotype, 358 metabolites were upregulated and 205 were downregulated in FLS-1 samples. The 563 DEMs were mapped to 77 KEGG pathways, with 15 pathways showing significant enrichment. These included pathways such as arginine biosynthesis, β-alanine metabolism, flavonoid biosynthesis, diterpene biosynthesis, flavonoid and flavonol biosynthesis, and phenylpropanoid biosynthesis (Table 4 ). Table 4 Significantly enriched pathways of differential metabolites Pathway ID Pathway Description Num Pvalue Qvalue map00590 Arachidonic acid metabolism 17 1.62E-10 1.25E-08 map00940 Phenylpropanoid biosynthesis 8 5.56E-04 2.14E-02 map00591 Linoleic acid metabolism 5 1.95E-03 5.01E-02 map01232 Nucleotide metabolism 7 2.73E-03 5.25E-02 map00380 Tryptophan metabolism 8 5.69E-03 8.77E-02 map00944 Flavone and flavonol biosynthesis 6 6.20E-03 7.95E-02 map00904 Diterpenoid biosynthesis 11 7.43E-03 8.17E-02 map00941 Flavonoid biosynthesis 7 1.05E-02 1.01E-01 map00460 Cyanoamino acid metabolism 5 1.55E-02 1.32E-01 map00770 Pantothenate and CoA biosynthesis 4 1.60E-02 1.23E-01 map00240 Pyrimidine metabolism 6 1.82E-02 1.27E-01 map00410 beta-Alanine metabolism 4 2.00E-02 1.28E-01 map00999 Biosynthesis of various plant secondary metabolites 9 2.71E-02 1.60E-01 map02010 ABC transporters 9 3.77E-02 2.08E-01 map00220 Arginine biosynthesis 3 3.85E-02 1.97E-01 map00470 D-Amino acid metabolism 6 6.55E-02 3.15E-01 map00780 Biotin metabolism 3 6.88E-02 3.12E-01 map00360 Phenylalanine metabolism 4 7.69E-02 3.29E-01 map00960 Tropane, piperidine and pyridine alkaloid biosynthesis 6 8.79E-02 3.56E-01 map00400 Phenylalanine, tyrosine and tryptophan biosynthesis 3 1.00E-01 3.86E-01 Note: Pathway id: The pathway identifier; Description: The name of the pathway; Num: The number of genes or transcripts enriched in this pathway; Pvalue: Uncorrected P-value, with smaller values indicating higher statistical significance; Qvalue: Adjusted p-value after correction.. 3.6 Analysis of DEGs and DEMs in chlorophyll synthesis and plant hormone synthesis Pathway Chlorophyll is a key pigment involved in the process of photosynthesis. KEGG pathway analysis identified a significant enrichment of 10 DEGs associated with chlorophyll synthesis. Further examination revealed that the expression of these genes was markedly downregulated at both the 25th and 35th days. Notably, the enzymes encoded by these downregulated genes encompass nearly the entire biosynthetic pathway of chlorophyll, including glutamyl-tRNA reductase (HemA), 5-aminolevulinic acid dehydratase (HemB), magnesium chelatase subunit H (chlH), magnesium protoporphyrin IX monomethyl ester (oxidative) cyclase (chlE), and protochlorophyllide reductase (por) (Fig. 8 ). In this study, 13 DEGs involved in the gibberellin biosynthesis pathway were identified. These included 4 copalyl diphosphate synthase (CPS) genes, 1 ent-kaurene synthase (KS) gene, 1 kaurene oxidase (KO) gene, 2 ent-kaurenoic acid oxidase (KAO) genes, 1 GA20-oxidase (GA20ox) gene, 2 GA2-oxidase (GA2ox) genes, and 2 GA3-oxidase (GA3ox) genes. Expression analysis revealed that KS and KO genes were highly expressed on the 25th and 35th day, whereas CPS and GA20ox exhibited lower expression levels. Additionally, five DEMs involved in gibberellin biosynthesis were detected, including GA12-aldehyde, GA12, GA53, GA24, and GA7. Of these, the first four metabolites were upregulated, while GA7 was downregulated (Fig. 9 a). Further analysis identified 3 DEGs encoding S-adenosylmethionine synthetase (SAMS), 1 DEG encoding 1-aminocyclopropane-1-carboxylic acid synthase (ACS), and 1 DEG encoding 1-aminocyclopropane-1-carboxylic acid oxidase (ACO), all involved in ethylene biosynthesis. SAMS gene expression was significantly downregulated on both the 25th and 35th days, while ACS and ACO showed upregulation. In ethylene signal transduction, 17 DEGs were identified, including Constitutive Triple Response 1 (CTR1), EIN3-binding F-box 1/2 (EBF1/2), and Ethylene Response Factor 1 (ERF1), all of which were upregulated (Fig. 9 b). Three DEGs related to auxin biosynthesis were also identified, including 2 tryptophan decarboxylase (TDC) genes and 1 aldehyde dehydrogenase (ALDH) gene, with ALDH showing high expression at both time points. Furthermore, a total of 32 DEGs involved in auxin signal transduction were detected, consisting of 10 AUX/IAA genes, 3 Gretchen Hagen3 (GH3) genes, and 19 small auxin upregulated RNA (SAUR) genes. Notably, AUX/IAA and SAUR families were downregulated, while GH3 was upregulated (Fig. 9 c). Regarding cytokinin synthesis, 1 DEG encoding isopentenyl transferase (IPT) was downregulated, while 4 DEGs involved in cytokinin signal transduction were identified, including 2 cytokinin response 1 (CRE1) genes, 1 B-type Arabidopsis response regulator (B-ARR), and 1 A-type Arabidopsis response regulator (A-ARR). CRE1 was highly expressed, B-ARR was significantly downregulated, and A-ARR showed downregulation on day 25 and upregulation on day 35 (Fig. 9 d). Finally, 4 DEGs related to abscisic acid (ABA) biosynthesis were identified, including 1 lutein deficient 5 (LUT5) gene and 3 9-cis-epoxycarotenoid dioxygenase (NCED) genes, most of which showed low expression. In ABA signal transduction, 6 DEGs were identified, including 1 pyrabactin resistance 1-like (PYL) gene and 5 protein phosphatase 2C (PP2C) genes, with PYL highly expressed and PP2C genes showing downregulation on day 25 and upregulation on day 35. Additionally, the expression of abscisic aldehyde (a DEM) was downregulated (Fig. 9 e). This comprehensive analysis highlights the intricate regulation of hormonal pathways, particularly gibberellin, ethylene, auxin, cytokinin, and ABA, in the development and signaling processes of tissue culture seedlings. 3.7 qRT-PCR validation To validate the reliability of the transcriptome data, 10 DEGs, comprising 6 downregulated and 4 upregulated genes, were randomly selected from significantly enriched pathways for qRT-PCR analysis. The qRT-PCR results confirmed that the expression patterns of these genes were consistent with the RNA-Seq data, demonstrating the high reliability of the sequencing results for subsequent analyses (Fig. S1). 4 Discussion Weeping forsythia is a widely distributed plant in China, valued for its ornamental, ecological, and medicinal properties (Li et al. 2023 ). To meet market demand and improve the quality of medicinal materials, artificial cultivation of forsythia has increased significantly in recent years (Yuan et al. 2023 ). Plant tissue culture technology has been employed to quickly generate superior varieties. Therefore, it is important to analyze the mechanism of causing the slow growth and development of some genotype (such as FLS-1) plants during tissue culture for weeping forsythia breeding. Plant height is an important trait of plant phenotype, reflecting a certain stage of growth and development (Cheng et al. 2019 ). Studies have shown that plant dwarfing, lower ear height, and hindered growth and development are closely related to the decline of biological yield and economic yield (Hua 2009 ). In this study, compared to FLS-2, the seedlings of the FLS-1 genotype exhibited slower growth, pronounced leaf chlorosis, and a significant reduction in chlorophyll content. The chloroplast abnormalities of FLS-1 can be seen in the microstructure, such as blurred boundary of bilayer membrane, reduced internal starch granules, and unclear internal capsule stacking texture. These structural variations can seriously affect the light reaction in photosynthesis, resulting in lower photosynthetic efficiency of plants (Zhu et al. 2021 ; Kulkov et al. 2024 ; Wu et al. 2007 ). Chlorophyll is an important natural green pigment responsible for the absorption of light energy and conversion into chemical energy via photosynthesis in plants (da and Sant'Anna 2017). The complete biosynthetic pathway of chlorophyll, from glutamyl-tRNA to the production of chlorophyll a and chlorophyll b, involves approximately 20 distinct enzymatic steps. Protoporphyrin IX, a precursor to chlorophyll, is synthesized through several enzymatic steps (Nagata et al. 2005 ; Li et al. 2016 ). Mutations in the chlH gene have been shown to cause chlorophyll deficiency, resulting in a yellow or chlorotic phenotype in both Oryza sativa (Zhao et al. 2016 ) and Arabidopsis thaliana (Mochizuki et al. 2001 ). Kong et al (Kong et al. 2016 ) reported a novel rice mutant, YGL8, which displays a yellow-green leaf phenotype accompanied by abnormal chloroplast development. In the present study, transcriptome sequencing identified 10 DEGs associated with chlorophyll biosynthesis, all of which showed down-regulated expression patterns. These genes include 2 HemA, 1 HemB, 2 chlH, 2 chlE, and 3 por (porphyrin biosynthetic enzymes). Glutamyl-tRNA reductase, a key enzyme in this pathway, is downregulated in FLS-1 compared to FLS-2. This may lead to reduced synthesis of 5-aminolevulinic acid (ALA) and protoporphyrin IX, impairing chlorophyll production and resulting in leaf color variation in the study (Fig. 8 ). Hormonal homeostasis is pivotal in coordinating plant growth and development, with regulation occurring at multiple levels, including hormone biosynthesis, degradation, perception, and signal transduction (Zhang et al. 2023 ). Gibberellins (GAs), including GA1, GA3, GA4, and GA7, are diterpenoid hormones that regulate various aspects of plant growth and development, such as germination, stem elongation, flower formation, leaf senescence, and fruit ripening (Li et al. 2024 ; Lee et al. 2022 ; Wang et al. 2022 ). GAs are synthesized through complex pathways, with key enzymes like CPS, KS, KO, and KAO catalyzing the initial steps. Among the genes involved, GA20ox plays a critical role in regulating plant height (Elias et al. 2012 ). Inhibition of GA20ox reduces internode length and plant stature in apple trees, while its overexpression leads to increased height and branch diameter in pine trees (Park et al. 2015 ). Consistent with previous studies, our findings show that downregulation of GA20ox expression on day 25 and 35 resulted in reduced plant height and internode length in FLS-1. Metabolomics analysis revealed a decrease in GA7 levels. Attempts to promote FLS-1 growth by supplementing GA7 to MS medium, however, efforts to enhance FLS-1 growth by supplementing GA7 into MS medium yielded inconclusive results (Fig. 9 a). The biosynthesis of ethylene involves methionine conversion to S-adenosylmethionine (AdoMet) by SAMS, followed by its transformation to 1-aminocyclopropane-1-carboxylic acid (ACC) by ACS, and finally to ethylene by ACO (Van et al. 2014; Luo et al. 2018 ). ACS and ACO are critical enzymes in ethylene biosynthesis, maintaining balanced ethylene production during normal development (Khan et al. 2024 ). Overexpression of CiACS4 induces a dwarf phenotype and increased ethylene release, while its suppression enhances plant height in transgenic citrus, demonstrating its key role in growth regulation (Chu et al. 2023 ). This is further supported by our findings, where the high expression of ACS and ACO enhances ethylene biosynthesis, thereby influencing the growth of FLS-1 and resulting in a dwarf phenotype (Fig. 9 b). Auxin in plants can act directly on cell membranes and intracellular components to regulate essential processes such as cell division, elongation, and differentiation (Xing et al. 2024 ). The KEGG pathways enriched among the DEGs were auxin biosynthesis and signal transduction, suggesting that these two pathways are important to tissue culture seedling growth and development (Fig. 9 c). In this study, the increased expression of the ALDH gene may lead to elevated auxin levels, subsequently suppressing the growth of FLS-1. Auxin-responsive genes, including the Auxin/Indole-3-Acetic Acid (AUX/IAA) family, auxin response factor (ARF) family, SAUR and the auxin-responsive GH3 family, play critical roles in regulating plant growth (Luo et al. 2018 ). Among these, the SAUR family contains the highest number of members. Recent research has demonstrated that SAUR genes primarily regulate plant cell elongation and cell wall relaxation (Lv et al. 2022 ; Luan et al. 2023 ). The observed inhibition of FLS-1 tissue culture seedling growth in this study may be attributed to the downregulation of the SAUR homologous gene. The cytokinins (CKs) are known to regulate the biogenesis of chloroplasts, which are considered as one of the main groups of phytohormones as they, together with auxins, control cell division and, hence, influence the overall plant’s architecture. The first step of CK biosynthesis is catalysed by IPT (Hluska et al. 2021 ). ABA is a key phytohormone regulating diverse physiological processes and influencing plant growth and development by modulating the production of protective metabolites (Singh et al. 2023). Key ABA biosynthetic genes, including zeaxanthin epoxidase (ZEP), NCED and abscisic aldehyde oxidase (AAO3), have been identified, with NCED-catalyzed xanthoxin production recognized as the primary regulatory step in ABA biosynthesis (Ng et al. 2014 ). ABA receptors, mainly comprising the PYR/PYL/RCAR protein family, undergo conformational changes upon binding ABA, forming receptor complexes that relieve PP2C-mediated inhibition of SnRK2, thereby activating SnRK2 through phosphorylation and initiating downstream ABA-responsive gene expression (Varshney et al. 2021 ). In this study, changes in the expression levels of the ABA biosynthetic gene NCED, receptor gene PYL, and signaling negative regulator gene PP2C suggest their potential involvement in the growth of Forsythia suspensa tissue culture seedlings. Metabolomic analysis further identified an upregulation of abscisic aldehyde, an ABA precursor, indicating enhanced ABA biosynthesis (Fig. 9 e). Additionally, the downregulation of PP2C likely reduces its inhibitory effect on SnRK2, impairing SnRK2 phosphorylation and subsequently disrupting ABA signaling. Collectively, these findings suggest that altered ABA biosynthesis and signaling pathways may contribute to the growth inhibition observed in FLS-1 lines. Abbreviations AdoMet S-adenosylmethionine AAO3 Abscisic aldehyde oxidase A-ARR A-type arabidopsis response regulator ABA Abscisic acid ACC 1-aminocyclopropane-1-carboxylic acid ACO 1-aminocyclopropane-1-carboxylic acid oxidase ACS 1-aminocyclopropane-1-carboxylic acid synthase ALA 5-aminolevulinic acid ALDH Aldehyde dehydrogenase ARF Auxin response factor ARF Auxin response factor AUX/IAA Auxin/Indole-3-Acetic Acid B-ARR B-type arabidopsis response regulator CKs Cytokinins CPS Copalyl diphosphate synthase CRE1 Cytokinin response 1 CTR1 Constitutive Triple Response 1 DEGs Differentially expressed genes DEMs Differentially expressed metabolites EBF1/2 EIN3-binding F-box 1/2 EF-1α Elongation Factor-1α ERF1 Ethylene Response Factor 1 FDA False Discovery Rate FPKM Fragments Per Kilobase of exon model per Million mapped fragments FLS Forsythia suspensa withlong style GAs Gibberellins GC Guanine-Cytosine GH3 Gretchen Hagen3 GO Gene Ontology IBA Indole-3-butyric Acid IPT Isopentenyl transferase KAO Kaurenoic acid oxidase KEGG Kyoto Encyclopedia of Genes and Genomes KO Kaurene oxidase KS Kaurene synthase LHCI Light-harvesting chlorophyll protein complex I LHCII Light-harvesting chlorophyll protein complex II LUT5 Lutein deficient 5 NCED 9-cis-epoxycarotenoid dioxygenase OPLS-DA Orthogonal Partial Least Squares-Discriminant Analysis PCA Principal Component Analysis PP2C Protein phosphatase 2C PSI Photosystem I PSII Photosystem II PYL Pyrabactin resistance 1-like qRT-PCR Quantitative Real-time polymerase chain reaction RIN RNA Integrity Number SAMS S-adenosylmethionine Synthetase SAUR Small auxin upregulated RNA TCM Traditional Chinese Medicine TDC Tryptophan decarboxylase TEM Transmission Electron Microscopy ZEP Zeaxanthin epoxidase 6-BA 6-benzylaminopurine Declarations Funding This work was supported in part by grants from the Henan Science and Technology Research Project (252102110153) and the National Key Research and Development Program of China Project (2023YFD2201100). Competing interests The authors declare no competing interests. Authors' contributions YWJ, HYX. and WXP. conceived the research project.ZYP, GJQ, LX, WXX, SX and ZXQ. were involved in the analysis of the data. ZYP. drafted the paper and HYX. revised it critically for intellectual content. All authors have read and approved the final manuscript. All authors agree to be accountable for all aspects of the work. Ethical Approval and Consent to participate Not applicable. No human or animal subjects were involved in this research. Consent for publication All authors consent to the publication of this manuscript in its current form Availability of supporting data The sequence data that support the findings of this study are openly available in GenBank of NCBI at https://www.ncbi.nlm.nih.gov/, and the associated *SRA* numbers of the raw sequence data are from SRR27452189 to SRR27452200. References Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM et al (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25(1):25–29. https://doi.org/10.1038/75556 Adhikary D, Kulkarni M, El-Mezawy A, Mobini S, Elhiti M, Gjuric R et al (2021) Medical Cannabis and Industrial Hemp Tissue Culture: Present Status and Future Potential. Front Plant Sci 12:627240. https://doi.org/10.3389/fpls.2021.627240 Cheng Q, Dong LD, Su T, Li TY, Gan ZR, Nan HY et al (2019) )CRISPR/Cas9-mediated targeted mutagenesis of GmLHY genes alters plant height and internode length in soybean. BMC Plant Biol 19(1):562. https://doi.org/10.1186/s12870-019-2145-8 Chu LL, Yan Z, Sheng XX, Liu HQ, Wang QY, Zeng RF et al (2023) Citrus ACC synthase CiACS4 regulates plant height by inhibiting gibberellin biosynthesis. Plant Physiol 192(3):1947–1968. https://doi.org/10.1093/plphys/kiad159 Chen SF, Zhou YQ, Chen YR, Gu J (2018) fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34(17):i884–i890. https://doi.org/10.1093/bioinformatics/bty560 da Silva Ferreirada V, Sant'Anna C (2017) Impact of culture conditions on the chlorophyll content of microalgae for biotechnological applications. World J Microbiol Biotechnol 33(1):20. https://doi.org/10.1007/s11274-016-2181-6 Elias AA, Busov VB, Kosola KR, Ma C, Etherington E, Shevchenko O et al (2012) Green revolution trees: semidwarfism transgenes modify gibberellins, promote root growth, enhance morphological diversity, and reduce competitiveness in hybrid poplar. Plant Physiol 160(2):1130–1144. https://doi.org/10.1104/pp.112.200741 Gao BY, Zhu HS, Liu ZH, He XH, Sun JH, LI YF et al (2024) Chemical Compositions of Lianqiao (Forsythia suspensa) Extracts and Their Potential Health Benefits. Pharmaceuticals (Basel) 7(6):740. https://doi.org/10.3390/ph17060740 Hua Q (2009) Effect of water stress on maize yield during different growing stages (in Chinese). J Maize Sci 17(2):60–63. https://api.semanticscholar.org/CorpusID:111875327 Hluska T, Hlusková L, Emery RJN (2021) The Hulks and the Deadpools of the Cytokinin Universe: A Dual Strategy for Cytokinin Production, Translocation, and Signal Transduction. Biomolecules 11(2):209. https://doi.org/10.3390/biom11020209 Kulkov L, Arkhipov R, Abramova A, Vereshchagin M, Voronkov A, Khalilova V et al (2024) Long-term effects of silver nanoparticles and mineral nutrition components on the photosynthetic processes, chloroplast ultrastructure and productivity of Solanum lycopersicum plants. J Photochem Photobiol B 260:113038. https://doi.org/10.1016/j.jphotobiol.2024.113038 Kuo CL, Agrawal DC, Chang HC, Chiu YT, Huang CP, Chen YL et al (2015) In vitro culture and production of syringin and rutin in Saussurea involucrata (Kar. et Kir.) - an endangered medicinal plant. Bot Stud 56(1):12. https://doi.org/10.1186/s40529-015-0092-8 Khan S, Alvi AF, Saify S, Iqbal N, Khan NA (2024) The Ethylene Biosynthetic Enzymes, 1-Aminocyclopropane-1-Carboxylate (ACC) Synthase (ACS) and ACC Oxidase (ACO): The Less Explored Players in Abiotic Stress Tolerance. Biomolecules 14(1):90. https://doi.org/10.3390/biom14010090 Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28(1):27–30. https://doi.org/10.1093/nar/28.1.27 Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12(4):357–360. https://doi.org/10.1038/nmeth.3317 Kong WY, Yu XW, Chen HY, Liu LL, Xiao YJ, Wang YL et al (2016) The catalytic subunit of magnesium-protoporphyrin IX monomethyl ester cyclase forms a chloroplast complex to regulate chlorophyll biosynthesis in rice. Plant Mol Biol 92(1–2):177–191. https://doi.org/10.1007/s11103-016-0513-4 Lalitha S (2000) Primer Premier 5. Biotech Softw Internet Rep 1(6):270–272. https://doi.org/10.1089/152791600459894 Lu WY, Bennett BD, Rabinowitz JD (2008) Analytical strategies for LC-MS-based targeted metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci 871(2):236–242. https://doi.org/10.1016/j.jchromb.2008.04.031 Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. https://doi.org/10.1186/1471-2105-12-323 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. https://doi.org/10.1186/s13059-014-0550-8 Lv WZ, He X, Guo HJ, Lan HB, Jiao YQ, Li L et al (2022) Genome-Wide Identification of TaSAUR Gene Family Members in Hexaploid Wheat and Functional Characterization of TaSAUR66-5B in Improving Nitrogen Use Efficiency. Int J Mol Sci 23(14):7574. https://doi.org/10.3390/ijms23147574 Li Y, Shi LC, Pei NC, Cushman SA, Si YT (2021) Transcriptomic responses to drought stress among natural populations provide insights into local adaptation of weeping forsythia. BMC Plant Biol 21(1):273. https://doi.org/10.1186/s12870-021-03075-6 Liu LD, Sun Y, Wen CX, Jiang T, Tian W, Xie XL et al (2022) Metabolome analysis of genus forsythia related constituents in Forsythia suspensa leaves and fruits using UPLC-ESI-QQQ-MS/MS technique. PLoS ONE 17(6):e0269915. https://doi.org/10.1371/journal.pone.0269915 Li W, Tang S, Zhang S, Shan JG, Tang CJ, Chen QN et al (2016) Gene mapping and functional analysis of the novel leaf color gene SiYGL1 in foxtail millet [Setaria italica (L.) P. Beauv]. Physiol Plant 157(1):24–37. https://doi.org/10.1111/ppl.12405 Li Y, Wang F, Pei NC, Li Q, Liu HL, Yuan WJ et al (2023) The updated weeping forsythia genome reveals the genomic basis for the evolution and the forsythin and forsythoside A biosynthesis. Hortic Plant J 9(6):1149–1161. https://www.sciopen.com/article/ 10.1016/j.hpj.2022.09.004 Li QX, Xue XD (2024) Study on Synergistic Mechanism Between Forsythia Cultivation and Rural Development. J Life Sci Agric 1:68–72. https://doi.org/10.62517/jlsa.202407212 Luan J, Xin M, Qin ZW (2023) Genome-Wide Identification and Functional Analysis of the Roles of SAUR Gene Family Members in the Promotion of Cucumber Root Expansion. Int J Mol Sci 24(6):5940. https://doi.org/10.3390/ijms24065940 Lee BD, Yim Y, Cañibano E, Kim SH, García-León M, Rubio V et al (2022) CONSTITUTIVE PHOTOMORPHOGENIC 1 promotes seed germination by destabilizing RGA-LIKE 2 in Arabidopsis. Plant Physiol 189(3):1662–1676. https://doi.org/10.1093/plphys/kiac060 Li Y, Zhao LM, Guo CM, Tang M, Lian WL, Chen SY et al (2024) OsNAC103, an NAC transcription factor negatively regulates plant height in rice. Planta 259(2):35. https://doi.org/10.1007/s00425-023-04309-7 Luo J, Zhou JJ, Zhang JZ (2018) Aux/IAA Gene Family in Plants: Molecular Structure, Regulation, and Function. Int J Mol Sci 19(1):259. https://doi.org/10.3390/ijms19010259 Mochizuki N, Brusslan JA, Larkin R, Nagatani A, Chory J (2001) Arabidopsis genomes uncoupled 5 (GUN5) mutant reveals the involvement of Mg-chelatase H subunit in plastid-to-nucleus signal transduction. Proc Natl Acad Sci U S A 98(4):2053–2058. https://doi.org/10.1073/pnas.98.4.2053 Mircea DM, Calone R, Shakya R, Zuzunaga-Rosas J, Sestras RE, Boscaiu M et al (2023) Evaluation of Drought Responses in Two Tropaeolum Species Used in Landscaping through Morphological and Biochemical Markers. Life 13(4):960. https://doi.org/10.3390/life13040960 Niazian M (2019) Application of genetics and biotechnology for improving medicinal plants. Planta 249(4):953–973. https://doi.org/10.1007/s00425-019-03099-1 Ng LM, Melcher K, Teh BT, Xu HE (2014) Abscisic acid perception and signaling: structural mechanisms and applications. Acta Pharmacol Sin 35(5):567–584. https://doi.org/10.1038/aps.2014.5 Nagata N, Tanaka R, Satoh S, Tanaka A (2005) Identification of a vinyl reductase gene for chlorophyll synthesis in Arabidopsis thaliana and implications for the evolution of Prochlorococcus species. Plant Cell 17(1):233–240. https://doi.org/10.1105/tpc.104.027276 Park EJ, Lee WY, Kurepin LV, Zhang RC, Janzen L, Pharis RP (2015) Plant hormone-assisted early family selection in Pinus densiflora via a retrospective approach. Tree Physiol 35(1):86–94. https://doi.org/10.1093/treephys/tpu102 Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL (2015) StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol 33(3):290–295. https://doi.org/10.1038/nbt.3122 Qi XP, Ogden EL, Die JV, Ehlenfeldt MK, Polashock JJ, Darwish O et al (2019) Transcriptome analysis identifies genes related to the waxy coating on blueberry fruit in two northern-adapted rabbiteye breeding populations. BMC Plant Biol 19(1):460. https://doi.org/10.1186/s12870-019-2073-7 Singh A, Roychoudhury A (2023) Abscisic acid in plants under abiotic stress: crosstalk with major phytohormones. Plant Cell Rep 42(6):961–974. https://doi.org/10.1007/s00299-023-03013-w Teixeira da Silva JA, Cardoso JC, Dobránszki J, Zeng SJ (2015) Dendrobium micropropagation: a review. Plant Cell Rep 34(5):671–704. https://doi.org/10.1007/s00299-015-1754-4 Varshney V, Majee M (2021) JA Shakes Hands with ABA to Delay Seed Germination. Trends Plant Sci 26(8):764–766. https://doi.org/10.1016/j.tplants.2021.05.002 Van de Poel B, Van Der Straeten D (2014) 1-aminocyclopropane-1-carboxylic acid (ACC) in plants: more than just the precursor of ethylene! Front Plant Sci 5:640. https://doi.org/10.3389/fpls.2014.00640 Wang YD, Huang X, Huang XM, Su W, Hao YW, Liu HC et al (2022) BcSOC1 Promotes Bolting and Stem Elongation in Flowering Chinese Cabbage. Int J Mol Sci 23(7):3459. https://doi.org/10.3390/ijms23073459 Wu ZM, Zhang X, He B, Diao LP, Sheng SL, Wang JL et al (2007) A chlorophyll-deficient rice mutant with impaired chlorophyllide esterification in chlorophyll biosynthesis. Plant Physiol 145(1):29–40. https://doi.org/10.1104/pp.107.100321 Xing N, Li XQ, Wu SH, Wang ZW (2024) Transcriptome and Metabolome Reveal Key Genes from the Plant Hormone Signal Transduction Pathway Regulating Plant Height and Leaf Size in Capsicum baccatum. Cells 13(10):827. https://doi.org/10.3390/cells13100827 Yuan WJ, He ZY, Zhang SP, Zheng YP, Zhang XQ, He SQ et al (2023) Comparative transcriptomics provides insights into the pathogenic immune response of brown leaf spots in weeping forsythia. Tree Physiol 43(9):1641–1652. https://doi.org/10.1093/treephys/tpad060 Zhang YQ, Berman A, Shani E (2023) Plant Hormone Transport and Localization: Signaling Molecules on the Move. Annu Rev Plant Biol 74:453–479. https://doi.org/10.1146/annurev-arplant-070722-015329 Zhu JC, Cai DF, Wang JP, Cao JH, Wen YC, He JP et al (2021) Physiological and anatomical changes in two rapeseed (Brassica napus L.) genotypes under drought stress conditions. Oil Crop Sci 6(02):97–104. https://doi.org/10.1016/j.ocsci.2016-0153 Zhou MY, Huo JH, Wang CR, Wang WM (2022) UPLC/Q-TOF MS Screening and Identification of Antibacterial Compounds in Forsythia suspensa (Thunb.) Vahl Leaves. Front Pharmacol 12:704260. https://doi.org/10.3389/fphar.2021.704260 Zhao SL, Long WH, Wang YH, Liu LL, Wang YL, Niu M et al (2016) rice White-stripe leaf3 (wsl3) mutant lacking an HD domain-containing protein affects chlorophyll biosynthesis and chloroplast development. J Plant Biol 59:282–292. https://doi.org/10.1007/s12374-016-0459-8 Zhang CC, Wang S, Wang YF, Wang HY, Qin M, Dai XY et al (2023) plication of tissue culture technology of medicinal plants in sustainable development of Chinese medicinal resources. Zhongguo Zhong Yao Za Zhi 48(5):1186–1193. https://doi.org/10.19540/j.cnki.cjcmm.20221017.104 Zhou YS, Zhang T, Wang XC, Wu WQ, Xing JJ, Li ZL et al (2023) A maize epimerase modulates cell wall synthesis and glycosylation during stomatal morphogenesis. Nat Commun 14(1):4384. https://doi.org/10.1038/s41467-023-40013-6 Supplementary Files 2025.6.6Additionalfile.docx Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6833324\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":471572422,\"identity\":\"7761c695-9d47-4007-bc0e-b59a0971fb06\",\"order_by\":0,\"name\":\"Yanxia He\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yanxia\",\"middleName\":\"\",\"lastName\":\"He\",\"suffix\":\"\"},{\"id\":471572423,\"identity\":\"18912b3e-afcd-46c4-afe6-e0ef5bd5a9ab\",\"order_by\":1,\"name\":\"Yanping Zheng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yanping\",\"middleName\":\"\",\"lastName\":\"Zheng\",\"suffix\":\"\"},{\"id\":471572424,\"identity\":\"fe2ba77f-5b21-4381-a2eb-00d2676fe832\",\"order_by\":2,\"name\":\"Jiaqi Geng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jiaqi\",\"middleName\":\"\",\"lastName\":\"Geng\",\"suffix\":\"\"},{\"id\":471572425,\"identity\":\"705ffbbc-823d-41da-9858-953ce1d0f21e\",\"order_by\":3,\"name\":\"Xu Lu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xu\",\"middleName\":\"\",\"lastName\":\"Lu\",\"suffix\":\"\"},{\"id\":471572426,\"identity\":\"306cd55c-1ce2-4734-a054-5aa3af4a9c60\",\"order_by\":4,\"name\":\"Xiaoxiao Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xiaoxiao\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":471572427,\"identity\":\"6f6d50bf-fb50-431f-bb22-1483400b821f\",\"order_by\":5,\"name\":\"Xin Sun\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xin\",\"middleName\":\"\",\"lastName\":\"Sun\",\"suffix\":\"\"},{\"id\":471572428,\"identity\":\"5ec887f7-7e08-4a2c-9dcd-98a72ab73978\",\"order_by\":6,\"name\":\"Xiaoqian Zhang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xiaoqian\",\"middleName\":\"\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":471572429,\"identity\":\"ab396a0b-0171-4445-9b7b-f7cca8ec4f13\",\"order_by\":7,\"name\":\"Xianping Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Henan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xianping\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":471572430,\"identity\":\"7c58e2ea-913a-4710-866c-95e802af60df\",\"order_by\":8,\"name\":\"Wangjun Yuan\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYBACNmbmAwcSDGzk+BkYG0AIDCTwaeFjb0t88KEizViygVgtcjxnjA1nnDmUuOEAkEeUFjaJBDNp3rYDxsY3ktseMO6wyTM4wHzwNg+DXR4eLWlALXfkzG4kthswnkkrNjjAlmzNw5BcjEfLMaCWZ8ZmZw62STC2HQa6kMdMmofhQGIDTi2JbUAthxM394C1/Adq4f+GXwvPYWag94GGszeCtBwA2cKGXwt7GyM4kCWON7YbJLYlJ848zGZsOccgGacW+Wb+D5CobGZ/9uBjm11i3/HmhzfeVNjh1IJiI0MCiGIGEQZEqAdrGQWjYBSMglGADQAAbc1bxv7vHRcAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0002-8717-4649\",\"institution\":\"Henan University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Wangjun\",\"middleName\":\"\",\"lastName\":\"Yuan\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-06-06 03:57:47\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6833324/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6833324/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":84808352,\"identity\":\"4165b9ad-4f74-480f-9e16-00ab7d12f562\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:33:02\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":148195,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eGrowth status of FLS-1 and FLS-2 subcultured seedlings at different time periods\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/20333e1eb910a9b6028770f8.jpg\"},{\"id\":84807878,\"identity\":\"e5b6f11a-73b5-427d-968f-aab440981a6b\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":74592,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eChlorophyll content of FLS-1 and FLS-2 subcultured seedlings\\u003c/p\\u003e\\n\\u003cp\\u003eNote: a and b refer chlorophyll content of FLS-1 and FLS-2 subcultured seedlings on the 25\\u003csup\\u003eth\\u003c/sup\\u003e day 35\\u003csup\\u003eth\\u003c/sup\\u003e day respectively. (***\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/1394caad8a5887f48089a2b2.jpg\"},{\"id\":84807881,\"identity\":\"02a211ce-bd0a-4d59-9d11-6b6f38b61596\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":242482,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eUltrastructural differences in chloroplasts between two genotypes\\u003c/p\\u003e\\n\\u003cp\\u003eNote: The images of chloroplast a-d for FLS-2 and e-h for FLS-1. Ch, chloroplast; CM, chloroplast membrane; E, epidermis cell tissue; PT, palisade mesophyll tissue; Sg, starch grain; G, granum.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture3.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/6216f79dd2d3d19a465a466c.jpg\"},{\"id\":84807880,\"identity\":\"51716552-d7b7-4ea6-b5e7-4aab607b8a85\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":43644,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePrincipal component analysis (PCA) of the expression patterns\\u003c/p\\u003e\\n\\u003cp\\u003eNote: The horizontal axis represents the contribution degree of principal component 1 (PC1) in the two-dimensional figure to the distinguished samples, and the vertical axis represents the contribution degree of principal component 2 (PC2) in the two-dimensional figure to the distinguished samples. The red circle indicates the 3 replicates of 25_FLS-1, the light blue triangle represents the 3 replicates of 25_FLS-2, the green diamond represents the 3 replicates of 35_FLS-1, and the dark blue square represents the 3 replicates of 35_FLS-2.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/d1ca6b29b63f6f928e4c0d4f.jpg\"},{\"id\":84807884,\"identity\":\"55e7907d-befc-4287-be77-f8672f3a3614\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"jpg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":100011,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eVolcano plots showing the number of DEGs between two genotype\\u003c/p\\u003e\\n\\u003cp\\u003eNote: a and b refer Volcano plot analysis of differential genes on the 25\\u003csup\\u003eth\\u003c/sup\\u003e and 35\\u003csup\\u003eth\\u003c/sup\\u003e day, respectively. The horizontal axis represents the fold-change of gene expression between the two samples, and the vertical axis represents the statistical test value of gene expression difference. Red dots represent significantly up-regulated genes, blue dots represent significantly down-regulated genes, and gray dots represent non-significantly differenced genes. The closer the points are to the boundary, the more significant the expression difference.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture5.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/7ba1d0d39b6ea1bfd670d3e6.jpg\"},{\"id\":84810538,\"identity\":\"5bdbf633-b72a-4e5c-b23d-8f4a999d0ecc\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:49:02\",\"extension\":\"jpg\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":44331,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePrincipal component analysis (PCA) of metabolites for FLS-1 and FLS-2 samples\\u003c/p\\u003e\\n\\u003cp\\u003eNote: The abscissa represents the first principal component, and the ordinate represents the second principal component; The green circle represents 6 replicate samples of 35_FLS-1, the blue circle represents 6 replicate samples of 35_FLS-2, and the yellow circle represents 3 replicate samples of quality control. QC: Quality control sample.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture6.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/4bee40bb842cc28cbab9357d.jpg\"},{\"id\":84807885,\"identity\":\"976621bd-56c4-49b0-9c71-b1098c1b841f\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"jpg\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":117537,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAnnotation infographic of all metabolites\\u003c/p\\u003e\\n\\u003cp\\u003eNote: Each color represents a different class of compounds\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture7.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/16fdb6088fde2685365b8eed.jpg\"},{\"id\":84808357,\"identity\":\"8b67ec90-a3f9-4329-9edf-9f7a7c9fb463\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:33:02\",\"extension\":\"jpg\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":154756,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDifferentially expressed genes (DEGs) in the chlorophyll metabolic pathway\\u003c/p\\u003e\\n\\u003cp\\u003eNote: In the figure, circle represent chemical compounds, the blue oval box represent the synthetic related hormones, and the yellow box indicate the differentially expressed genes within each pathway. The EVM number corresponds to the gene ID. The two squares in the heatmap from left to right represent 25_FLS-1_vs_25_FLS-2 and 35_FLS-1_vs_35_FLS-2, The black text at the top of the heatmap represents the abbreviation of the enzyme name. Blue indicates down-regulation and red indicates up-regulation, the darker the color, the greater the fold change.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture8.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/194f08a8afebf28c68474fa6.jpg\"},{\"id\":84807900,\"identity\":\"9253097d-572d-4cc6-898d-4b51069df8b8\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"jpg\",\"order_by\":9,\"title\":\"Figure 9\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":404782,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDifferentially expressed genes (DEGs) in plant hormone biosynthesis pathways\\u003c/p\\u003e\\n\\u003cp\\u003eNote: a-e refer Gibberellin, Ethylene, Auxin, Cytokinin and Abscisic acid respectively. In the figure, circle represent chemical compounds, the blue oval box represent the synthetic related hormones, and the yellow box indicate the differentially expressed genes within each pathway. The EVM number corresponds to the gene ID. The two squares in the heatmap from left to right represent 25_FLS-1_vs_25_FLS-2 and 35_FLS-1_vs_35_FLS-2, The black text at the top of the heatmap represents the abbreviation of the enzyme name. Blue indicates down-regulation and red indicates up-regulation, the darker the color, the greater the fold change.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture9.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/92ace6416ce60ab2ad701850.jpg\"},{\"id\":88640735,\"identity\":\"e46d2eaf-0554-474b-8c79-6415cd00a0c3\",\"added_by\":\"auto\",\"created_at\":\"2025-08-08 16:03:44\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2641031,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/f76f5b8c-6210-43c9-8ba3-1c23d7c88412.pdf\"},{\"id\":84807888,\"identity\":\"e812292d-d370-4717-a34f-a9d94112b48b\",\"added_by\":\"auto\",\"created_at\":\"2025-06-17 14:25:02\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":625225,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"2025.6.6Additionalfile.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6833324/v1/86cffd693d1475249b076d0a.docx\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Integrated Morphological, Transcriptomic, and Metabolomic Profiling Reveals Differential Development Mechanisms in Two Weeping Forsythia Genotypes during Tissue Culture\",\"fulltext\":[{\"header\":\"Key Message\",\"content\":\"\\u003cp\\u003eElucidating the molecular mechanisms underlying growth differences between \\u003cem\\u003eForsythia\\u003c/em\\u003e genotypes in tissue culture.\\u003c/p\\u003e\"},{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003eWeeping forsythia (\\u003cem\\u003eForsythia suspensa\\u003c/em\\u003e (Thunb.) Vahl), a deciduous shrub belonging to the Oleaceae family, is renowned for its medicinal and ornamental value. The fruit of this species, commonly referred to as \\\"Forsythiae Fructus\\\" in Traditional C hinese Medicine (TCM), is extensively used for the treatment of various conditions, including gonorrhea, erysipelas, inflammation, pyrexia, and ulcers (Zhou et al. \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Liu et al. \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). \\u003cem\\u003eF. suspensa\\u003c/em\\u003e is naturally distributed across regions in China, such as Henan, Shanxi, Shaanxi, and Hebei (Gao et al. \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Its branches are characterized by their graceful, arching form, and the plant produces vibrant yellow flowers that bloom in early spring. These attributes make it a popular choice for urban greening and beautification initiatives (Li et al. \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eGiven its medicinal, ornamental, and economic significance, \\u003cem\\u003eF. suspensa\\u003c/em\\u003e has garnered increasing attention in recent years. However, the growing market demand and diminishing natural resources have underscored the importance of cultivation, presenting substantial opportunities for its development in rural areas (Li et al. \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). Micropropagation, a tissue culture technique, enables the production of millions of clonal individuals through the induction of morphogenesis from various plant tissues or organs. This approach is widely utilized for the large-scale propagation of medicinal and ornamental plant species, as well as for the conservation of valuable genetic resources, including \\u003cem\\u003eDendrobium\\u003c/em\\u003e (Teixeira et al. 2015), \\u003cem\\u003eSaussurea involucrata\\u003c/em\\u003e (Kuo et al. \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e), and \\u003cem\\u003eCannabis sativa\\u003c/em\\u003e (Adhikary et al. \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). Consequently, plant tissue culture serves as a highly effective platform for the large-scale cultivation and production of superior forsythia germplasm. It ensures a consistent and sustainable supply of raw materials for TCM without exerting pressure on natural habitats (Niazian \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Zhang et al. \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e ).\\u003c/p\\u003e \\u003cp\\u003eIn the case of weeping forsythia, a comprehensive and efficient in vitro rapid propagation system has been successfully developed using tissue culture technology (Yuan et al. \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e ). Notably, significant variations in growth and development have been observed among different weeping forsythia genotypes under optimal culture conditions, highlighting the influence of genetic diversity on in vitro propagation outcomes.\\u003c/p\\u003e \\u003cp\\u003eIn this study, an optimized tissue culture system was established for two distinct genotypes (FLS-1 and FLS-2) of weeping forsythia under laboratory conditions. Key growth indices, ultrastructural characteristics, and the chlorophyll a and chlorophyll b contents of subcultured seedlings were systematically evaluated. Comparative transcriptomic and metabolomic analyses were conducted to identify differentially expressed genes (DEGs) and differentially expressed metabolites (DEMs) between the two genotypes of FLS-1 and FLS-2. These findings provide valuable insights into the photosynthetic difference and underlying mechanisms driving growth differences among genotypes of weeping forsythia during tissue culture.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Plant materials and samples\\u003c/h2\\u003e \\u003cp\\u003eTwo elite weeping forsythia genotypes, FLS-1 and FLS-2, were used as experimental materials. The plants were cultivated in the field at Da Mei Lian Qiao Company, Sanmenxia, Henan Province, China. Tissue culture experiments were conducted in the laboratory of the School of Life Sciences, Henan University. Healthy stem segments of FLS-1 and FLS-2 were selected as explants and inoculated onto an optimized and sterilized Murashige and Skoog (MS) medium supplemented with 3.0 mg\\u0026middot;L⁻\\u0026sup1; 6-benzylaminopurine (6-BA), 1.0 mg\\u0026middot;L⁻\\u0026sup1; indole-3-butyric acid (IBA), 30 g\\u0026middot;L⁻\\u0026sup1; sucrose, and 7 g\\u0026middot;L⁻\\u0026sup1; agar, adjusted to pH 6.0 prior to sterilization. The cultures were maintained under optimal conditions: a temperature of 25\\u0026deg;C, a light intensity of 2,000\\u0026ndash;2,500 lx, and a photoperiod of 12 hours light and 12 hours darkness. Subsequently, the seedlings were subcultured under the same conditions.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Determination of growth index and chlorophyll content during the tissue culture of \\u003cem\\u003eF. suspensa\\u003c/em\\u003e\\u003c/h2\\u003e \\u003cp\\u003ePlant heights of FLS-1 and FLS-2 were measured every 5 days over 1-month period, beginning on the 10th day of subculture, with each measurement performed in triplicate. Fresh leaves were collected on the 25th and 35th day for chlorophyll determination. Chlorophyll was extracted using 80% acetone for 24 hours in darkness, and its content was quantified using a spectrophotometer following the method described as Mircea (Mircea et al. \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Anatomical Structure Observation\\u003c/h2\\u003e \\u003cp\\u003eThe transmission electron microscopy (TEM) protocol was adapted from the method of Zhou et al. with minor modifications (Zhou et al. \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The middle region of the third leaf from 35-day-old subcultured seedlings was harvested for analysis. Leaf samples were immediately fixed in a solution containing 5% glutaraldehyde and 4% paraformaldehyde, buffered with 0.1 M sodium phosphate (pH 7.2). Following rinsing in the same buffer, the samples were post-fixed in 1% osmium tetroxide, also in 0.1 M sodium phosphate (pH 7.2), for 3 hours at 4\\u0026deg;C. The specimens were subsequently dehydrated through a graded ethanol series, transferred to acetone, and infiltrated with Epon812 epoxy resin for embedding. Ultra-thin sections were then prepared using a Leica EM UC7 ultramicrotome and stained with uranyl acetate and lead citrate. The prepared sections were examined using a FEI Talos F200C transmission electron microscope (Thermo Fisher Scientific, USA) for ultrastructural analysis.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 RNA extraction, library construction and sequencing\\u003c/h2\\u003e \\u003cp\\u003eThe whole tissue culture seedlings of FLS-1 and FLS-2 were harvested on the 25th day and 35th day at noon, immediately flash-frozen in liquid nitrogen, and stored at -80\\u0026deg;C for subsequent transcriptome sequencing analysis. Each group consisted of three biological replicates.Total RNA was extracted from tissue samples using TRIzol\\u0026reg; Reagent according to the manufacturer\\u0026rsquo;s instructions. RNA quality was assessed using the 5,300 Bioanalyzer (Agilent) and quantified with the ND-2000 spectrophotometer (NanoDrop Technologies). Only high-quality RNA samples, meeting the criteria of OD260/280\\u0026thinsp;=\\u0026thinsp;1.8\\u0026ndash;2.2, OD260/230\\u0026thinsp;\\u0026ge;\\u0026thinsp;2.0, and a RNA Integrity Number (RIN)\\u0026thinsp;\\u0026ge;\\u0026thinsp;6.5, were used for library construction.\\u003c/p\\u003e \\u003cp\\u003eRNA purification, library construction, and sequencing were performed by Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd. (Shanghai, China). Raw sequencing data were processed for quality control and trimming using the fastp tool (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/OpenGene/fastp\\u003c/span\\u003e\\u003cspan address=\\\"https://github.com/OpenGene/fastp\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) (Chen et al. \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e), employing default parameters. Clean reads were then aligned to the reference genome in orientation mode using HISAT2 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://ccb.jhu.edu/software/hisat2/index.shtml\\u003c/span\\u003e\\u003cspan address=\\\"http://ccb.jhu.edu/software/hisat2/index.shtml\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) (Kim et al. \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e;Li et al. \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The mapped reads for each sample were subsequently assembled as per the method outlined by Pertea et al (Pertea et al. \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 Differential expression analysis and functional enrichment\\u003c/h2\\u003e \\u003cp\\u003eTo identify DEGs between the two samples, transcript expression levels were quantified using the Fragments Per Kilobase of exon model per Million mapped fragments (FPKM) method. Gene abundances were calculated using RSEM (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://deweylab.github.io/RSEM/\\u003c/span\\u003e\\u003cspan address=\\\"http://deweylab.github.io/RSEM/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) (Li et al. 2011). Differential expression analysis was conducted with DESeq2 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://bioconductor.org/packages/stats/bioc/DESeq2\\u003c/span\\u003e\\u003cspan address=\\\"http://bioconductor.org/packages/stats/bioc/DESeq2\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) (Love et al. \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). Genes with an absolute log₂ fold change (|log₂FC|)\\u0026thinsp;\\u0026ge;\\u0026thinsp;2 and a false discovery rate (FDR)\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 were considered significantly differentially expressed.\\u003c/p\\u003e \\u003cp\\u003eGene Ontology (GO) (Ashburner et al. \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa and Goto \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e) enrichment analyses were performed to elucidate the functional roles and biological pathways associated with the DEGs.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6 qRTPCR validation\\u003c/h2\\u003e \\u003cp\\u003ePrimers for the 10 selected DEGs were designed using Primer 5.0 software (Lalitha \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e). Quantitative Real-time polymerase chain reaction (qRT-PCR) was performed using a LightCycler\\u0026reg; 480 Real-Time PCR System (Roche, Switzerland) with the Hieff qPCR SYBR Green Master Mix (Yisheng, Shanghai, China). The elongation factor-1α (EF-1α) gene served as an internal reference for normalization. Gene-specific primer sequences are provided in Table S1.\\u003c/p\\u003e \\u003cp\\u003eRelative gene expression levels were calculated using the method as Qi et al (Qi et al. \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Each experiment included three biological replicates and three technical replicates to ensure accuracy and reproducibility.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.7 Metabolomics analyses\\u003c/h2\\u003e \\u003cp\\u003eSamples of FLS-1 and FLS-2 were collected on the 35th day at noon of subculture for metabolomic analysis, with each group consisting of three biological replicates. The samples, along with grinding beads, were placed into centrifuge tubes for metabolite extraction. LC-MS/MS analysis was performed by Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) following standard protocols (Lu et al. \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e). Data analysis was conducted using the Majorbio Cloud Platform (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://cloud.majorbio.com\\u003c/span\\u003e\\u003cspan address=\\\"https://cloud.majorbio.com\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) following database retrieval. Principal Component Analysis (PCA) and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed on the pre-processed data matrix using the ropls package (version 1.6.2) in R language. The model's stability and reliability were assessed through seven cycles of interactive cross-validation.\\u003c/p\\u003e \\u003cp\\u003eDifferential metabolites between the two groups were mapped to biochemical pathways using metabolic enrichment and pathway analysis based on the KEGG database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.genome.jp/kegg/\\u003c/span\\u003e\\u003cspan address=\\\"http://www.genome.jp/kegg/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) (Kanehisa et al. 2000). These metabolites were further classified according to their involvement in specific pathways or their functional roles.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.1 Growth of FLS-1 is significantly slower than FLS-2 during tissue culture\\u003c/h2\\u003e\\n \\u003cp\\u003eThe proliferation and growth of weeping forsythia seedlings became noticeable after the 10th day of subculture. Compared to FLS-2, the growth of FLS-1 was significantly slower, as evidenced by a reduced average plant height and the appearance of chlorosis, characterized by distinctly lighter green leaves (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). Furthermore, FLS-1 exhibited significantly fewer total nodes, branches, and a shorter average internode length compared to FLS-2 (Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). These findings indicate that the period from the 25th to the 35th day represents a phase of rapid growth in weeping forsythia under tissue culture conditions.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003ePhenotypic data of FLS-1 and FLS-2 subcultured seedlings during growth\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"9\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\" rowspan=\\\"2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eSingle Plant Height\\u003c/p\\u003e\\n \\u003cp\\u003e(mm)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eTotal Number of Branches(pcs)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eNumber of Branches\\u003c/p\\u003e\\n \\u003cp\\u003e(pcs)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\" colspan=\\\"2\\\"\\u003e\\n \\u003cp\\u003eAverage Internode Length(mm)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-1\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFLS-2\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.37\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.25e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.18\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.28F\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.42\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.25\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.11F\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09b\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.83\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.08C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.31\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.13a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09D\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.87\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.26e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.96\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.44F\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.54\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.13e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.08\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.22E\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.38\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12ab\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.10BC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.34\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.10a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.76\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.22D\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.35\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.4de\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15.76\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.64E\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.88\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.19de\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.92\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.19D\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.38\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12ab\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.00BC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.44\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.10a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.17\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.16CD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.99\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.59cd\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20.05\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.94D\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.54\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.25cd\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.58\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.23C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.58\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12ab\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.04\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.04BC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.46\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.16a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.55\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.19C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e30d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e9.18\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.78bc\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e28.58\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.37C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.17\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.27bc\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.96\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.19B\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.63\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12ab\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.08\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.06B\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.47\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.17a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.23\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.23B\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10.66\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.93b\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e40.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.1B\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.63\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.22ab\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.58\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.22B\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.67\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12ab\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.08\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.06B\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.50\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.13a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.89\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.30A\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e40d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e13.98\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.24a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e50.41\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.54A\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.21\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.39a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.25\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.35A\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.71\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.14a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.09A\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.18a\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.99\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.31A\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"9\\\"\\u003eNote: Different lowercase letters and uppercase letters within the same column indicate the significant differences between FLS-1 and FLS-2 in different time points, respectively (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05).\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.2 Significant difference in chlorophyll content between the two genotypes\\u003c/h2\\u003e\\n \\u003cp\\u003eIn this study, the chlorophyll a content of FLS-1 was 0.51 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e on the 25th day, whereas FLS-2 exhibited a content of 1.41 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e. On the 35th day, the chlorophyll a content was 0.60 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in FLS-1 and 1.10 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in FLS-2. For chlorophyll b, the content was 0.161 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in FLS-1 and 0.409 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in FLS-2 on the 25th day, and 0.190 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in FLS-1 and 0.363 mg∙g\\u003csup\\u003e\\u0026minus;\\u0026thinsp;1\\u003c/sup\\u003e in FLS-2 on the 35th day. Statistical analysis using a T-test demonstrated significant differences in both chlorophyll a and chlorophyll b contents between FLS-1 and FLS-2 (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.3 Difference of leaf ultrastructure between two genotypes\\u003c/h2\\u003e\\n \\u003cp\\u003eAt low magnification, the chloroplasts in mesophyll cells of FLS-1 and FLS-2 were in rings close to the cell wall. However, the palisade tissue cells of FLS-2 were small and neatly arranged, while that of FLS-1 were relatively large and loosely (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea,b,e). The chloroplast morphology of FLS-2 was smooth, the bilayer membrane structure was complete and clear, and the structure of the inner capsule was clearly visible (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ed). Generally, 2\\u0026ndash;3 starch granules can be seen in a single chloroplast (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ec). While the morphological edge of FLS-1 was fuzzy, the boundary of the bilayer membrane was unclear, and the texture of the inner capsule overlaps could not be identified. The number of starch granules in a single chloroplast was visibly reduced (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003eg,h).\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.4 Transcriptome analysis\\u003c/h2\\u003e\\n \\u003cp\\u003eA total of 12 forsythia tissue culture seedling samples were sequenced using the Illumina NovaSeq 6,000 platform. After filtering out low-quality sequences, a total of 96.96 Gb of clean data were obtained. The effective data amount for each sample exceeded 6.04 Gb, with the average Q30 value of each sample being above 95.32%. The guanine-cytosine (GC) content ranged from 43.91\\u0026ndash;44.49%. Additionally, the overall alignment rate for the 12 samples ranged from 91.45\\u0026ndash;92.00%, with the unique mapping alignment rate ranging from 88.3\\u0026ndash;89.12% (Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eQuality control assessment of sequencing data\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSample\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eClean reads\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eQ30(%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGC content(%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTotal mapped\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eUniquely mapped\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25_FLS-1_1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e55721004\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e51000271(91.53%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e49280832(88.44%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25_FLS-1_2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e59287946\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.63\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.24\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e54419881(91.79%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e52696039(88.88%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25_FLS-1_3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e59848444\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.68\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e54805232(91.57%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e53037157(88.62%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25_FLS-2_1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e57892392\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.58\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.26\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e52941403(91.45%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e51218413(88.47%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25_FLS-2_2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e40396634\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36941403(91.45%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e35820138(88.67%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e25_FLS-2_3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e59809034\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e54698240(91.45%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e52866257(88.39%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35_FLS-1_1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e62139654\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.59\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e56916878(91.6%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e54869701(88.3%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35_FLS-1_2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e63134870\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.72\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.00\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e57909494(91.72%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e55986672(88.68%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35_FLS-1_3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e54772656\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e43.91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e50173731(91.6%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e48418411(88.4%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35_FLS-2_1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e48363582\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44284768(91.57%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e42836722(88.57%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35_FLS-2_2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e49923374\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.21\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e45713008(91.57%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44302334(88.74%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e35_FLS-2_3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e47782580\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e95.57\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e44.49\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e43958249(92.0%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e42583282(89.12%)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eNote: Sample: The name of the sample; Clean reads: The total number of items in the sequencing data after quality control; Q30 (%): Quality assessment of sequencing data after quality control, Q30 refer to the percentage of bases with sequencing quality above 99.9% in the total base; GC content (%): The percentage of the total sum of G and C bases corresponding to the quality control data in the total bases.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003eA total of 33,062 unigenes were annotated, and correlation analysis as well as PCA were performed for all samples. The PCA results showed that the expression patterns of FLS-1 and FLS-2 were distinctly separated, classifying them as independent groups (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). Compared to FLS-2, a total of 2,059 DEGs were identified in FLS-1 on the 25th day, of which 1,078 were up-regulated and 981 down-regulated. On the 35th day, 3,482 DEGs were identified, with 2,059 up-regulated and 1,423 down-regulated (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cp\\u003eOn the 25th day, up-regulated genes were primarily enriched in oxidoreductase activity, binding, secondary metabolic processes, and phenylpropanoid metabolism, while down-regulated genes were mainly associated with photosynthesis and chlorophyll binding. On the 35th day, up-regulated genes were enriched in defense responses to external stimuli and oxidoreductase activity processes, while the down-regulated genes were again enriched in photosynthesis and chlorophyll binding, consistent with findings from the 25th day (Table S2).\\u003c/p\\u003e\\n \\u003cp\\u003eOn the 25th and 35th day, the DEGs of FLS-1 were mapped to 111 and 122 KEGG pathways, respectively, with 9 and 12 pathways significantly enriched. Notably, \\u0026quot;photosynthesis\\u0026quot; and \\u0026quot;photosynthesis-antenna proteins\\u0026quot; were among the significantly enriched pathways (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). Based on GO and KEGG enrichment analyses, and considering the observed absence of chlorophyll in the FLS-1 samples, we focused on DEGs associated with the photosynthetic pathway. A total of 46 DEGs were identified, including 10 genes involved in photosystem I (PSI), 10 in photosystem II (PSII), 5 in F-type ATPase, 4 in the light-harvesting chlorophyll protein complex I (LHCI), and 13 in the light-harvesting chlorophyll protein complex II (LHCII). Notably, all of these genes showed down-regulated expression patterns, further indicating significant disruption of photosynthetic processes in FLS-1.\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eKEGG pathway enrichment analysis of differentially expressed genes in FLS-1_vs_FLS-2 on the 25th and 35th day\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"5\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePathway ID\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eDescription\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNum\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePvalue\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eQvalue\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003e25d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00196\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhotosynthesis-antenna proteins\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.00E-07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.11E-05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00052\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGalactose metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.47E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e9.14E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00940\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhenylpropanoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e23\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.97E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.09E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00945\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eStilbenoid, diarylheptanoid and gingerol biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4.51E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.25E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00592\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ealpha-Linolenic acid metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.86E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.96E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap04626\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePlant-pathogen interaction\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e36\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.62E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.99E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00073\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCutin, suberine and wax biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.40E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.33E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00520\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAmino sugar and nucleotide sugar metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.54E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.41E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00941\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFlavonoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.84E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.50E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" colspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003e35d\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00196\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhotosynthesis-antenna proteins\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.31E-14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.70E-12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00940\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhenylpropanoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e38\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.18E-06\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.33E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap04626\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePlant-pathogen interaction\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.75E-05\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.52E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00195\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhotosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.37E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.87E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00945\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eStilbenoid, diarylheptanoid and gingerol biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.03E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.20E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00908\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eZeatin biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.98E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.28E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00904\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eDiterpenoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.98E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.28E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00909\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eSesquiterpenoid and triterpenoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.87E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.95E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00630\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eGlyoxylate and dicarboxylate metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e19\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.74E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.36E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00592\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ealpha-Linolenic acid metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.39E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.91E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap04075\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePlant hormone signal transduction\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e54\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.02E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.35E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00910\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNitrogen metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.85E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.91E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"5\\\"\\u003eNote: Pathway id: The pathway identifier; Description: The name of the pathway; Num: The number of genes or transcripts enriched in this pathway; Pvalue: Uncorrected P-value, with smaller values indicating higher statistical significance; Qvalue: Adjusted p-value after correction.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.5 Metabolome profiles between FLS-1and FLS-2\\u003c/h2\\u003e\\n \\u003cp\\u003eTo examine the differences in metabolites between tissue culture seedlings of two genotypes, metabolomics analysis was conducted using LC-MS. PCA was employed to analyze the metabolomic profiles and provide insights into distinct clustering patterns between the groups (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). A total of 1,643 metabolites were identified, of which 1,595 had defined chemical formulas. The major classes of metabolites identified included terpenoids (16.18%), lipids (13.86%), carbohydrates and derivatives (9.53%), amino acids and derivatives (8.28%), and flavonoids (7.21%) (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cp\\u003eDEMs were identified using both univariate and multivariate analyses. In comparison to the FLS-2 genotype, 358 metabolites were upregulated and 205 were downregulated in FLS-1 samples. The 563 DEMs were mapped to 77 KEGG pathways, with 15 pathways showing significant enrichment. These included pathways such as arginine biosynthesis, \\u0026beta;-alanine metabolism, flavonoid biosynthesis, diterpene biosynthesis, flavonoid and flavonol biosynthesis, and phenylpropanoid biosynthesis (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u0026nbsp;\\u003ctable id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eSignificantly enriched pathways of differential metabolites\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003ccolgroup cols=\\\"5\\\"\\u003e\\u003c/colgroup\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePathway ID\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePathway Description\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNum\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePvalue\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eQvalue\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00590\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eArachidonic acid metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.62E-10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.25E-08\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00940\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhenylpropanoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.56E-04\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.14E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00591\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eLinoleic acid metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.95E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.01E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap01232\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNucleotide metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.73E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.25E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00380\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTryptophan metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5.69E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.77E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00944\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFlavone and flavonol biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.20E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.95E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00904\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eDiterpenoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.43E-03\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.17E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00941\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFlavonoid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.05E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.01E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00460\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eCyanoamino acid metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.55E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.32E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00770\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePantothenate and CoA biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.60E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.23E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00240\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePyrimidine metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.82E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.27E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00410\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ebeta-Alanine metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.00E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.28E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00999\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBiosynthesis of various plant secondary metabolites\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.71E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.60E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap02010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eABC transporters\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.77E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2.08E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00220\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eArginine biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.85E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.97E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00470\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eD-Amino acid metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.55E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.15E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00780\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eBiotin metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6.88E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.12E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00360\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhenylalanine metabolism\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7.69E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.29E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00960\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTropane, piperidine and pyridine alkaloid biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8.79E-02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.56E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003emap00400\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ePhenylalanine, tyrosine and tryptophan biosynthesis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1.00E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3.86E-01\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"5\\\"\\u003eNote: Pathway id: The pathway identifier; Description: The name of the pathway; Num: The number of genes or transcripts enriched in this pathway; Pvalue: Uncorrected P-value, with smaller values indicating higher statistical significance; Qvalue: Adjusted p-value after correction..\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n \\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.6 Analysis of DEGs and DEMs in chlorophyll synthesis and plant hormone synthesis Pathway\\u003c/h2\\u003e\\n \\u003cp\\u003eChlorophyll is a key pigment involved in the process of photosynthesis. KEGG pathway analysis identified a significant enrichment of 10 DEGs associated with chlorophyll synthesis. Further examination revealed that the expression of these genes was markedly downregulated at both the 25th and 35th days. Notably, the enzymes encoded by these downregulated genes encompass nearly the entire biosynthetic pathway of chlorophyll, including glutamyl-tRNA reductase (HemA), 5-aminolevulinic acid dehydratase (HemB), magnesium chelatase subunit H (chlH), magnesium protoporphyrin IX monomethyl ester (oxidative) cyclase (chlE), and protochlorophyllide reductase (por) (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e).\\u003c/p\\u003e\\n \\u003cp\\u003eIn this study, 13 DEGs involved in the gibberellin biosynthesis pathway were identified. These included 4 copalyl diphosphate synthase (CPS) genes, 1 ent-kaurene synthase (KS) gene, 1 kaurene oxidase (KO) gene, 2 ent-kaurenoic acid oxidase (KAO) genes, 1 GA20-oxidase (GA20ox) gene, 2 GA2-oxidase (GA2ox) genes, and 2 GA3-oxidase (GA3ox) genes. Expression analysis revealed that KS and KO genes were highly expressed on the 25th and 35th day, whereas CPS and GA20ox exhibited lower expression levels. Additionally, five DEMs involved in gibberellin biosynthesis were detected, including GA12-aldehyde, GA12, GA53, GA24, and GA7. Of these, the first four metabolites were upregulated, while GA7 was downregulated (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ea).\\u003c/p\\u003e\\n \\u003cp\\u003eFurther analysis identified 3 DEGs encoding S-adenosylmethionine synthetase (SAMS), 1 DEG encoding 1-aminocyclopropane-1-carboxylic acid synthase (ACS), and 1 DEG encoding 1-aminocyclopropane-1-carboxylic acid oxidase (ACO), all involved in ethylene biosynthesis. SAMS gene expression was significantly downregulated on both the 25th and 35th days, while ACS and ACO showed upregulation. In ethylene signal transduction, 17 DEGs were identified, including Constitutive Triple Response 1 (CTR1), EIN3-binding F-box 1/2 (EBF1/2), and Ethylene Response Factor 1 (ERF1), all of which were upregulated (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003eb).\\u003c/p\\u003e\\n \\u003cp\\u003eThree DEGs related to auxin biosynthesis were also identified, including 2 tryptophan decarboxylase (TDC) genes and 1 aldehyde dehydrogenase (ALDH) gene, with ALDH showing high expression at both time points. Furthermore, a total of 32 DEGs involved in auxin signal transduction were detected, consisting of 10 AUX/IAA genes, 3 Gretchen Hagen3 (GH3) genes, and 19 small auxin upregulated RNA (SAUR) genes. Notably, AUX/IAA and SAUR families were downregulated, while GH3 was upregulated (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ec).\\u003c/p\\u003e\\n \\u003cp\\u003eRegarding cytokinin synthesis, 1 DEG encoding isopentenyl transferase (IPT) was downregulated, while 4 DEGs involved in cytokinin signal transduction were identified, including 2 cytokinin response 1 (CRE1) genes, 1 B-type Arabidopsis response regulator (B-ARR), and 1 A-type Arabidopsis response regulator (A-ARR). CRE1 was highly expressed, B-ARR was significantly downregulated, and A-ARR showed downregulation on day 25 and upregulation on day 35 (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ed).\\u003c/p\\u003e\\n \\u003cp\\u003eFinally, 4 DEGs related to abscisic acid (ABA) biosynthesis were identified, including 1 lutein deficient 5 (LUT5) gene and 3 9-cis-epoxycarotenoid dioxygenase (NCED) genes, most of which showed low expression. In ABA signal transduction, 6 DEGs were identified, including 1 pyrabactin resistance 1-like (PYL) gene and 5 protein phosphatase 2C (PP2C) genes, with PYL highly expressed and PP2C genes showing downregulation on day 25 and upregulation on day 35. Additionally, the expression of abscisic aldehyde (a DEM) was downregulated (Fig. \\u003cspan class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ee).\\u003c/p\\u003e\\n \\u003cp\\u003eThis comprehensive analysis highlights the intricate regulation of hormonal pathways, particularly gibberellin, ethylene, auxin, cytokinin, and ABA, in the development and signaling processes of tissue culture seedlings.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e3.7 qRT-PCR validation\\u003c/h2\\u003e\\n \\u003cp\\u003eTo validate the reliability of the transcriptome data, 10 DEGs, comprising 6 downregulated and 4 upregulated genes, were randomly selected from significantly enriched pathways for qRT-PCR analysis. The qRT-PCR results confirmed that the expression patterns of these genes were consistent with the RNA-Seq data, demonstrating the high reliability of the sequencing results for subsequent analyses (Fig. S1).\\u003c/p\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"4 Discussion\",\"content\":\"\\u003cp\\u003eWeeping forsythia is a widely distributed plant in China, valued for its ornamental, ecological, and medicinal properties (Li et al. \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). To meet market demand and improve the quality of medicinal materials, artificial cultivation of forsythia has increased significantly in recent years (Yuan et al. \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Plant tissue culture technology has been employed to quickly generate superior varieties. Therefore, it is important to analyze the mechanism of causing the slow growth and development of some genotype (such as FLS-1) plants during tissue culture for weeping forsythia breeding.\\u003c/p\\u003e \\u003cp\\u003ePlant height is an important trait of plant phenotype, reflecting a certain stage of growth and development (Cheng et al. \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Studies have shown that plant dwarfing, lower ear height, and hindered growth and development are closely related to the decline of biological yield and economic yield (Hua \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). In this study, compared to FLS-2, the seedlings of the FLS-1 genotype exhibited slower growth, pronounced leaf chlorosis, and a significant reduction in chlorophyll content. The chloroplast abnormalities of FLS-1 can be seen in the microstructure, such as blurred boundary of bilayer membrane, reduced internal starch granules, and unclear internal capsule stacking texture. These structural variations can seriously affect the light reaction in photosynthesis, resulting in lower photosynthetic efficiency of plants (Zhu et al. \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e; Kulkov et al. \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e; Wu et al. \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). Chlorophyll is an important natural green pigment responsible for the absorption of light energy and conversion into chemical energy via photosynthesis in plants (da and Sant'Anna 2017). The complete biosynthetic pathway of chlorophyll, from glutamyl-tRNA to the production of chlorophyll a and chlorophyll b, involves approximately 20 distinct enzymatic steps. Protoporphyrin IX, a precursor to chlorophyll, is synthesized through several enzymatic steps (Nagata et al. \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e; Li et al. \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). Mutations in the chlH gene have been shown to cause chlorophyll deficiency, resulting in a yellow or chlorotic phenotype in both \\u003cem\\u003eOryza sativa\\u003c/em\\u003e (Zhao et al. \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e) and \\u003cem\\u003eArabidopsis thaliana\\u003c/em\\u003e (Mochizuki et al. \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2001\\u003c/span\\u003e). Kong et al (Kong et al. \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e) reported a novel rice mutant, YGL8, which displays a yellow-green leaf phenotype accompanied by abnormal chloroplast development. In the present study, transcriptome sequencing identified 10 DEGs associated with chlorophyll biosynthesis, all of which showed down-regulated expression patterns. These genes include 2 HemA, 1 HemB, 2 chlH, 2 chlE, and 3 por (porphyrin biosynthetic enzymes). Glutamyl-tRNA reductase, a key enzyme in this pathway, is downregulated in FLS-1 compared to FLS-2. This may lead to reduced synthesis of 5-aminolevulinic acid (ALA) and protoporphyrin IX, impairing chlorophyll production and resulting in leaf color variation in the study (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eHormonal homeostasis is pivotal in coordinating plant growth and development, with regulation occurring at multiple levels, including hormone biosynthesis, degradation, perception, and signal transduction (Zhang et al. \\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Gibberellins (GAs), including GA1, GA3, GA4, and GA7, are diterpenoid hormones that regulate various aspects of plant growth and development, such as germination, stem elongation, flower formation, leaf senescence, and fruit ripening (Li et al. \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e; Lee et al. \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Wang et al. \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e). GAs are synthesized through complex pathways, with key enzymes like CPS, KS, KO, and KAO catalyzing the initial steps. Among the genes involved, GA20ox plays a critical role in regulating plant height (Elias et al. \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). Inhibition of GA20ox reduces internode length and plant stature in apple trees, while its overexpression leads to increased height and branch diameter in pine trees (Park et al. \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e). Consistent with previous studies, our findings show that downregulation of GA20ox expression on day 25 and 35 resulted in reduced plant height and internode length in FLS-1. Metabolomics analysis revealed a decrease in GA7 levels. Attempts to promote FLS-1 growth by supplementing GA7 to MS medium, however, efforts to enhance FLS-1 growth by supplementing GA7 into MS medium yielded inconclusive results (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ea).\\u003c/p\\u003e \\u003cp\\u003eThe biosynthesis of ethylene involves methionine conversion to S-adenosylmethionine (AdoMet) by SAMS, followed by its transformation to 1-aminocyclopropane-1-carboxylic acid (ACC) by ACS, and finally to ethylene by ACO (Van et al. 2014; Luo et al. \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). ACS and ACO are critical enzymes in ethylene biosynthesis, maintaining balanced ethylene production during normal development (Khan et al. \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eOverexpression of CiACS4 induces a dwarf phenotype and increased ethylene release, while its suppression enhances plant height in transgenic citrus, demonstrating its key role in growth regulation (Chu et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). This is further supported by our findings, where the high expression of ACS and ACO enhances ethylene biosynthesis, thereby influencing the growth of FLS-1 and resulting in a dwarf phenotype (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003eb). Auxin in plants can act directly on cell membranes and intracellular components to regulate essential processes such as cell division, elongation, and differentiation (Xing et al. \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e2024\\u003c/span\\u003e). The KEGG pathways enriched among the DEGs were auxin biosynthesis and signal transduction, suggesting that these two pathways are important to tissue culture seedling growth and development (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ec). In this study, the increased expression of the ALDH gene may lead to elevated auxin levels, subsequently suppressing the growth of FLS-1. Auxin-responsive genes, including the Auxin/Indole-3-Acetic Acid (AUX/IAA) family, auxin response factor (ARF) family, SAUR and the auxin-responsive GH3 family, play critical roles in regulating plant growth (Luo et al. \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Among these, the SAUR family contains the highest number of members. Recent research has demonstrated that SAUR genes primarily regulate plant cell elongation and cell wall relaxation (Lv et al. \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e; Luan et al. \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The observed inhibition of FLS-1 tissue culture seedling growth in this study may be attributed to the downregulation of the SAUR homologous gene. The cytokinins (CKs) are known to regulate the biogenesis of chloroplasts, which are considered as one of the main groups of phytohormones as they, together with auxins, control cell division and, hence, influence the overall plant\\u0026rsquo;s architecture. The first step of CK biosynthesis is catalysed by IPT (Hluska et al. \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). ABA is a key phytohormone regulating diverse physiological processes and influencing plant growth and development by modulating the production of protective metabolites (Singh et al. 2023). Key ABA biosynthetic genes, including zeaxanthin epoxidase (ZEP), NCED and abscisic aldehyde oxidase (AAO3), have been identified, with NCED-catalyzed xanthoxin production recognized as the primary regulatory step in ABA biosynthesis (Ng et al. \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). ABA receptors, mainly comprising the PYR/PYL/RCAR protein family, undergo conformational changes upon binding ABA, forming receptor complexes that relieve PP2C-mediated inhibition of SnRK2, thereby activating SnRK2 through phosphorylation and initiating downstream ABA-responsive gene expression (Varshney et al. \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003e2021\\u003c/span\\u003e). In this study, changes in the expression levels of the ABA biosynthetic gene NCED, receptor gene PYL, and signaling negative regulator gene PP2C suggest their potential involvement in the growth of \\u003cem\\u003eForsythia suspensa\\u003c/em\\u003e tissue culture seedlings. Metabolomic analysis further identified an upregulation of abscisic aldehyde, an ABA precursor, indicating enhanced ABA biosynthesis (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003ee). Additionally, the downregulation of PP2C likely reduces its inhibitory effect on SnRK2, impairing SnRK2 phosphorylation and subsequently disrupting ABA signaling. Collectively, these findings suggest that altered ABA biosynthesis and signaling pathways may contribute to the growth inhibition observed in FLS-1 lines.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"504\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAdoMet\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eS-adenosylmethionine\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAAO3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAbscisic aldehyde oxidase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eA-ARR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eA-type arabidopsis response regulator\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eABA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAbscisic acid\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eACC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e1-aminocyclopropane-1-carboxylic acid\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eACO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e1-aminocyclopropane-1-carboxylic acid oxidase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eACS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e1-aminocyclopropane-1-carboxylic acid synthase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eALA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5-aminolevulinic acid\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eALDH\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAldehyde dehydrogenase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eARF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAuxin response factor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eARF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eAuxin response factor\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAUX/IAA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAuxin/Indole-3-Acetic Acid\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eB-ARR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eB-type arabidopsis response regulator\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCKs\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCytokinins\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCPS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eCopalyl diphosphate synthase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCRE1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCytokinin response 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eCTR1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eConstitutive Triple Response 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eDEGs\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eDifferentially expressed genes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eDEMs\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eDifferentially expressed metabolites\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eEBF1/2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eEIN3-binding F-box 1/2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eEF-1α\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eElongation Factor-1α\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eERF1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eEthylene Response Factor 1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eFDA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eFalse Discovery Rate\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eFPKM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eFragments Per Kilobase of exon model per Million mapped fragments\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eFLS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eForsythia suspensa\\u0026nbsp;\\u003c/em\\u003ewithlong style\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGAs\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGibberellins\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eGC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eGuanine-Cytosine\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eGH3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eGretchen Hagen3\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGene Ontology\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eIBA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eIndole-3-butyric Acid\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eIPT\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eIsopentenyl transferase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKAO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKaurenoic acid oxidase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKEGG\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKyoto Encyclopedia of Genes and Genomes\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKaurene oxidase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eKaurene synthase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLHCI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLight-harvesting chlorophyll protein complex I\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLHCII\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eLight-harvesting chlorophyll protein complex II\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eLUT5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eLutein deficient 5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eNCED\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e9-cis-epoxycarotenoid dioxygenase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOPLS-DA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eOrthogonal Partial Least Squares-Discriminant Analysis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePCA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePrincipal Component Analysis\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePP2C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eProtein phosphatase 2C\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePSI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePhotosystem I\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePSII\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003ePhotosystem II\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePYL\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003ePyrabactin resistance 1-like\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eqRT-PCR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eQuantitative\\u0026nbsp;Real-time polymerase chain reaction\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eRIN\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eRNA Integrity Number\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eSAMS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eS-adenosylmethionine Synthetase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eSAUR\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eSmall auxin upregulated RNA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eTCM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eTraditional Chinese Medicine\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eTDC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eTryptophan decarboxylase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eTEM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eTransmission Electron Microscopy\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eZEP\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003eZeaxanthin epoxidase\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6-BA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e6-benzylaminopurine\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\"\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was supported in part by grants from the Henan Science and Technology Research Project (252102110153)\\u0026nbsp;and the National Key Research and Development Program of China Project (2023YFD2201100).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eYWJ, HYX. and WXP. conceived the research project.ZYP, GJQ, LX, WXX, SX and ZXQ. were involved in the analysis of the data. ZYP. drafted the paper and HYX. revised it critically for intellectual content. All authors have read and approved the final manuscript. All authors agree to be accountable for all aspects of the work.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthical Approval and Consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;No human or animal subjects were involved in this research.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll authors consent to the publication of this manuscript in its current form\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of supporting data\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe sequence data that support the findings of this study are openly available in GenBank of NCBI at https://www.ncbi.nlm.nih.gov/, and the associated *SRA* numbers of the raw sequence data are from SRR27452189 to SRR27452200.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAshburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM et al (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25(1):25\\u0026ndash;29. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/75556\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/75556\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAdhikary D, Kulkarni M, El-Mezawy A, Mobini S, Elhiti M, Gjuric R et al (2021) Medical Cannabis and Industrial Hemp Tissue Culture: Present Status and Future Potential. Front Plant Sci 12:627240. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3389/fpls.2021.627240\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fpls.2021.627240\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCheng Q, Dong LD, Su T, Li TY, Gan ZR, Nan HY et al (2019) )CRISPR/Cas9-mediated targeted mutagenesis of GmLHY genes alters plant height and internode length in soybean. BMC Plant Biol 19(1):562. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/s12870-019-2145-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s12870-019-2145-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChu LL, Yan Z, Sheng XX, Liu HQ, Wang QY, Zeng RF et al (2023) Citrus ACC synthase CiACS4 regulates plant height by inhibiting gibberellin biosynthesis. Plant Physiol 192(3):1947\\u0026ndash;1968. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1093/plphys/kiad159\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/plphys/kiad159\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen SF, Zhou YQ, Chen YR, Gu J (2018) fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34(17):i884\\u0026ndash;i890. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1093/bioinformatics/bty560\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/bioinformatics/bty560\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eda Silva Ferreirada V, Sant'Anna C (2017) Impact of culture conditions on the chlorophyll content of microalgae for biotechnological applications. World J Microbiol Biotechnol 33(1):20. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s11274-016-2181-6\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s11274-016-2181-6\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eElias AA, Busov VB, Kosola KR, Ma C, Etherington E, Shevchenko O et al (2012) Green revolution trees: semidwarfism transgenes modify gibberellins, promote root growth, enhance morphological diversity, and reduce competitiveness in hybrid poplar. Plant Physiol 160(2):1130\\u0026ndash;1144. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1104/pp.112.200741\\u003c/span\\u003e\\u003cspan address=\\\"10.1104/pp.112.200741\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGao BY, Zhu HS, Liu ZH, He XH, Sun JH, LI YF et al (2024) Chemical Compositions of Lianqiao (Forsythia suspensa) Extracts and Their Potential Health Benefits. Pharmaceuticals (Basel) 7(6):740. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/ph17060740\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ph17060740\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHua Q (2009) Effect of water stress on maize yield during different growing stages (in Chinese). J Maize Sci 17(2):60\\u0026ndash;63. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://api.semanticscholar.org/CorpusID:111875327\\u003c/span\\u003e\\u003cspan address=\\\"https://api.semanticscholar.org/CorpusID:111875327\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHluska T, Hluskov\\u0026aacute; L, Emery RJN (2021) The Hulks and the Deadpools of the Cytokinin Universe: A Dual Strategy for Cytokinin Production, Translocation, and Signal Transduction. Biomolecules 11(2):209. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/biom11020209\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/biom11020209\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKulkov L, Arkhipov R, Abramova A, Vereshchagin M, Voronkov A, Khalilova V et al (2024) Long-term effects of silver nanoparticles and mineral nutrition components on the photosynthetic processes, chloroplast ultrastructure and productivity of Solanum lycopersicum plants. J Photochem Photobiol B 260:113038. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.jphotobiol.2024.113038\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.jphotobiol.2024.113038\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKuo CL, Agrawal DC, Chang HC, Chiu YT, Huang CP, Chen YL et al (2015) In vitro culture and production of syringin and rutin in Saussurea involucrata (Kar. et Kir.) - an endangered medicinal plant. Bot Stud 56(1):12. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/s40529-015-0092-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s40529-015-0092-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKhan S, Alvi AF, Saify S, Iqbal N, Khan NA (2024) The Ethylene Biosynthetic Enzymes, 1-Aminocyclopropane-1-Carboxylate (ACC) Synthase (ACS) and ACC Oxidase (ACO): The Less Explored Players in Abiotic Stress Tolerance. Biomolecules 14(1):90. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/biom14010090\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/biom14010090\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28(1):27\\u0026ndash;30. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1093/nar/28.1.27\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/nar/28.1.27\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12(4):357\\u0026ndash;360. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/nmeth.3317\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/nmeth.3317\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKong WY, Yu XW, Chen HY, Liu LL, Xiao YJ, Wang YL et al (2016) The catalytic subunit of magnesium-protoporphyrin IX monomethyl ester cyclase forms a chloroplast complex to regulate chlorophyll biosynthesis in rice. Plant Mol Biol 92(1\\u0026ndash;2):177\\u0026ndash;191. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s11103-016-0513-4\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s11103-016-0513-4\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLalitha S (2000) Primer Premier 5. Biotech Softw Internet Rep 1(6):270\\u0026ndash;272. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1089/152791600459894\\u003c/span\\u003e\\u003cspan address=\\\"10.1089/152791600459894\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLu WY, Bennett BD, Rabinowitz JD (2008) Analytical strategies for LC-MS-based targeted metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci 871(2):236\\u0026ndash;242. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.jchromb.2008.04.031\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.jchromb.2008.04.031\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/1471-2105-12-323\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/1471-2105-12-323\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLove MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/s13059-014-0550-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s13059-014-0550-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLv WZ, He X, Guo HJ, Lan HB, Jiao YQ, Li L et al (2022) Genome-Wide Identification of TaSAUR Gene Family Members in Hexaploid Wheat and Functional Characterization of TaSAUR66-5B in Improving Nitrogen Use Efficiency. Int J Mol Sci 23(14):7574. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/ijms23147574\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ijms23147574\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, Shi LC, Pei NC, Cushman SA, Si YT (2021) Transcriptomic responses to drought stress among natural populations provide insights into local adaptation of weeping forsythia. BMC Plant Biol 21(1):273. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/s12870-021-03075-6\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s12870-021-03075-6\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLiu LD, Sun Y, Wen CX, Jiang T, Tian W, Xie XL et al (2022) Metabolome analysis of genus forsythia related constituents in Forsythia suspensa leaves and fruits using UPLC-ESI-QQQ-MS/MS technique. PLoS ONE 17(6):e0269915. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1371/journal.pone.0269915\\u003c/span\\u003e\\u003cspan address=\\\"10.1371/journal.pone.0269915\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi W, Tang S, Zhang S, Shan JG, Tang CJ, Chen QN et al (2016) Gene mapping and functional analysis of the novel leaf color gene SiYGL1 in foxtail millet [Setaria italica (L.) P. Beauv]. Physiol Plant 157(1):24\\u0026ndash;37. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1111/ppl.12405\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/ppl.12405\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, Wang F, Pei NC, Li Q, Liu HL, Yuan WJ et al (2023) The updated weeping forsythia genome reveals the genomic basis for the evolution and the forsythin and forsythoside A biosynthesis. Hortic Plant J 9(6):1149\\u0026ndash;1161. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.sciopen.com/article/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.sciopen.com/article/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.hpj.2022.09.004\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.hpj.2022.09.004\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi QX, Xue XD (2024) Study on Synergistic Mechanism Between Forsythia Cultivation and Rural Development. J Life Sci Agric 1:68\\u0026ndash;72. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.62517/jlsa.202407212\\u003c/span\\u003e\\u003cspan address=\\\"10.62517/jlsa.202407212\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLuan J, Xin M, Qin ZW (2023) Genome-Wide Identification and Functional Analysis of the Roles of SAUR Gene Family Members in the Promotion of Cucumber Root Expansion. Int J Mol Sci 24(6):5940. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/ijms24065940\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ijms24065940\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee BD, Yim Y, Ca\\u0026ntilde;ibano E, Kim SH, Garc\\u0026iacute;a-Le\\u0026oacute;n M, Rubio V et al (2022) CONSTITUTIVE PHOTOMORPHOGENIC 1 promotes seed germination by destabilizing RGA-LIKE 2 in Arabidopsis. Plant Physiol 189(3):1662\\u0026ndash;1676. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1093/plphys/kiac060\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/plphys/kiac060\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, Zhao LM, Guo CM, Tang M, Lian WL, Chen SY et al (2024) OsNAC103, an NAC transcription factor negatively regulates plant height in rice. Planta 259(2):35. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00425-023-04309-7\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00425-023-04309-7\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLuo J, Zhou JJ, Zhang JZ (2018) Aux/IAA Gene Family in Plants: Molecular Structure, Regulation, and Function. Int J Mol Sci 19(1):259. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/ijms19010259\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ijms19010259\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMochizuki N, Brusslan JA, Larkin R, Nagatani A, Chory J (2001) Arabidopsis genomes uncoupled 5 (GUN5) mutant reveals the involvement of Mg-chelatase H subunit in plastid-to-nucleus signal transduction. Proc Natl Acad Sci U S A 98(4):2053\\u0026ndash;2058. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1073/pnas.98.4.2053\\u003c/span\\u003e\\u003cspan address=\\\"10.1073/pnas.98.4.2053\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMircea DM, Calone R, Shakya R, Zuzunaga-Rosas J, Sestras RE, Boscaiu M et al (2023) Evaluation of Drought Responses in Two Tropaeolum Species Used in Landscaping through Morphological and Biochemical Markers. Life 13(4):960. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/life13040960\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/life13040960\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNiazian M (2019) Application of genetics and biotechnology for improving medicinal plants. Planta 249(4):953\\u0026ndash;973. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00425-019-03099-1\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00425-019-03099-1\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNg LM, Melcher K, Teh BT, Xu HE (2014) Abscisic acid perception and signaling: structural mechanisms and applications. Acta Pharmacol Sin 35(5):567\\u0026ndash;584. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/aps.2014.5\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/aps.2014.5\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNagata N, Tanaka R, Satoh S, Tanaka A (2005) Identification of a vinyl reductase gene for chlorophyll synthesis in Arabidopsis thaliana and implications for the evolution of Prochlorococcus species. Plant Cell 17(1):233\\u0026ndash;240. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1105/tpc.104.027276\\u003c/span\\u003e\\u003cspan address=\\\"10.1105/tpc.104.027276\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePark EJ, Lee WY, Kurepin LV, Zhang RC, Janzen L, Pharis RP (2015) Plant hormone-assisted early family selection in Pinus densiflora via a retrospective approach. Tree Physiol 35(1):86\\u0026ndash;94. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1093/treephys/tpu102\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/treephys/tpu102\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL (2015) StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol 33(3):290\\u0026ndash;295. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/nbt.3122\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/nbt.3122\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eQi XP, Ogden EL, Die JV, Ehlenfeldt MK, Polashock JJ, Darwish O et al (2019) Transcriptome analysis identifies genes related to the waxy coating on blueberry fruit in two northern-adapted rabbiteye breeding populations. BMC Plant Biol 19(1):460. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/s12870-019-2073-7\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/s12870-019-2073-7\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSingh A, Roychoudhury A (2023) Abscisic acid in plants under abiotic stress: crosstalk with major phytohormones. Plant Cell Rep 42(6):961\\u0026ndash;974. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00299-023-03013-w\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00299-023-03013-w\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTeixeira da Silva JA, Cardoso JC, Dobr\\u0026aacute;nszki J, Zeng SJ (2015) Dendrobium micropropagation: a review. Plant Cell Rep 34(5):671\\u0026ndash;704. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s00299-015-1754-4\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s00299-015-1754-4\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVarshney V, Majee M (2021) JA Shakes Hands with ABA to Delay Seed Germination. Trends Plant Sci 26(8):764\\u0026ndash;766. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.tplants.2021.05.002\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.tplants.2021.05.002\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVan de Poel B, Van Der Straeten D (2014) 1-aminocyclopropane-1-carboxylic acid (ACC) in plants: more than just the precursor of ethylene! Front Plant Sci 5:640. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3389/fpls.2014.00640\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fpls.2014.00640\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWang YD, Huang X, Huang XM, Su W, Hao YW, Liu HC et al (2022) BcSOC1 Promotes Bolting and Stem Elongation in Flowering Chinese Cabbage. Int J Mol Sci 23(7):3459. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/ijms23073459\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/ijms23073459\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWu ZM, Zhang X, He B, Diao LP, Sheng SL, Wang JL et al (2007) A chlorophyll-deficient rice mutant with impaired chlorophyllide esterification in chlorophyll biosynthesis. Plant Physiol 145(1):29\\u0026ndash;40. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1104/pp.107.100321\\u003c/span\\u003e\\u003cspan address=\\\"10.1104/pp.107.100321\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eXing N, Li XQ, Wu SH, Wang ZW (2024) Transcriptome and Metabolome Reveal Key Genes from the Plant Hormone Signal Transduction Pathway Regulating Plant Height and Leaf Size in Capsicum baccatum. Cells 13(10):827. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3390/cells13100827\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/cells13100827\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYuan WJ, He ZY, Zhang SP, Zheng YP, Zhang XQ, He SQ et al (2023) Comparative transcriptomics provides insights into the pathogenic immune response of brown leaf spots in weeping forsythia. Tree Physiol 43(9):1641\\u0026ndash;1652. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1093/treephys/tpad060\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/treephys/tpad060\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang YQ, Berman A, Shani E (2023) Plant Hormone Transport and Localization: Signaling Molecules on the Move. Annu Rev Plant Biol 74:453\\u0026ndash;479. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1146/annurev-arplant-070722-015329\\u003c/span\\u003e\\u003cspan address=\\\"10.1146/annurev-arplant-070722-015329\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhu JC, Cai DF, Wang JP, Cao JH, Wen YC, He JP et al (2021) Physiological and anatomical changes in two rapeseed (Brassica napus L.) genotypes under drought stress conditions. Oil Crop Sci 6(02):97\\u0026ndash;104. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.ocsci.2016-0153\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.ocsci.2016-0153\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhou MY, Huo JH, Wang CR, Wang WM (2022) UPLC/Q-TOF MS Screening and Identification of Antibacterial Compounds in Forsythia suspensa (Thunb.) Vahl Leaves. Front Pharmacol 12:704260. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.3389/fphar.2021.704260\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fphar.2021.704260\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhao SL, Long WH, Wang YH, Liu LL, Wang YL, Niu M et al (2016) rice White-stripe leaf3 (wsl3) mutant lacking an HD domain-containing protein affects chlorophyll biosynthesis and chloroplast development. J Plant Biol 59:282\\u0026ndash;292. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s12374-016-0459-8\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s12374-016-0459-8\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhang CC, Wang S, Wang YF, Wang HY, Qin M, Dai XY et al (2023) plication of tissue culture technology of medicinal plants in sustainable development of Chinese medicinal resources. Zhongguo Zhong Yao Za Zhi 48(5):1186\\u0026ndash;1193. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.19540/j.cnki.cjcmm.20221017.104\\u003c/span\\u003e\\u003cspan address=\\\"10.19540/j.cnki.cjcmm.20221017.104\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZhou YS, Zhang T, Wang XC, Wu WQ, Xing JJ, Li ZL et al (2023) A maize epimerase modulates cell wall synthesis and glycosylation during stomatal morphogenesis. Nat Commun 14(1):4384. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1038/s41467-023-40013-6\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/s41467-023-40013-6\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Weeping forsythia, Tissue culture, Metabolomics, Transcriptome\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6833324/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6833324/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eWeeping forsythia (\\u003cem\\u003eForsythia suspensa\\u003c/em\\u003e) is an important medicinal and ornamental plant. To explore genotype-dependent growth variation under tissue culture, we compared two long-style genotypes, FLS-1 and FLS-2. FLS-1 exhibited reduced plant height, branching, internode length, and chlorophyll content, along with chlorosis and impaired chloroplast ultrastructure. Transcriptomic analysis identified 2,059 and 3,482 DEGs between FLS-1 and FLS-2 on days 25 and 35, respectively, with 46 DEGs related to photosynthesis. Metabolomic profiling revealed 563 DEMs, with 15 KEGG pathways significantly enriched. These results elucidate key molecular differences affecting growth and photosynthesis between \\u003cem\\u003eF. suspensa\\u003c/em\\u003e genotypes in vitro.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Integrated Morphological, Transcriptomic, and Metabolomic Profiling Reveals Differential Development Mechanisms in Two Weeping Forsythia Genotypes during Tissue Culture\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-17 14:24:57\",\"doi\":\"10.21203/rs.3.rs-6833324/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"f5f09de4-c15b-4ea1-b26b-255053fb2f59\",\"owner\":[],\"postedDate\":\"June 17th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-08-08T15:55:36+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-06-17 14:24:57\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6833324\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6833324\",\"identity\":\"rs-6833324\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}