Transcriptome and hormonal profiles of Polygonatum kingianum under low temperature stress

Transcriptome and hormonal profiles of Polygonatum kingianum under low temperature stress | 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 data-descriptor Transcriptome and hormonal profiles of Polygonatum kingianum under low temperature stress Xiheng Wan, You Lu, Jia Chen, Yingsi Gao, Furui Sang, Xiaoye Zhang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8322139/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 Polygonatum kingianum is a significant medicinal and edible plant, with low temperatures serving as a critical environmental factor that restricts its distribution and growth. In this study, the freezing tolerance of P. kingianum was enhanced by pre-treating seedlings at 4°C for 3 days. The differential expression of transcripts and hormones during the freezing treatment and subsequent recovery process was compared between control and cold-acclimated samples. A total of 93 differential hormones were identified among these samples along with 372.63 Gb of transcriptome data. This study provides insights into potential hormones and candidate genes involved in the freezing resistance of P. kingianum , facilitating strategies to cope with extreme temperatures during its cultivation and the selection of freezing-tolerant varieties. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background and Summary Polygonatum kingianum Coll.et Hemsl is a perennial herb belonging to the Liliaceae family, commonly referred to as 'Xianrenfan'. This plant is well-known for its medicinal and edible properties, playing a significant role as both food and medicine ( http://www.nhc.gov.cn/ ). P. kingianum is primarily distributed across the provinces of Yunnan, Guizhou, and Sichuan in China, with a cultivation history extending over 600 years 1 . The planting area of P. kingianum in Yunnan Province has exceeded 100,000 acres, yielding 11,512 tons and generating an output value of 659.68 million RMB 2 . During the growth period of P. kingianum , extreme temperature events, such as late spring cold snaps and early frosts can severely compromise the yield and quality of the plant (Fig. 1 ). However, little is known about the response of P. kingianum to extreme low temperatures. Treating plants with low nonfreezing temperatures, a process known as cold acclimation, is an effective method for enhancing the freezing tolerance of plants 3 . During this process, plants undergo a reorganization of metabolites through adjustments in their transcriptomes. For instance, the accumulation of phenolic compounds 4 , dehydrins 5 , proline and soluble sugars 6 , anthocyanins and phenylpropanoids 7 during cold acclimation may protect plants from freezing damage. Plant hormones play a crucial role in plant responses to low temperatures, and alterations in hormone metabolism are vital strategies for coping with cold stress 8 , 9 . Abscisic acid (ABA) is the most important plant hormone responsible for cold acclimation. Cold acclimation induces a rapid increase in ABA levels, which subsequently regulates the expression of downstream freezing resistance genes, such as COR and WCS120 10,11 . Additionally, ABA activates GA2-oxidase (GA2ox), leading to the degradation of active gibberellin acid (GA), thereby inhibiting plant growth and reducing energy consumption 11 . The ABA induced by cold acclimation also helps plants minimize excessive water loss under cold stress conditions by inducing stomatal closure 12 . Furthermore, cold acclimation can cause a transient decrease in indole-3-acetic acid (IAA) and cytokinin (CK) levels, which inhibits cell division and elongation, thus reducing metabolic consumption 10 . Jasmonic acid (JA) exhibits stage-specific changes during cold acclimation. For example, in wheat, JA levels decrease at extremely low temperatures (-25°C), but its signaling pathway indirectly enhances resistance by regulating CBF expression 13 . Additionally, the accumulation of salicylic acid (SA) has also been shown to improve cold resistance in plants 14 . Research on enhancing plant cold tolerance through cold acclimation has primarily focused on crops 15 – 19 , while little is known about the impact of cold acclimation on the freezing tolerance of medicinal herbs with perennial roots. This study investigates the significant impact of cold acclimation on the freezing resistance of P. kingianum seedlings through targeted hormone metabolome and transcriptome analyses. After treating seedlings at -6°C for 3 hours, the leaves of the plants in the cold acclimation group (seedlings pre-treated at 4°C for 3 days) exhibited moderate damage and were able to recover after 3 days recovery treatment, while the control group (un-cold acclimated seedlings) experienced severe injuries and failed to recover (Fig. 2 ). Among the 109 hormone molecules tested, 98 were detected. There were 43, 34, 65, 39 and 69 differentially expressed hormones between the control and cold acclimation groups at the stages of non-freezing treatment, freezing, thawing, and 1 and 3 days of recovery, respectively (Table. 1). The total content of ABA, auxin, CK, aminocyclopropane-1-carboxylic acid (ACC), gibberellins, JA, and salicylic acid (SA) did not show significant changes after cold acclimation and freezing treatment (Table 2 ). During the thawing process, most hormones in the control group, including ABA, auxin, CK, strigolactones, JA, and SA, increased significantly, while the level of ACC decreased (Table 2 ). Both the control and cold acclimated groups exhibited similar trends in hormone changes following freezing treatment and during the subsequent recovery process; however, the hormonal fluctuations in the control group were more pronounced than those in the cold acclimation group (Table.2). Table 1 Statistics on the number of differential metabolites between the cold acclimation and the control at different stages. Total Up Down CA-C_VS_CK-C 43 17 26 CA-F_VS_CK-F 34 20 14 CA-T_VS_CK-T 65 14 51 CA-R1_VS_CK-R1 39 23 16 CA-R3_VS_CK-R3 69 12 57 Table 2 The content of plant hormones in P. kingianum . Treatment ABA CK SL GA (ng/g) C CK 59.05 ± 21.53 c 9.9 ± 1.09 c 11.44 ± 5.61 b 50.5 ± 10.4 b CA 28.08 ± 8.52 a 9.54 ± 1.56 a 8.96 ± 8.79 a 33.86 ± 4.91 a F CK 47.6 ± 0.52 c 21.56 ± 0.34 c 0.00 ± 0.00 b 34.82 ± 1.34 b CA 22.63 ± 3.69 a 7.69 ± 0.41 a 0.32 ± 0.13 a 35.23 ± 10.95 a T CK 267.8 ± 125.31 ab* 214.1 ± 41.62 a* 46.18 ± 41.74 ab 81.11 ± 0.92 b CA 61.52 ± 19.48 a 6.55 ± 0.74 a 7.58 ± 3.68 a 36.34 ± 3.95 a R1 CK 332.54 ± 11.78 a 90.49 ± 1.45 b 104.69 ± 9.27 a* 107.99 ± 6.85 b CA 131.07 ± 104.58 a 76.45 ± 70.08 a 10.76 ± 4.18a 75.32 ± 48.22 a R3 CK 100.52 ± 31.62 bc 62.3 ± 19.83 bc 24.33 ± 21.15 b 530.08 ± 231.5 a* CA 20.53 ± 9.01 a 10.74 ± 0.74 a 4.74 ± 4.44 a 38.84 ± 10.37 a Treatment JA Auxin ACC SA (mg/g) C CK 0.16 ± 0.03 a 37.36 ± 25.24 ab 18.24 ± 3.04 a 22.68 ± 2.61 c CA 0.09 ± 0.05 a 12.05 ± 3.99 b 20.77 ± 1.9 a 23.89 ± 15.15 a F CK 0.33 ± 0.03 a 8.84 ± 0.43 b 21.56 ± 1.12 a 22.92 ± 0.37 c CA 0.05 ± 0.04 a 19.66 ± 4.26 b 22.53 ± 0.67 a 25.52 ± 2.45 a T CK 1.57 ± 1.04 a* 75.39 ± 4.37 a 9.07 ± 1.29 b* 37.20 ± 5.16 b* CA 0.16 ± 0.03 a 21.79 ± 4.49 b 23.42 ± 2.00 a 21.08 ± 4.51 a R1 CK 0.68 ± 0.04 a 33.75 ± 1.70 ab 10.98 ± 0.46 b 45.46 ± 0.54 ab CA 0.60 ± 0.47 a 57.48 ± 18.71 a 16.97 ± 5.74 a 32.77 ± 11.41 a R3 CK 1.02 ± 0.50 a 49.20 ± 15.45 ab 12.00 ± 2.09 b 48.49 ± 4.06 a* CA 0.12 ± 0.03 a 30.74 ± 2.64 ab 19.91 ± 1.51 a 31.07 ± 0.92 a Table 3 Statistics on the number of differential genes between the cold acclimation and the control at different stages. Total Up Down CA-C_VS_CK-C 9846 5231 4615 CA-F_VS_CK-F 31823 12349 19474 CA-T_VS_CK-T 54415 11831 42584 CA-R1_VS_CK-R1 3752 1519 2233 CA-R3_VS_CK-R3 17719 7202 10517 RNA sequencing (RNA-seq) generated a total of 372.63 Gb of transcriptomic data. Applying screening criteria of |log2Fold Change| ≥ 1 and FDR < 0.05, 9846, 31823, 54415, 3752, and 17719 differentially expressed genes (DEGs) were identified at the five stages of the cold acclimation group compared to the control group (Table.3). KEGG enrichment analysis indicated that DEGs induced by cold acclimation were predominantly enriched in metabolic pathways, biosynthesis of secondary metabolites, and plant hormone signal transduction pathways, with 1153, 686, and 234 significantly altered genes, respectively (Fig. 3 ). Notably, the high expression levels of PP2C , PYL , ABF , JAZ , GRE , PIF , ETR , and EIN3 may be play crucial roles in cold acclimation-induced hormone metabolism, contributing to freezing tolerance. The majority of the most significantly changed genes in the control group were associated with the thawing process, while the most significantly altered genes in the cold acclimation group were observed during the recovery phase at one day post-freezing, indicating a recovery from freezing stress (Fig. 4 ). This study provides a comprehensive transcriptomic and hormonal profile for the freezing response of P. kingianum , establishing a foundation for understanding cold acclimation induced freezing tolerance in medicinal herbs with perennial roots, and may assist in the selection of cultivars with enhanced freezing tolerance. Methods Plant materials and treatment. Seeds of Polygonatum kingianum were collected from Honghe, Yunnan Province, China (23°55'32"N, 102°24'33"E), at an altitude of 2115.3 m. The seeds were germinated in a soil mixture composed of humus soil and clay in a ratio of 4:1. For cold acclimation, one-year-old seedlings were subjected to dark conditions at 4°C for 3 days. Following this acclimation, all seedlings were exposed to -6°C for 3 hours. After 1 day of exposure to 4°C, the seedlings were placed in a growth chamber under normal growth conditions (12/12 h light/dark cycle at 22°C ) for recovery periods of 1 and 3 days. Biological samples were collected at each stage of treatment: non-freezing treated samples (C), freezing (F), thawing (T), and recovery periods of 1 day (R1) and 3 day (R3). Samples intended of transcriptome analysis and plant hormone detection were rapidly frozen in liquid nitrogen and stored at -80°C for metabolomic and transcriptomic analysis. Plant hormone metabolome analyses and data processing. The sample was ground using a grinder set at 30 Hz for 1 minute until it transformed into a powder. An aliquot of 50 mg of the ground sample was taken, and 10 µL of an internal standard mixed solution at a concentration of 100 ng/mL was added, followed by 1 mL of a methanol/water/formic acid extractant (15:4:1, v/v/v). The mixture was thoroughly mixed and vortexed at 4°C for 10 minutes, then centrifuged at 12,000 rpm for 5 minutes. The supernatant was transferred to a new centrifuge tube for concentration. The sample was reconstituted with 100 µL of an 80% methanol/aqueous solution, filtered through a 0.22 µm filter membrane, and placed in an injection flask for LC-MS/MS analysis. The analysis was performed using the UPLC-ESI-MS/MS system 20 , 21 with a Waters ACQUITY UPLC HSS T3 C18 column. The mobile phase comprised Phase A (ultrapure water containing 0.04% acetic acid) and Phase B (acetonitrile containing 0.04% acetic acid), employing a gradient elution procedure: At 0 min, the A/B ratio was 95:5 (v/v); at 1.0 min, it remained 95:5 (v/v); at 8.0 min, it shifted to 5:95 (v/v); at 9.0 min, it continued at 5:95 (v/v); at 9.1 min, it reverted to 95:5 (v/v); and at 12.0 min, it remained at 95:5 (v/v). The flow rate was set at 0.35 mL/min, and the column oven temperature was maintained at 40°C. An injection volume of 2 µL was utilized. At 550°C, voltages of + 5500 V and − 4500 V were applied to the sample liquid via the electrospray method to generate aerosols, which were dispersed in a 35 psi gas curtain. In the Q-Trap 6500 + mass spectrometer, each ion pair was scanned and detected based on the optimized Declustering Potential (DP) and Collision Energy (CE). The precursor ions of the target substance were screened using triple quadrupole mass spectrometry, and following induced ionization, the characteristic fragment ions were filtered. Ultimately, the obtained mass spectrometry data were integrated with chromatographic peaks and quantitatively analyzed through standard curves. To calculate the content of the substance in the actual samples, substitute the ratio of the integral peak areas of all detected samples into the standard curve linear equation. The hormone content in the sample (ng/g) can be determined using the following formula: concentration value from standard curve(ng/mL) × volume of solution for redissolution (µL)/ mass of sample weighed (g). Plant transcriptomic sequencing and data processing. A total of 1 µg of RNA per sample was utilized as the input material for RNA sample preparations. Sequencing libraries were generated using the NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA), adhering to the manufacturer's recommendations, and index codes were incorporated to attribute sequences to each sample. To select cDNA fragments preferentially ranging from 250 to 300 bp in length, the library fragments were purified using the AMPure XP system (Beckman Coulter, Beverly, USA). Subsequently, 3 µL of USER Enzyme (NEB, USA) was applied to the size-selected, adaptor-ligated cDNA at 37°C for 15 minutes, followed by a 5-minute incubation at 95°C before PCR. PCR was then conducted using Phusion High-Fidelity DNA polymerase, Universal PCR primers, and Index (X) Primer. Finally, the PCR products were purified using the AMPure XP system, and library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using the TruSeq PE Cluster Kit v3-cBot-HS (Illumina), following the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina platform, resulting in the generation of 150 bp paired-end reads. Data analysis. The raw data were analyzed using Excel 2019. A one-way ANOVA was conducted using SPSS Statistics 22, with significance determined through Fisher’s Least Significant Difference (LSD) method. Additionally, a visual analysis of the heat map was performed using GraphPad Prism 9.5 software. Data Records The original metabolomic data of Polygonatum kingianum Collett & Hemsl. leaves, collected at various stages of low-temperature treatment, can be accessed through the China National Center for Bioinformation (CNCB) of National Genomics Data Center (NGDC) ( https://ngdc.cncb.ac.cn/omix : accession no. OMIX011073) 22 . Additionally, the raw transcriptome data have been submitted to the Genome Sequence Archive (GSA) of National Genomics Data Center (NGDC) under the accession number CRA026628 23 . Technical Validation In the analysis process utilizing a mixed solution as a quality control (QC) sample, a QC sample is typically inserted after every ten detection and analysis samples. By superimposing the total ion chromatogram (TIC) obtained from the mass spectrometry analysis of the same QC sample, one can evaluate the instrument's stability throughout the detection period, which reflects its technical repeatability (Fig. 5 A). The high stability of the instrument is critical as it guarantees the repeatability and reliability of the data. Mass spectrometry data were processed using MultiQuant 3.0.3 software, where the retention time and peak shape information of reference standards were employed to conduct integral correction on the chromatographic peaks detected in various samples of the analyte, thereby ensuring the accuracy of qualitative quantification (Fig. 5 B). Declarations Competing Interest The authors declare that they have no any competing interests that could have influenced the work reported in this paper. Funding This work was supported by the National Natural Science Foundation of China (82360751), High-Level Talents Project of Yunnan Province (YNWR-QNBJ-2020-257, XDYC-QNRC-2022-0277). Author Contribution Xiheng Wan: Methodology, Investigation, Data curation, Writing - original draft. Jia Chen: Methodology, Data curation, Investigation. You Lu: Methodology, Data curation. Yingsi Gao: Data analysis. Furui Sang: Investigation. Xiaoye Zhang: Data analysis. Menxue Du: material acquisition. Junzhe Zhou: material acquisition. Yanan Li: material acquisition. Guowei Zheng: Supervision, Resources, Writing-review and editing, Project administration. All authros reviewed the manuscript. Acknowledgement This work was supported by the National Natural Science Foundation of China (82360751),High-Level Talents Project of Yunnan Province (YNWR-QNBJ-2020-257, XDYC-QNRC-2022-0277). We thank Wuhan Metware Biotechnology Co., Ltd., for its technical support in the metabolome and transcriptome analysis. Data Availability The original metabolomic data of *Polygonatum kingianum* Collett & Hemsl. leaves, collected at various stages of low-temperature treatment, can be accessed through the China National Center for Bioinformation (CNCB) of National Genomics Data Center (NGDC) (https://ngdc.cncb.ac.cn/omix: accession no. OMIX011073) 22 . Additionally, the raw transcriptome data have been submitted to the Genome Sequence Archive (GSA) of National Genomics Data Center (NGDC) under the accession number CRA026628 23 . Code Availability The software version and parameters utilized are detailed in the Methods section. This study did not employ any custom code for dataset curation or validation. References Shi Y. et al. Huangjing—From medicine to healthy food and diet. Food Frontiers , 4, 1068–1090 (2023). yu X. How to solve the supply-demand contradiction of Dianhuang Jing. Rich World , 10, 43 (2021). Browse J.&Xin Z. Temperature sensing and cold acclimation. Current Opinion in Plant Biology , 4, 241–246 (2001). Zanotto S. et al. Biochemical changes after cold acclimation in Nordic red clover ( Trifolium pratense L.) accessions with contrasting levels of freezing tolerance. Physiologia Plantarum , 175, e13953 (2023). Peng Y. et al. 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BMC Genomics , 20, 624 (2019). Howell G. S.&Weiser C. J. The environmental control of cold acclimation in apple. Plant Physiology , 45, 390–394 (1970). Šimura J. et al. Plant Hormonomics: Multiple Phytohormone Profiling by Targeted Metabolomics. Plant Physiology , 177, 476–489 (2018). Cai B.-D. et al. Rapid and high-throughput determination of endogenous cytokinins in Oryza sativa by bare Fe3O4 nanoparticles-based magnetic solid-phase extraction. Journal of Chromatography A , 1340, 146–150 (2014). NGDC histology raw data archives (OMIX011073) https://ngdc.cncb.ac.cn/omix/release/OMIX011073 . (2025) NGDC histology raw data archives (CRA026628). https://ngdc.cncb.ac.cn/gsa/browse/CRA026628 . (2025) Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8322139","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"data-descriptor","associatedPublications":[],"authors":[{"id":636697388,"identity":"96a56465-c93b-42aa-adb0-3ed81afe7d14","order_by":0,"name":"Xiheng Wan","email":"","orcid":"","institution":"Yunnan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xiheng","middleName":"","lastName":"Wan","suffix":""},{"id":636697389,"identity":"523adf44-620f-4245-867b-3120ee06b4e4","order_by":1,"name":"You Lu","email":"","orcid":"","institution":"Yunnan Agricultural 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(B).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8322139/v1/b6bb6db6b08088ccc9bf5185.jpg"},{"id":109080480,"identity":"31bb4c77-c222-4c87-8ae3-400adef5b67a","added_by":"auto","created_at":"2026-05-12 11:26:40","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":140020,"visible":true,"origin":"","legend":"\u003cp\u003ePhenotypes of \u003cem\u003eP. kingianum\u003c/em\u003e in control and cold acclimation groups after freeing treatment and thereafter recovery process.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8322139/v1/a8775764f8a77305ddb3410f.jpg"},{"id":109080481,"identity":"874c3386-a716-4843-8df9-565a8aa909d4","added_by":"auto","created_at":"2026-05-12 11:26:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":109457,"visible":true,"origin":"","legend":"\u003cp\u003eThe top 50 KEGG enriched terms of DEGs between control and cold acclimated \u003cem\u003eP. kingianum\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8322139/v1/5f68099124ffaee091dd251f.jpg"},{"id":109080726,"identity":"82cf92df-f975-4291-a0b6-cb8cf36522d7","added_by":"auto","created_at":"2026-05-12 11:27:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5448321,"visible":true,"origin":"","legend":"\u003cp\u003eK-means plot with top 9 clusters of control (A) and cold acclimation (B) groups during freezing treatment.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8322139/v1/4243dedbc4b8871cc1d3c683.png"},{"id":109080321,"identity":"cccf6e54-b9b8-4026-ad47-0df03499c2d0","added_by":"auto","created_at":"2026-05-12 11:26:07","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":13777375,"visible":true,"origin":"","legend":"\u003cp\u003eThe total ion chromatogram (A) and chromatographic peak integration calibration plot (B) of the samples.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8322139/v1/2c7897333e3ca5ab40f208b4.jpg"},{"id":109082696,"identity":"9a92a783-4101-4a8c-a11f-9d7ace95756f","added_by":"auto","created_at":"2026-05-12 12:42:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":19353978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8322139/v1/27e8ae9d-b86f-4bac-af55-c61bbcb7e488.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transcriptome and hormonal profiles of Polygonatum kingianum under low temperature stress","fulltext":[{"header":"Background and Summary","content":"\u003cp\u003e \u003cem\u003ePolygonatum kingianum\u003c/em\u003e Coll.et Hemsl is a perennial herb belonging to the Liliaceae family, commonly referred to as 'Xianrenfan'. This plant is well-known for its medicinal and edible properties, playing a significant role as both food and medicine (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.nhc.gov.cn/\u003c/span\u003e\u003cspan address=\"http://www.nhc.gov.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). \u003cem\u003eP. kingianum\u003c/em\u003e is primarily distributed across the provinces of Yunnan, Guizhou, and Sichuan in China, with a cultivation history extending over 600 years\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The planting area of \u003cem\u003eP. kingianum\u003c/em\u003e in Yunnan Province has exceeded 100,000 acres, yielding 11,512 tons and generating an output value of 659.68\u0026nbsp;million RMB\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. During the growth period of \u003cem\u003eP. kingianum\u003c/em\u003e, extreme temperature events, such as late spring cold snaps and early frosts can severely compromise the yield and quality of the plant (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, little is known about the response of \u003cem\u003eP. kingianum\u003c/em\u003e to extreme low temperatures.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTreating plants with low nonfreezing temperatures, a process known as cold acclimation, is an effective method for enhancing the freezing tolerance of plants\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. During this process, plants undergo a reorganization of metabolites through adjustments in their transcriptomes. For instance, the accumulation of phenolic compounds\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, dehydrins\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, proline and soluble sugars\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, anthocyanins and phenylpropanoids\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e during cold acclimation may protect plants from freezing damage. Plant hormones play a crucial role in plant responses to low temperatures, and alterations in hormone metabolism are vital strategies for coping with cold stress\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Abscisic acid (ABA) is the most important plant hormone responsible for cold acclimation. Cold acclimation induces a rapid increase in ABA levels, which subsequently regulates the expression of downstream freezing resistance genes, such as \u003cem\u003eCOR\u003c/em\u003e and \u003cem\u003eWCS120\u003c/em\u003e\u003csup\u003e10,11\u003c/sup\u003e. Additionally, ABA activates GA2-oxidase (GA2ox), leading to the degradation of active gibberellin acid (GA), thereby inhibiting plant growth and reducing energy consumption\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The ABA induced by cold acclimation also helps plants minimize excessive water loss under cold stress conditions by inducing stomatal closure\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Furthermore, cold acclimation can cause a transient decrease in indole-3-acetic acid (IAA) and cytokinin (CK) levels, which inhibits cell division and elongation, thus reducing metabolic consumption\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Jasmonic acid (JA) exhibits stage-specific changes during cold acclimation. For example, in wheat, JA levels decrease at extremely low temperatures (-25\u0026deg;C), but its signaling pathway indirectly enhances resistance by regulating CBF expression\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Additionally, the accumulation of salicylic acid (SA) has also been shown to improve cold resistance in plants\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Research on enhancing plant cold tolerance through cold acclimation has primarily focused on crops\u003csup\u003e\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, while little is known about the impact of cold acclimation on the freezing tolerance of medicinal herbs with perennial roots.\u003c/p\u003e \u003cp\u003eThis study investigates the significant impact of cold acclimation on the freezing resistance of \u003cem\u003eP. kingianum\u003c/em\u003e seedlings through targeted hormone metabolome and transcriptome analyses. After treating seedlings at -6\u0026deg;C for 3 hours, the leaves of the plants in the cold acclimation group (seedlings pre-treated at 4\u0026deg;C for 3 days) exhibited moderate damage and were able to recover after 3 days recovery treatment, while the control group (un-cold acclimated seedlings) experienced severe injuries and failed to recover (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among the 109 hormone molecules tested, 98 were detected. There were 43, 34, 65, 39 and 69 differentially expressed hormones between the control and cold acclimation groups at the stages of non-freezing treatment, freezing, thawing, and 1 and 3 days of recovery, respectively (Table. 1). The total content of ABA, auxin, CK, aminocyclopropane-1-carboxylic acid (ACC), gibberellins, JA, and salicylic acid (SA) did not show significant changes after cold acclimation and freezing treatment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). During the thawing process, most hormones in the control group, including ABA, auxin, CK, strigolactones, JA, and SA, increased significantly, while the level of ACC decreased (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Both the control and cold acclimated groups exhibited similar trends in hormone changes following freezing treatment and during the subsequent recovery process; however, the hormonal fluctuations in the control group were more pronounced than those in the cold acclimation group (Table.2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistics on the number of differential metabolites between the cold acclimation and the control at different stages.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUp\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDown\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-C_VS_CK-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-F_VS_CK-F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-T_VS_CK-T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-R1_VS_CK-R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-R3_VS_CK-R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe content of plant hormones in \u003cem\u003eP. kingianum\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eABA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e(ng/g)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.05\u0026thinsp;\u0026plusmn;\u0026thinsp;21.53\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.44\u0026thinsp;\u0026plusmn;\u0026thinsp;5.61\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.08\u0026thinsp;\u0026plusmn;\u0026thinsp;8.52\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.96\u0026thinsp;\u0026plusmn;\u0026thinsp;8.79\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.86\u0026thinsp;\u0026plusmn;\u0026thinsp;4.91\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.63\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.23\u0026thinsp;\u0026plusmn;\u0026thinsp;10.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267.8\u0026thinsp;\u0026plusmn;\u0026thinsp;125.31\u003csup\u003eab*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e214.1\u0026thinsp;\u0026plusmn;\u0026thinsp;41.62\u003csup\u003ea*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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rowspan=\"2\"\u003e \u003cp\u003eR3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.52\u0026thinsp;\u0026plusmn;\u0026thinsp;31.62\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.3\u0026thinsp;\u0026plusmn;\u0026thinsp;19.83\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.33\u0026thinsp;\u0026plusmn;\u0026thinsp;21.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e530.08\u0026thinsp;\u003cb\u003e\u0026plusmn;\u003c/b\u003e\u0026thinsp;231.5\u003csup\u003ea*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.53\u0026thinsp;\u0026plusmn;\u0026thinsp;9.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;4.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.84\u0026thinsp;\u0026plusmn;\u0026thinsp;10.37\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e 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colname=\"c5\"\u003e \u003cp\u003e18.24\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.61\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.05\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003csup\u003ea*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.39\u0026thinsp;\u0026plusmn;\u0026thinsp;4.37\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.16\u003csup\u003eb*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.79\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.08\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.48\u0026thinsp;\u0026plusmn;\u0026thinsp;18.71\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.97\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.77\u0026thinsp;\u0026plusmn;\u0026thinsp;11.41\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eR3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.20\u0026thinsp;\u0026plusmn;\u0026thinsp;15.45\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.49\u0026thinsp;\u0026plusmn;\u0026thinsp;4.06\u003csup\u003ea*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.74\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistics on the number of differential genes between the cold acclimation and the control at different stages.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUp\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDown\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-C_VS_CK-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-F_VS_CK-F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19474\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-T_VS_CK-T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-R1_VS_CK-R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-R3_VS_CK-R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10517\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRNA sequencing (RNA-seq) generated a total of 372.63 Gb of transcriptomic data. Applying screening criteria of |log2Fold Change| \u0026ge; 1 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, 9846, 31823, 54415, 3752, and 17719 differentially expressed genes (DEGs) were identified at the five stages of the cold acclimation group compared to the control group (Table.3). KEGG enrichment analysis indicated that DEGs induced by cold acclimation were predominantly enriched in metabolic pathways, biosynthesis of secondary metabolites, and plant hormone signal transduction pathways, with 1153, 686, and 234 significantly altered genes, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Notably, the high expression levels of \u003cem\u003ePP2C\u003c/em\u003e, \u003cem\u003ePYL\u003c/em\u003e, \u003cem\u003eABF\u003c/em\u003e, \u003cem\u003eJAZ\u003c/em\u003e, \u003cem\u003eGRE\u003c/em\u003e, \u003cem\u003ePIF\u003c/em\u003e, \u003cem\u003eETR\u003c/em\u003e, and \u003cem\u003eEIN3\u003c/em\u003e may be play crucial roles in cold acclimation-induced hormone metabolism, contributing to freezing tolerance. The majority of the most significantly changed genes in the control group were associated with the thawing process, while the most significantly altered genes in the cold acclimation group were observed during the recovery phase at one day post-freezing, indicating a recovery from freezing stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This study provides a comprehensive transcriptomic and hormonal profile for the freezing response of \u003cem\u003eP. kingianum\u003c/em\u003e, establishing a foundation for understanding cold acclimation induced freezing tolerance in medicinal herbs with perennial roots, and may assist in the selection of cultivars with enhanced freezing tolerance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003ePlant materials and treatment.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeeds of \u003cem\u003ePolygonatum kingianum\u003c/em\u003e were collected from Honghe, Yunnan Province, China (23\u0026deg;55'32\"N, 102\u0026deg;24'33\"E), at an altitude of 2115.3 m. The seeds were germinated in a soil mixture composed of humus soil and clay in a ratio of 4:1. For cold acclimation, one-year-old seedlings were subjected to dark conditions at 4\u0026deg;C for 3 days. Following this acclimation, all seedlings were exposed to -6\u0026deg;C for 3 hours. After 1 day of exposure to 4\u0026deg;C, the seedlings were placed in a growth chamber under normal growth conditions (12/12 h light/dark cycle at 22\u0026deg;C ) for recovery periods of 1 and 3 days. Biological samples were collected at each stage of treatment: non-freezing treated samples (C), freezing (F), thawing (T), and recovery periods of 1 day (R1) and 3 day (R3). Samples intended of transcriptome analysis and plant hormone detection were rapidly frozen in liquid nitrogen and stored at -80\u0026deg;C for metabolomic and transcriptomic analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlant hormone metabolome analyses and data processing.\u003c/b\u003e The sample was ground using a grinder set at 30 Hz for 1 minute until it transformed into a powder. An aliquot of 50 mg of the ground sample was taken, and 10 \u0026micro;L of an internal standard mixed solution at a concentration of 100 ng/mL was added, followed by 1 mL of a methanol/water/formic acid extractant (15:4:1, v/v/v). The mixture was thoroughly mixed and vortexed at 4\u0026deg;C for 10 minutes, then centrifuged at 12,000 rpm for 5 minutes. The supernatant was transferred to a new centrifuge tube for concentration. The sample was reconstituted with 100 \u0026micro;L of an 80% methanol/aqueous solution, filtered through a 0.22 \u0026micro;m filter membrane, and placed in an injection flask for LC-MS/MS analysis. The analysis was performed using the UPLC-ESI-MS/MS system\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e with a Waters ACQUITY UPLC HSS T3 C18 column. The mobile phase comprised Phase A (ultrapure water containing 0.04% acetic acid) and Phase B (acetonitrile containing 0.04% acetic acid), employing a gradient elution procedure: At 0 min, the A/B ratio was 95:5 (v/v); at 1.0 min, it remained 95:5 (v/v); at 8.0 min, it shifted to 5:95 (v/v); at 9.0 min, it continued at 5:95 (v/v); at 9.1 min, it reverted to 95:5 (v/v); and at 12.0 min, it remained at 95:5 (v/v). The flow rate was set at 0.35 mL/min, and the column oven temperature was maintained at 40\u0026deg;C. An injection volume of 2 \u0026micro;L was utilized. At 550\u0026deg;C, voltages of +\u0026thinsp;5500 V and \u0026minus;\u0026thinsp;4500 V were applied to the sample liquid via the electrospray method to generate aerosols, which were dispersed in a 35 psi gas curtain. In the Q-Trap 6500\u0026thinsp;+\u0026thinsp;mass spectrometer, each ion pair was scanned and detected based on the optimized Declustering Potential (DP) and Collision Energy (CE). The precursor ions of the target substance were screened using triple quadrupole mass spectrometry, and following induced ionization, the characteristic fragment ions were filtered. Ultimately, the obtained mass spectrometry data were integrated with chromatographic peaks and quantitatively analyzed through standard curves. To calculate the content of the substance in the actual samples, substitute the ratio of the integral peak areas of all detected samples into the standard curve linear equation. The hormone content in the sample (ng/g) can be determined using the following formula: concentration value from standard curve(ng/mL) \u0026times; volume of solution for redissolution (\u0026micro;L)/ mass of sample weighed (g).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlant transcriptomic sequencing and data processing.\u003c/b\u003e A total of 1 \u0026micro;g of RNA per sample was utilized as the input material for RNA sample preparations. Sequencing libraries were generated using the NEBNext\u0026reg; UltraTM RNA Library Prep Kit for Illumina\u0026reg; (NEB, USA), adhering to the manufacturer's recommendations, and index codes were incorporated to attribute sequences to each sample. To select cDNA fragments preferentially ranging from 250 to 300 bp in length, the library fragments were purified using the AMPure XP system (Beckman Coulter, Beverly, USA). Subsequently, 3 \u0026micro;L of USER Enzyme (NEB, USA) was applied to the size-selected, adaptor-ligated cDNA at 37\u0026deg;C for 15 minutes, followed by a 5-minute incubation at 95\u0026deg;C before PCR. PCR was then conducted using Phusion High-Fidelity DNA polymerase, Universal PCR primers, and Index (X) Primer. Finally, the PCR products were purified using the AMPure XP system, and library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using the TruSeq PE Cluster Kit v3-cBot-HS (Illumina), following the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina platform, resulting in the generation of 150 bp paired-end reads.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData analysis.\u003c/b\u003e The raw data were analyzed using Excel 2019. A one-way ANOVA was conducted using SPSS Statistics 22, with significance determined through Fisher\u0026rsquo;s Least Significant Difference (LSD) method. Additionally, a visual analysis of the heat map was performed using GraphPad Prism 9.5 software.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Records\u003c/h2\u003e \u003cp\u003eThe original metabolomic data of \u003cem\u003ePolygonatum kingianum\u003c/em\u003e Collett \u0026amp; Hemsl. leaves, collected at various stages of low-temperature treatment, can be accessed through the China National Center for Bioinformation (CNCB) of National Genomics Data Center (NGDC) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ngdc.cncb.ac.cn/omix\u003c/span\u003e\u003cspan address=\"https://ngdc.cncb.ac.cn/omix\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e: accession no. OMIX011073)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Additionally, the raw transcriptome data have been submitted to the Genome Sequence Archive (GSA) of National Genomics Data Center (NGDC) under the accession number CRA026628\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTechnical Validation\u003c/h3\u003e\n\u003cp\u003eIn the analysis process utilizing a mixed solution as a quality control (QC) sample, a QC sample is typically inserted after every ten detection and analysis samples. By superimposing the total ion chromatogram (TIC) obtained from the mass spectrometry analysis of the same QC sample, one can evaluate the instrument's stability throughout the detection period, which reflects its technical repeatability (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The high stability of the instrument is critical as it guarantees the repeatability and reliability of the data. Mass spectrometry data were processed using MultiQuant 3.0.3 software, where the retention time and peak shape information of reference standards were employed to conduct integral correction on the chromatographic peaks detected in various samples of the analyte, thereby ensuring the accuracy of qualitative quantification (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting Interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no any competing interests that could have influenced the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the National Natural Science Foundation of China (82360751), High-Level Talents Project of Yunnan Province (YNWR-QNBJ-2020-257, XDYC-QNRC-2022-0277).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXiheng Wan: Methodology, Investigation, Data curation, Writing - original draft. Jia Chen: Methodology, Data curation, Investigation. You Lu: Methodology, Data curation. Yingsi Gao: Data analysis. Furui Sang: Investigation. Xiaoye Zhang: Data analysis. Menxue Du: material acquisition. Junzhe Zhou: material acquisition. Yanan Li: material acquisition. Guowei Zheng: Supervision, Resources, Writing-review and editing, Project administration. All authros reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (82360751),High-Level Talents Project of Yunnan Province (YNWR-QNBJ-2020-257, XDYC-QNRC-2022-0277). We thank Wuhan Metware Biotechnology Co., Ltd., for its technical support in the metabolome and transcriptome analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe original metabolomic data of *Polygonatum kingianum* Collett \u0026amp; Hemsl. leaves, collected at various stages of low-temperature treatment, can be accessed through the China National Center for Bioinformation (CNCB) of National Genomics Data Center (NGDC) (https://ngdc.cncb.ac.cn/omix: accession no. OMIX011073) 22 . Additionally, the raw transcriptome data have been submitted to the Genome Sequence Archive (GSA) of National Genomics Data Center (NGDC) under the accession number CRA026628 23 .\u003c/p\u003e\n\u003ch3\u003eCode Availability\u003c/h3\u003e\n\u003cp\u003eThe software version and parameters utilized are detailed in the Methods section. This study did not employ any custom code for dataset curation or validation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShi Y. \u003cem\u003eet al.\u003c/em\u003e Huangjing\u0026mdash;From medicine to healthy food and diet. \u003cem\u003eFood Frontiers\u003c/em\u003e, 4, 1068\u0026ndash;1090 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eyu X. How to solve the supply-demand contradiction of Dianhuang Jing. \u003cem\u003eRich World\u003c/em\u003e, 10, 43 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrowse J.\u0026amp;Xin Z. 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(2025)\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":"[email protected]","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":"","lastPublishedDoi":"10.21203/rs.3.rs-8322139/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8322139/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003ePolygonatum kingianum\u003c/em\u003e is a significant medicinal and edible plant, with low temperatures serving as a critical environmental factor that restricts its distribution and growth. In this study, the freezing tolerance of \u003cem\u003eP. kingianum\u003c/em\u003e was enhanced by pre-treating seedlings at 4\u0026deg;C for 3 days. The differential expression of transcripts and hormones during the freezing treatment and subsequent recovery process was compared between control and cold-acclimated samples. A total of 93 differential hormones were identified among these samples along with 372.63 Gb of transcriptome data. This study provides insights into potential hormones and candidate genes involved in the freezing resistance of \u003cem\u003eP. kingianum\u003c/em\u003e, facilitating strategies to cope with extreme temperatures during its cultivation and the selection of freezing-tolerant varieties.\u003c/p\u003e","manuscriptTitle":"Transcriptome and hormonal profiles of Polygonatum kingianum under low temperature stress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 11:22:10","doi":"10.21203/rs.3.rs-8322139/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","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":"c60013fb-a3b2-4efd-9f42-e68ade7aa970","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-15T10:26:18+00:00","index":69,"fulltext":""},{"type":"reviewerAgreed","content":"290317410420159362006689248364922835390","date":"2026-05-06T10:04:59+00:00","index":67,"fulltext":""},{"type":"reviewersInvited","content":"5","date":"2026-05-01T09:59:23+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T11:22:11+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 11:22:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8322139","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8322139","identity":"rs-8322139","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}