Integrated transcriptomic and metabolomic analyses uncover the key pathways of Tamarix ramosissima in adaptation to coppice dune development

Integrated transcriptomic and metabolomic analyses uncover the key pathways of Tamarix ramosissima in adaptation to coppice dune development | 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 transcriptomic and metabolomic analyses uncover the key pathways of Tamarix ramosissima in adaptation to coppice dune development Wei Guo, Haiyu Zhao, Zhengwu Dong, Jingbo Zhang, Yanqin Xu, Bingqian Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9072853/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Tamarix ramosissima is a crucial windbreak and sand-fixing shrub species in the arid deserts of northwest China, where it helps stabilize the ecosystem by trapping dust and enriching soil nutrients. In this study, we systematically investigated the molecular mechanisms underlying T. ramosissima ’s transition through the four developmental stages (initial, growth, stable, and decline) of coppice dunes through integrated physiological, transcriptomic, and metabolomic analyses. Results: From the initial to the growth stage of coppice dunes, soil water content (SWC) gradually decreased, whereas the malondialdehyde (MDA) content in T. ramosissima increased. T. ramosissima could resist drought stress by enhancing soluble protein (SP) and proline (Pro) contents and catalase (CAT) activity. In addition, the decrease in SWC can promote the accumulation of zeatin, dihydrozeatin, and indole-3-acetate in T. ramosissima , thereby accelerating starch consumption to meet plant growth demands. Transcriptome and metabolome analyses revealed that T. ramosissima primarily coordinates gene expression and metabolite accumulation through the ABC transporters, glycerophospholipid metabolism, and glutathione metabolism pathways to adapt to coppice dune development; meanwhile, four hub genes identified by weighted gene co-expression network analysis (WGCNA) are promising candidates for improving drought tolerance in this species. Conclusion: This study reveals that T. ramosissima can adapt to coppice dune development by coordinating gene expression, metabolite accumulation, and physiological regulations. The results provide an important theoretical basis for ecological restoration in arid regions. Transcriptome Metabolome Tamarix ramosissima Coppice dune Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction Global climate change has intensified the spatiotemporal heterogeneity and regional asymmetry of precipitation, profoundly altering the fundamental processes of the global water cycle [ 1 ] . Arid regions face increasingly severe challenges, including shifts in precipitation patterns, elevated evaporative demand, and sustained declines in soil water availability [ 2 ] . These changes drive groundwater depletion and land desertification, threatening vegetation survival and ecosystem stability [ 3 ] . Water scarcity coupled with soil impoverishment constitutes a primary constraint on desert plant growth [ 4 ] . However, coppice dunes can mitigate these stresses by creating a “fertile island effect”, which improves local soil moisture, nutrient availability, and microtopography, thereby providing relatively favorable microhabitats for desert shrubs [ 5 ] . To cope with water stress during the accumulation and development of coppice dune, desert plants typically activate complex antioxidant defense systems. These include enzymatic antioxidants like superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), as well as non-enzymatic substances such as proline (Pro), reduced glutathione, and ascorbic acid, which collectively scavenge excessive reactive oxygen species (ROS) to maintain cellular membrane stability and integrity [ 6 ] . To cope with drought stress and reduce tissue water loss, plants can synthesize osmoprotectants such as Pro, soluble protein (SP), and soluble sugar (SS), thereby lowering cellular osmotic potential, maintaining cell turgor, and facilitating water uptake [ 7 ] . Moreover, under continuous drought stress, plant photosynthesis is inhibited, and the synthesis of non-structural carbohydrates (NSC) is also restricted. When the rate of carbon consumption exceeds the capacity of carbon assimilation, carbon sources become gradually depleted, potentially exposing plants to the risk of carbon starvation and restricting normal physiological processes such as growth and osmotic adjustment [ 8 ] . To balance the dual demands of carbon fixation and water conservation, plants employ adaptive resource allocation strategies. For instance, Nitraria sibirica and Pinus densiflora reallocate resources from growth to defense mechanisms under drought conditions [ 9 , 10 ] . Besides, Phytohormones, serving as central signaling molecules, orchestrate these physiological and metabolic adjustments to enhance drought tolerance [ 11 ] . Therefore, analyzing the integrated physiological and biochemical responses of desert plants is essential for elucidating their adaptation mechanisms to arid environments. Recent advances in high-throughput sequencing have accelerated research into plant stress resistance. Integrated transcriptomic and metabolomic analyses have emerged as powerful tools for deciphering the underlying molecular mechanisms [ 12 , 13 ] . Specifically, Transcriptomics reveals the genetic regulation of metabolite biosynthesis, transport, and signaling [ 14 ] , whereas metabolomics identifies and quantifies small-molecule metabolites, linking them to physiological changes [ 15 ] . Consequently, their combined analysis can reconstruct the complex regulatory network of "gene expression—metabolite accumulation—phenotypic response", enabling comprehensive elucidation of plant adaptation to adverse environments [ 16 ] . This integrated strategy has been widely applied to study drought adaptation in desert plants such as Haloxylon ammodendron , Haloxylon persicum , Salix psammophila , and Tamarix taklamakanensis [ 17 , 18 , 19 ] . However, Species-specific genetic backgrounds drive distinct adaptive mechanisms. For instance, H. ammodendron and H. persicum enhance drought tolerance by upregulating pathways related to glycolysis/gluconeogenesis and amino acid synthesis [ 19 ] . In contrast, drought represses photosynthesis in Nitraria sibirica through the downregulation of genes encoding key components, including photosystem II (e.g., PsbP , PsbQ , PsbR , PsbY , Psb27 ), photosystem I (e.g., PsaD , PsaF , PsaG , PsaH , PsaK , PsaO ), photosynthetic electron transport ( PetF ), and light-harvesting antenna proteins [ 10 ] . Meanwhile, Ammopiptanthus nanus enhances drought resistance via ABA signaling transduction, achieved by downregulating PYR/PYL and PP2C genes and promoting ABA accumulation [ 20 ] . Collectively, these studies lay a crucial foundation for understanding the drought response mechanisms of desert plants. T. ramosissima , a keystone windbreak and sand-fixing shrub in arid regions, forms distinctive coppice dunes through long-term wind-sand interactions and plays a pivotal role in soil and water conservation, desertification control, and biodiversity maintenance [ 21 , 22 ] . The formation of these dunes is an extremely protracted process, often spanning centuries to over a millennium, during which dune heights increase from tens of centimeters to tens of meters. Based on morphological characteristics, the development of Tamarix coppice dunes typically proceeds through four stages: initial, growth, stable, and decline [ 23 , 24 ] . Notably, at the decline stage of coppice dunes, T. ramosissima exhibits dwarfism, self-thinning, and degradation, ultimately losing its sand-fixing capacity [ 23 ] . This transformation turns the dunes into sources of sandstorms, threatening both ecosystem integrity and human well-being. Consequently, in the context of global climate change, deciphering the physiological and molecular adaptation of T. ramosissima to dune development is therefore critical for desert ecosystem conservation. Current research on Tamarix coppice dunes has primarily focused on soil nutrients, water-use strategies, and photosynthetic responses [ 23 , 25 , 26 ] . However, the associated physiological metabolism, gene regulatory networks, and metabolite accumulation patterns in T. ramosissima throughout dune development remain largely uncharacterized. Therefore, this study focused on T. ramosissima inhabiting coppice dunes at different developmental stages in the southwestern Gurbantunggut Desert. By integrating physiological trait analysis with transcriptomics and metabolomics, we elucidated the adaptive mechanisms underlying its response to dune development. Specifically, we addressed the following two questions: (1) What is the relationship between the physiological traits of T. ramosissima and soil water content during this process? (2) What are the molecular bases of T. ramosissima ’s adaptation to coppice dune development? Our findings advance the understanding of the physiological and molecular regulatory mechanisms behind T. ramosissima ’s adaptation to dune development and provide valuable genetic resources for breeding drought-tolerant plants. 2 Materials and methods 2.1. Study site The Gurbantunggut Desert (84°50'–91°20' E, 44°15'–46°50' N), located in the central Junggar Basin of Xinjiang, covers an area of approximately 4.88×10⁴ km² ( Fig. 1 ) . It is dominated by fixed and semi-fixed dunes, which account for about 97% of its total area, making it the largest desert of this type in China [ 27 ] . The region experiences a typical temperate continental climate characterized by hot summers and cold, snowy winters, with a stable snow cover period lasting 100–150 days. The annual average temperature ranges from 6 to 10 ℃, while annual precipitation averages between 70 and 150 mm, far below the annual potential evaporation, which exceeds 2,000 mm. Vegetation coverage is relatively high, ranging from 40% to 50%, and includes over 200 species of drought-tolerant and ephemeral plants [ 27 ] . Dominant species consist of xerophytic and super-xerophytic shrubs, such as Haloxylon ammodendron , Haloxylon persicum , Eremosparton songoricum , and Agriophyllum squarrosum . 2.2. Plot set up and sample collection With local department permission, we established a 5 km × 5 km experimental plot in the Mosuowan Desert Area (44°55′ N, 86°12′ E), at the southwestern edge of the Gurbantunggut Desert ( Fig. 1 ) . Using established dune classification criteria, we adopted the space-for-time substitution method and selected four developmental stages of T. ramosissima coppice dunes: initial, growth, stable, and decline [ 23 , 28 ] . For each stage, three replicate dunes were chosen, totaling 12 coppice dunes. Mature, intact, and pest-free leaf samples of T. ramosissima were collected from the east-oriented middle canopy of the selected dunes. Sampling took place between 07:00 and 10:00 local time on July 12, 2024. All samples were immediately flash-frozen in liquid nitrogen and then transported to the laboratory for storage at -80 ℃ for subsequent analysis. We also measured the soil water content (SWC) at 0–500 cm depth in coppice dunes of each developmental stage. Results showed that SWC decreased continuously as dune development progressed (Table S1 ) . In addition, a meteorological station within 5 km of the study area confirmed that no precipitation occurred in the 37 days before sampling. This ensured that sampling took place under extreme aridity and high temperatures, minimizing the confounding effects of short-term climatic variability. 2.3. Physiological indicator determination Following the method of Chang and Lv [ 10 ] , after 0.1 g of plant leaf tissue was weighed, the activities of SOD, CAT, and POD were determined using the nitroblue tetrazolium (NBT) reduction, spectrophotometric, and guaiacol methods, respectively; the contents of Pro, SS, SP, and MDA were quantified using the sulfosalicylic acid, anthrone colorimetric, Coomassie brilliant blue (G-250), and thiobarbituric acid (TBA) methods, respectively. Starch (ST) content was measured by acid hydrolysis followed by anthrone colorimetric quantification and conversion to starch equivalents. Non-structural carbohydrates (NSC) content was calculated as the sum of SS and ST [ 29 ] . All assays were performed with commercial kits (Grace Biotechnology Co., Ltd., Suzhou, China). 2.4. Metabolomic analysis Approximately 50 mg of frozen leaf tissue was ground at 45 Hz for 10 min, followed by sonication in an ice-water bath for 10 min and centrifugation at 12,000 rpm (4°C) for 15 min. The supernatant was collected, vacuum-dried, and then reconstituted in the extraction solution. The mixture was vortexed for 30 s, sonicated for 10 min in an ice-water bath, and centrifuged again. The final supernatant was used for LC-MS/MS analysis. Raw data files were processed using Progenesis QI software for peak extraction and alignment. Metabolites were identified by searching against the integrated METLIN database and public repositories, with confirmation based on theoretical fragment matching. They were subsequently annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG Database), the Human Metabolome Database (HMDB Database), and the Lipid Metabolites and Pathways Strategy (LIPID MAPS). Differentially accumulated metabolites (DAMs) were screened based on the following criteria: a variable importance in projection (VIP) value > 1.0 from orthogonal partial least squares-discriminant analysis (OPLS-DA), fold change ≥ 1, and p < 0.05. 2.5. Transcriptomic analysis Total RNA was extracted using the Polysaccharide-Polyphenol Plant Total RNA Extraction Kit (Tiangen, China). mRNA libraries were constructed and sequenced on the Illumina NovaSeq Xplus platform. Raw reads were filtered to remove adapters and low-quality bases, yielding clean reads. De novo transcriptome assembly was performed using Trinity software [ 30 ] . The assembled transcripts were clustered to remove redundancy using TGICL, generating a set of unigenes. Functional annotation of the unigenes was performed using BLAST searches against multiple databases, including NR, Swiss-Prot, COG, KOG, eggNOG, KEGG, GO, and Pfam. Transcription factors (TFs) were predicted using iTAK software [ 31 ] . Gene expression levels were quantified using the FPKM metric. Differentially expressed genes (DEGs) were identified with the DESeq2 package, applying thresholds of |log 2 FC| ≥ 1 and False Discovery Rate (FDR) < 0.01. 2.6. Quantitative Real-Time PCR (qRT-PCR) validation A total of 12 DEGs associated with drought stress were randomly selected for quantitative real-time PCR (qRT-PCR) validation. Total RNA was extracted using a total plant RNA extraction kit (FOREGENE, China), and first-strand cDNA was synthesized with a corresponding reverse transcription kit (FOREGENE, China). qRT-PCR assays were performed using SYBR Green I Master Mix (FOREGENE, China) with Actin serving as the reference gene. The primer sequences used are listed in Table S2 . Relative expression levels were calculated using the 2 ⁻ΔΔCT method based on three independent biological replicates. 2.7. Statistical analysis Statistical analyses of physiological data were performed using IBM SPSS Statistics 26. One-way analysis of variance (ANOVA) was conducted, followed by Duncan’s multiple-range test for post hoc comparisons, with a significance level of p < 0.05. Graphs were constructed using Origin 2024. Hub genes within key co-expression modules were identified with the degree algorithm in the cytoHubba plugin for Cytoscape 3.7.1. Venn diagrams were generated using TBtools. All other bioinformatics analyses were performed on an online platform ( https://www.biocloud.net/ ). 3. Results 3.1. Leaf physiological traits Leaf physiological and biochemical traits of T. ramosissima varied significantly across the developmental stages of coppice dunes ( Fig. 2 ) . SP and Pro contents were significantly higher at the decline stage of coppice dunes compared to the initial and growth stages of coppice dunes ( p < 0.05; Fig. 2 A, C ) . In contrast, SS content was highest at the growth stage of coppice dunes and lowest at the decline stage of coppice dunes ( p < 0.05; Fig. 2 B ) . ST content of T. ramosissima exhibited a gradual decrease with dune development, reaching its lowest level at the decline stage of coppice dunes ( p < 0.05), which represented a 52.6% reduction from the initial stage of coppice dunes ( Fig. 2 D ) . NSC content was significantly higher at initial (24.68 mg/g) and growth (24.37 mg/g) stages of coppice dunes than at stable and decline stages of coppice dunes ( p < 0.05; Fig. 2 E ) . Regarding antioxidant capacity, SOD activity peaked at growth and stable stages of coppice dunes ( p < 0.05) and was lowest at the decline stage of coppice dunes ( Fig. 2 I ) . In contrast, CAT activity showed the opposite trend, being highest at the decline stage of coppice dunes ( Fig. 2 H ) . MDA content was highest in plants at the decline stage of coppice dunes (27.66 nmol/g; p < 0.05), indicating the most severe membrane lipid peroxidation under environmental stress ( Fig. 2 F ) . These results indicate that the development of coppice dunes significantly affects the physiological characteristics of T. ramosissima . 3.2. Metabolomic analysis Principal Component Analysis (PCA) revealed clear separation among the four dune developmental stages, with biological replicates closely clustered within the 95% confidence ellipse ( Fig. 3 A ) . Furthermore, hierarchical clustering analysis demonstrated distinct, stage-specific patterns of metabolite accumulation across the developmental stages of coppice dunes ( Fig. 3 B ) . 3.3. DAMs statistics Across all pairwise comparisons encompassing the four dune developmental stages, a total of 4,504 DAMs were identified (Table S3 ) . Specifically, 1,981 DAMs (1,076 upregulated, 905 downregulated), 547 DAMs (248 upregulated, 299 downregulated), 987 DAMs (423 upregulated, 564 downregulated), 867 DAMs (260 upregulated, 607 downregulated), 795 DAMs (284 upregulated, 511 downregulated), and 755 DAMs (459 upregulated, 296 downregulated) were identified in the pairwise comparisons of ISL vs GSL, ISL vs SSL, ISL vs DSL, GSL vs SSL, GSL vs DSL, and SSL vs DSL, respectively. Notably, the number of DAMs in T. ramosissima gradually decreased across the comparisons of ISL vs GSL, GSL vs SSL, and SSL vs DSL, indicating that coppice dune development suppresses the metabolic regulatory capacity of T. ramosissima . 3.4. Phytohormone content changes Based on previous reports linking specific metabolites to drought response, we focused on analyzing changes in plant hormone levels among drought-related DAMs. Venn analysis was performed on DAMs involved in the plant hormone signal transduction pathway. The results demonstrated that zeatin and indole-3-acetate were commonly identified across three comparison groups: ISL vs GSL, GSL vs SSL, and SSL vs DSL ( Fig. 4 A ) . In contrast, Dihydrozeatin was exclusively shared between the ISL vs GSL and SSL vs DSL groups ( Fig. 4 A ) . Subsequently, the abundance dynamics of these three hormones were visualized to illustrate their accumulation patterns. We found that zeatin and indole-3-acetate levels exhibited a “rise–fall–rise” pattern across the dune developmental stages ( Fig. 4 B, D ) . Moreover, dihydrozeatin levels increased from the initial stage to the growth stage and from the stable stage to the decline stage ( Fig. 4 C ) . Notably, all three hormones reached their peak concentrations at the decline stage of coppice dunes ( Fig. 4 B-D ) . These results suggest that T. ramosissima actively modulates its endogenous hormone homeostasis to activate stress-responsive signaling pathways, thereby adapting to the changing environment during coppice dune development. 3.5. Transcriptome sequencing Transcriptome sequencing generated 72.52 Gb of high-quality clean data, with Q30 scores exceeding 95.26% and GC content above 43.19%, confirming high sequencing accuracy (Table S4) . De novo assembly yielded 99,886 unigenes with an N50 length of 2,038 bp, indicating good transcriptome continuity. High consistency among biological replicates was confirmed by Pearson correlation coefficients (R² > 0.95; Fig. 5 A). 3.6. Functional annotation of unigenes Among the assembled unigenes, 45,428 (45.48% of total) were successfully annotated against at least one of the eight public databases, while 7,036 unigenes obtained annotations from all databases ( Fig. 5 B ) . The eggNOG database provided the highest number of unique annotations, whereas the Gene Ontology (GO) database contributed the fewest exclusive annotations. 3.7. DEGs statistics Across all pairwise comparisons encompassing the four dune developmental stages, a total of 24,881 DEGs were identified. Among of 15,302 DEGs (12,915 upregulated, 2,387 downregulated), 9,243 DEGs (6,978 upregulated, 2,265 downregulated), 14,325 DEGs (11,653 upregulated, 2,672 downregulated), 15,594 DEGs (3,370 upregulated, 12,224 downregulated), 15,974 DEGs (7,128 upregulated, 8,846 downregulated), and 15,504 DEGs (10,897 upregulated, 4,607 downregulated) were identified in the pairwise comparisons of ISL vs GSL, ISL vs SSL, ISL vs DSL, GSL vs SSL, GSL vs DSL, and SSL vs DSL, respectively ( Fig. 6 A ) . Notably, upregulated DEGs predominated in comparisons involving ISL vs GSL and SSL vs DSL, whereas downregulated genes were markedly more abundant in GSL vs SSL. This pattern suggests that the progression from the growth to the stable stage of coppice dune is associated with a broad suppression of core metabolic processes. Transcription factor (TF) prediction identified hundreds of differentially expressed TFs in each comparison, with total counts ranging from 373 to 634 ( Fig. 6 B ) . The C2H2 and bHLH families were consistently the most abundant among these TFs across all comparisons, indicating their pivotal roles in regulating T. ramosissima ’s response to coppice dune development. 3.8. qRT-PCR validation The reliability of the RNA-seq expression data was validated by qRT-PCR analysis of 12 randomly selected DEGs related to drought stress. The results exhibited a high correlation (R² > 0.94) between the two methods (Fig. S1 ) , confirming the high consistency and robustness of the transcriptomic dataset. 3.9. Integrated transcriptomic and metabolomic analysis identifies key pathways Integrated transcriptomic and metabolomic analysis consistently revealed three co-enriched pathways across ISL vs GSL, ISL vs SSL, and ISL vs DSL, including glutathione metabolism (ko00480), ABC transporters (ko02010), and glycerophospholipid metabolism (ko00564) ( Fig. 7 A–C ) . This highlights their crucial roles in T. ramosissima ’s adaptation to the development of coppice dunes. DEGs expression within these pathways displayed distinct stage-specific patterns. In the glutathione metabolism pathway, most genes encoding glutathione S-transferase (16 upregulated, 3 downregulated), dehydroascorbate reductase (2 upregulated), and glutathione peroxidase (7 upregulated) were upregulated in ISL vs GSL; most were downregulated in GSL vs SSL (glutathione S-transferase: 4 upregulated, 14 downregulated; dehydroascorbate reductase: 2 downregulated; glutathione peroxidase: 3 upregulated, 7 downregulated); and re-upregulated in SSL vs DSL (glutathione S-transferase: 16 upregulated, 12 downregulated; dehydroascorbate reductase: 2 upregulated, 1 downregulated; glutathione peroxidase: 4 upregulated, 2 downregulated) (for detailed gene counts, see Table S5 ). Correspondingly, the GSH/GSSG ratio (reduced-to-oxidized glutathione ratio) decreased from GSL to SSL but increased from SSL to DSL, reflecting dynamic shifts in cellular redox state (Table S5) . Similarly, in both the ABC transporters and glycerophospholipid metabolism pathways, the predominant expression pattern for most genes was upregulated in ISL vs GSL, downregulated in GSL vs SSL, and subsequently re-upregulated in SSL vs DSL (Table S6 and S7) . Venn analysis of metabolites associated with these pathways identified 17 key differential metabolites ( Fig. 7 D, Table S8) . 3.10. Hub gene identification via weighted gene co-expression network analysis (WGCNA) To identify key gene modules linked to coppice dune development, we performed WGCNA by correlating DEGs expression matrices with the abundance of 17 key DAMs. Based on expression patterns, DEGs were clustered into eight distinct modules ( Fig. 8 A ) , and a heatmap visualized the correlation strengths between these gene modules and the DAMs ( Fig. 8 B ) . Among them, the MEturquoise and MEyellow modules showed the most significant correlations with the DAMs. Four drought response hub genes were identified based on gene connectivity within modules and the published literature. Of these, two were derived from the MEturquoise module ( Fig. 9 A, B ) , while the remaining two originated from the MEyellow module ( Fig. 9 C, D ) . These were TRINITY_DN1805_c0_g1 ( SAP4-like ), TRINITY_DN740_c1_g1 (EXO70B1) , TRINITY_DN2662_c2_g1 ( MAPKK5-like ), and TRINITY_DN4872_c1_g2 (bHLH47-like ). 3.11. Co-expression network analysis of molecular levels, physiological traits, and SWC A co-expression network was constructed based on Pearson correlation analysis among the screened DAMs, hub genes, phytohormone levels, physiological traits, and SWC. Strong correlations were observed, notably between hub genes and DAMs, as well as between DAMs and key physiological traits ( Fig. 10 , Table S9) . Furthermore, SWC exhibited a significant negative correlation with Pro, zeatin, dihydrozeatin, and indole-3-acetate ( p < 0.05), but a significant positive correlation with ST ( p < 0.05). This pattern underscores the profound influence of soil water content on the physiological status of T. ramosissima . MDA content was strongly positively correlated with Pro ( p < 0.01). It strongly negatively correlated with SS ( p < 0.01), suggesting that increased membrane lipid peroxidation triggers Pro accumulation and SS consumption to alleviate oxidative damage. In addition, NSC content was strongly negatively correlated with SP, Pro, and MDA ( p < 0.01). It strongly positively correlated with SS and ST ( p < 0.01), indicating that there was a tight metabolic coupling between NSC and other stress-responsive compounds. Notably, ST content exhibited a significant negative correlation with zeatin, dihydrozeatin, and indole-3-acetate ( p < 0.05), suggesting a potential trade-off between starch consumption and the signaling or action of these growth-related hormones during adaptation. 4 Discussion 4.1. Physiological metabolic changes in T. ramosissima during coppice dune development The formation and development of coppice dunes are mainly regulated by soil water content [ 32 ] . Our data show that SWC decreased gradually as coppice dunes developed (Table S1 ) . Correspondingly, SP and Pro contents were lowest at the initial and growth stages of coppice dunes and highest at the decline stage of coppice dunes. Notably, NSC exhibited highly significant negative correlations with SP and Pro. These findings suggest that T. ramosissima reallocates limited NSC resources away from growth and toward defense to adapt to the development of coppice dunes, prioritizing amino acid synthesis and transport, which in turn drives the accumulation of SP and Pro, thereby preventing water loss and maintaining osmotic balance [ 19 ] . In contrast, SS content was lowest at the decline stage of coppice dunes, a finding that differs from reports in Calligonum leucocladum [ 33 ] . This discrepancy may reflect a species-specific strategy in which SS in T. ramosissima shifts from osmotic regulation to energy provision as dune development progresses and drought intensifies [ 34 ] . Changes in NSC content can reflect plants’ carbon supply status and their adaptive strategies to environmental changes [ 23 , 35 , 36 ] . Specifically, ST is an important component of NSC and serves as a long-term energy storage mechanism [ 23 ] . In this study, we found that NSC content was lowest at the decline stage of coppice dunes. This result may stem from multiple factors: (i) stomatal closure under severe drought limiting photosynthetic carbon fixation [ 37 ] ; (ii) NSC consumption for drought defense mechanisms [ 38 ] ; and (iii) prioritization of resource allocation to the construction and storage of below-ground traits, which serve as a mobilizable energy reserve for growth and development after the alleviation of drought stress [ 39 ] . Correspondingly, field observations confirmed that T. ramosissima failed to flower at the decline stage of coppice dunes ( Fig. 11 ) . This observed impaired reproductive capacity is likely due to insufficient NSC reserves, resulting from reduced photochemical efficiency under stress [ 23 ] . Finally, we also found that ST was significantly positively correlated with SWC, indicating that a decrease in SWC promoted the consumption and decomposition of ST to meet plants’ energy demand. Abiotic stress typically triggers excessive ROS accumulation, leading to oxidative damage to cellular membranes, proteins, and nucleic acids [ 40 ] . MDA, a product of membrane lipid peroxidation, serves as a key indicator of the extent of ROS-induced damage, while antioxidant enzymes function to prevent excessive ROS accumulation [ 41 ] . In this study, the highest MDA content was observed in T. ramosissima at the decline stage of coppice dunes. This elevation is likely attributed to two main reasons. On the one hand, SWC was at its lowest during this stage, which induced ROS production in leaves and subsequently triggered lipid peroxidation of membrane lipid [ 42 ] . On the other hand, the extensive dieback of T. ramosissima on dunes led to the lowest canopy density, rendering the plants more susceptible to photoinhibition and resulting in the highest MDA content [ 43 ] . To reduce oxidative damage, T. ramosissima enhanced CAT activity, contributing to ROS homeostasis. However, a strong positive correlation was observed between Pro and MDA, with a negative correlation observed with SWC ( Fig. 10 ) , suggesting that the enzymatic antioxidant system alone may be insufficient for timely ROS scavenging. Meanwhile, the concurrent increase in Pro likely serves dual purposes: osmotic adjustment and direct antioxidant defense, thereby helping stabilize ROS levels [ 44 ] . Nevertheless, persistent drought stress ultimately overwhelms these protective mechanisms, leading to significant cellular damage, as reflected by elevated MDA content [ 45 ] . 4.2. Endogenous hormone changes in T. ramosissima during coppice dune development Zeatin, dihydrozeatin, and indole-3-acetate play crucial roles in regulating plant growth and development [ 46 , 47 ] . Among cytokinins, zeatin is the most active and ubiquitous [ 48 ] . Zeatin and dihydrozeatin have both been shown to promote the division and differentiation of plant cells [ 49 , 50 ] , whereas indole-3-acetate enhances plant height, increases branch number, and promotes biomass accumulation [ 46 ] . Consistent with their known regulatory roles, our study revealed that T. ramosissima dynamically regulated the levels of zeatin, dihydrozeatin, and indole-3-acetate throughout the development of coppice dunes. Specifically, during the transition from the initial to the growth stage of coppice dunes, these hormones accumulated ( Fig. 11 ) . It is likely due to improvements in the rhizosphere microenvironment, such as the increase in coppice dunes volume and height, which provides extensive growth space for plant root systems, enhances water and nutrient uptake, and supports the development of larger aboveground biomass. Simultaneously, facilitates the temporary retention of additional moisture, while the formation of a biological soil crust reduces soil water evaporation [ 51 ] . In addition, the "fertile island" effect promotes soil nutrient enrichment [ 52 ] . These changes promote elevated hormone levels and increase aboveground biomass [ 35 ] . Conversely, from the growth to the stable stage of coppice dunes, the contents of zeatin and indole-3-acetate in T. ramosissima decreased ( Fig. 11 ) . This shift coincides with continuously declining SWC and may reflect a strategic reallocation of resources from vigorous vegetative growth towards maintenance and defense [ 10 ] . Notably, from the stable to the decline stage of coppice dunes, the contents of zeatin, dihydrozeatin, and indole-3-acetate in T. ramosissima increased. This may be closely related to the dwarfism and withered branches caused by drought stress in T. ramosissima . These morphological adjustments reduce overall water demand and may alter internal hormone homeostasis or signaling, ultimately serving as a survival mechanism to prolong viability under extreme stress. In addition, both SWC and ST content showed significant negative correlations with zeatin, dihydrozeatin, and indole-3-acetate, indicating that decreased SWC can act as a stress signal to promote hormone accumulation and trigger plant stress resistance mechanisms. Meanwhile, the growth-promoting effects of these endogenous hormones require ST consumption to meet energy demands. 4.3. Key metabolic pathways in T. ramosissima’s adaptation to coppice dune development This study provides the first integrated transcriptomic and metabolomic profile of T. ramosissima across the developmental stages of coppice dunes, generating 72.52 Gb of high-quality sequencing data that constitutes a valuable resource for Tamarix functional genomics. Our analysis found that glutathione metabolism, ABC transporters, and glycerophospholipid metabolism are key pathways co-enriched with both DEGs and DAMs, highlighting their central role in T. ramosissima ’s adaptation to coppice dune development ( Fig. 11 ) . Notably, these pathways are highly conserved, aligning with core mechanisms reported in other plant species under drought stress [ 53 , 54 , 55 ] . This suggests a fundamental adaptive strategy across aridland plants. During the transition from the initial to the growth stage of coppice dunes, SWC began to decline. In response, T. ramosissima upregulated most genes in the glutathione metabolism pathway (e.g., encoding glutathione S-transferase, dehydroascorbate reductase, and glutathione peroxidase) to enhance redox homeostasis, stabilize the mitochondrial electron transport chain, and mitigate early oxidative stress. Furthermore, it activated the ABC transporters pathway (particularly ABCB, ABCC, and ABCG subfamilies), promoting the transport of secondary metabolites and hormones to support shoot and leaf morphogenesis [ 54 , 55 ] . We also found that levels of L‑proline and hydroxyproline associated with the ABC transporters pathway were upregulated, further corroborating their vital role in maintaining osmotic balance under drought stress (Table S8) . In contrast, deoxyguanosine and D‑ribose were downregulated, indicating that drought exacerbates the risk of ROS-induced DNA damage (Table S8) . The glycerophospholipid metabolism pathway was also induced, leading to upregulation of genes that facilitate cell division, membrane biosynthesis, and signal transduction, thereby supporting rapid growth and enhancing drought tolerance [ 56 ] . As dunes progressed from the growth to the stable stage of coppice dunes, SWC continued to decrease. Reflecting a strategic shift, most DEGs in the three core pathways were downregulated. This may be because T. ramosissima can preferentially allocate resources to other defense mechanisms that better ensure its survival. From the stable to the decline stage of coppice dunes, both SWC and NSC content decreased to their minimum levels, accompanied by substantial accumulation of MDA and an elevated GSH/GSSG ratio. Under these conditions, the plants upregulated the three metabolic pathways to repair membrane damage, enhance antioxidant capacity, and transport stress-related substances, thereby resisting drought stress. In summary, T. ramosissima dynamically regulated the expression of key genes and metabolites in core metabolic pathways across different developmental stages of coppice dunes, ultimately enabling adaptation to microhabitat changes in arid environments. 4.4. Hub genes mediating T. ramosissima’s drought response Four hub genes associated with T. ramosissima ’s response to coppice dune development were identified via WGCNA ( Fig. 9 ) . The TRINITY_DN2662_c2_g1 ( MAPKK5-like ) and TRINITY_DN4872_c1_g2 ( bHLH47-like ) were identified in the MEturquoise module. Investigations in potato have revealed that overexpression of StMAPKK5 significantly increases relative water content, antioxidant enzyme activity, and Pro accumulation, while reducing MDA content, thereby enhancing drought tolerance [ 57 ] . Furthermore, virus-induced gene silencing (VIGS)-mediated silencing of GhMAPKK5 in cotton accelerates wilting under salt and drought stress. In contrast, overexpression of GhMAPKK5 in A. thaliana promotes root growth and seed germination [ 58 ] . These findings suggest that MAPKK5-like and bHLH47-like may also contribute to improved drought tolerance in T. ramosissima . Similarly, TRINITY_DN1805_c0_g1 ( SAP4-like ) and TRINITY_DN740_c1_g1 ( EXO70B1 ) were identified from the MEyellow module. Prior research has demonstrated that overexpression of ZmSAP8 and MdSAP15 enhances drought stress tolerance in Arabidopsis thaliana [ 25 , 59 ] . Consistently, in A. thaliana , Exo70B1 and Exo70B2 positively regulate abscisic acid (ABA)- and mannitol-induced stomatal closure; overexpression of VviExo70B in Vitis vinifera callus and A. thaliana improves tolerance to drought and NaCl stress while increasing ABA sensitivity [ 60 ] . Accordingly, we hypothesize that SAP4-like and EXO70B1 may exert analogous functions in T. ramosissima ’s adaptation to water deficit. These results indicate that the four identified hub genes hold promise as candidate genes for enhancing drought tolerance in T. ramosissima . 5 Limitations This study has several limitations that need to be explicitly acknowledged. First, plant roots play a key role in water and nutrient uptake under drought stress. However, this study mainly focused on leaf samples of T. ramosissima and did not focus on root samples. Second, although WGCNA has revealed the potential role of hub genes in drought resistance regulation in depth, the present study did not conduct in situ functional validation experiments (e.g., gene overexpression, silencing, or knockout) in T. ramosissima , nor did it perform heterologous expression validation in model plants (e.g., A. thaliana ), which limits the translational applicability of the research results. To address these limitations, future studies should integrate root transcriptome and metabolome analyses to provide a more comprehensive understanding of whole-plant adaptive strategies; second, overexpress or silence the identified hub genes and explore their effects on drought-related phenotypes. 6 Conclusions (1) From the initial to the growth stage of coppice dunes, SWC gradually decreased, while the MDA content in T. ramosissima increased. In response, T. ramosissima resisted drought stress by enhancing SP and Pro contents and CAT activity. (2) The decrease in SWC can promote the accumulation of zeatin, dihydrozeatin, and indole-3-acetate in T. ramosissima , thereby accelerating starch consumption to meet plant growth demands. (3) T. ramosissima mainly coordinates gene expression and metabolite accumulation in the ABC transporters, glycerophospholipid metabolism, and glutathione metabolism pathways to adapt to coppice dune development. Abbreviations All abbreviations are defined upon first use in the manuscript. Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Author Contributions: W.G. and H.Z. carried out experiments. Z.W. and J.Z. developed the research ideas and designed the experiments. Z.W. acquired funding and revised the manuscript. Y.X. and B.Z. contributed to the field data collection. W.G. wrote the manuscript with contributions from all other authors. The authors declare no conflicts of interest. Acknowledgments : The authors thank the Mosuowan Desert Research Station, the Xinjiang Special Environment Species Protection and Regulation Biology Laboratory (Xinjiang, China) for their support in conducting this study. Funding: This research was funded by the National Natural Science Foundation of China (32560395), the Natural Science Foundation project of Xinjiang Uygur Autonomous Region (2024D01A84), and the 2025 Bortala Prefecture Grass Germplasm Resources Census Entrusted Project (Bid Item Three) (CYZZ2025003). Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon request. References Zhang W, Furtado K, Wu P, Zhou T, Chadwick R, Marzin C, et al. Increasing precipitation variability on daily-to-multiyear time scales in a warmer world. Science Advances. 2021;7(31):eabf8021. https://doi.org/10.1126/sciadv.abf8021. Patel R, Patel A. “Evaluating the impact of climate change on drought risk in semi-arid region using GIS technique.” Results in Engineering. 2024;21:101957. https://doi.org/10.1016/j.rineng.2024.101957. Feng L, Liu W, Zhao A. 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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-9072853","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":615218519,"identity":"48fb2f41-409f-4c65-bb2a-6a5102f2cbc4","order_by":0,"name":"Wei Guo","email":"","orcid":"","institution":"Xinjiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Guo","suffix":""},{"id":615218521,"identity":"c08fce94-c5bf-42ac-aa55-72c3d9a9f13a","order_by":1,"name":"Haiyu Zhao","email":"","orcid":"","institution":"Kashi University","correspondingAuthor":false,"prefix":"","firstName":"Haiyu","middleName":"","lastName":"Zhao","suffix":""},{"id":615218522,"identity":"70306a09-50cf-47ea-9d23-acbe731cfdf5","order_by":2,"name":"Zhengwu Dong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDCCA2DShoeNvfkAQwIJWtLk+HiOJZCk5bCxnESOAXHu4jvee/jlzzbmxDaeM58/PNxhx8Df3o3fMskz59IsJNvYEtvYe7dJJJ5JZpA4c3YDXi0GN3LMDAy38QBtObuNIbGNmcFAIpcILYlA89skch5/SGyrJ0qL8YOD2wyM2SRyGIAaDxPWInnmjBlj478EOTaeY2ZALcd5CPqF73iP8ccfZ/7zyLc3P/74s61ajr+9F78WIGCTQObxEFIOAswfiFE1CkbBKBgFIxgAAPjhTBSvftGmAAAAAElFTkSuQmCC","orcid":"","institution":"Xinjiang Normal University","correspondingAuthor":true,"prefix":"","firstName":"Zhengwu","middleName":"","lastName":"Dong","suffix":""},{"id":615218523,"identity":"ca7d0790-3c93-49d4-8e07-fdddd6a20c8e","order_by":3,"name":"Jingbo Zhang","email":"","orcid":"","institution":"Xinjiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Jingbo","middleName":"","lastName":"Zhang","suffix":""},{"id":615218525,"identity":"44593101-b1d2-4d3c-a131-8cab9663a7aa","order_by":4,"name":"Yanqin Xu","email":"","orcid":"","institution":"Xinjiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yanqin","middleName":"","lastName":"Xu","suffix":""},{"id":615218526,"identity":"b0a363e0-17e0-4bec-a88f-b2e178aefdfe","order_by":5,"name":"Bingqian Zhou","email":"","orcid":"","institution":"Xinjiang Normal University","correspondingAuthor":false,"prefix":"","firstName":"Bingqian","middleName":"","lastName":"Zhou","suffix":""}],"badges":[],"createdAt":"2026-03-09 12:24:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9072853/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9072853/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105952709,"identity":"962ab164-8237-41de-abde-870a71ff45b9","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":326269,"visible":true,"origin":"","legend":"\u003cp\u003eThe sample plot of the study area \u003csup\u003e[23]\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/69fda630f14a6a848a6f83df.png"},{"id":106093900,"identity":"34fdfad1-a485-432f-a0ab-7bef5878bfd4","added_by":"auto","created_at":"2026-04-03 11:39:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114659,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in osmotic adjustment substances, non-structural carbohydrates (NSC), and antioxidant enzyme activities of \u003cem\u003eT. ramosissima\u003c/em\u003e on coppice dunes at different developmental stages. (A) Soluble protein (SP) content. (B) Soluble sugar (SS) content. (C) Proline (Pro) content. (D) Starch (ST) content. (E) Non-structural carbohydrates (NSC) content. (F) Malondialdehyde (MDA) content. (G) Peroxidase (POD) activity. (H) Catalase (CAT) activity. (I) Superoxide dismutase (SOD) activity. ISL, GSL, SSL, and DSL represent the leaves of \u003cem\u003eT. ramosissima\u003c/em\u003e growing on coppice dunes at the initial, growth, stable, and decline stages, respectively. Different lowercase letters (a, b, c, d) indicate statistically significant differences among different stages at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/7d6e4a774b79173a3f3fa458.png"},{"id":106093186,"identity":"87fca303-3b2d-462d-88cf-1be4a9400043","added_by":"auto","created_at":"2026-04-03 11:35:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98495,"visible":true,"origin":"","legend":"\u003cp\u003eQuality control of metabolomics data and metabolite abundance across different samples. (A) Principal component analysis (PCA) of metabolomic samples. (B) Expression patterns of metabolites in different samples. ISL, GSL, SSL, and DSL represent the leaves of \u003cem\u003eT. ramosissima\u003c/em\u003e growing on coppice dunes at the initial, growth, stable, and decline stages, respectively.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/5956ea899a2957df6ddc1beb.png"},{"id":105952715,"identity":"b9d45d93-3248-4400-af87-23a8e0e2e6a6","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56430,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in endogenous hormone contents of \u003cem\u003eT. ramosissima\u003c/em\u003e under coppice dune development. Venn analysis of metabolites involved in the metabolic pathways of plant hormone signal transduction (A). Changes in zeatin (B), dihydrozeatin (C), and indole-3-acetate (D) abundances in different samples. ISL, GSL, SSL, and DSL represent the leaves of \u003cem\u003eT. ramosissima\u003c/em\u003e growing on coppice dunes at the initial, growth, stable, and decline stages, respectively.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/9e2f85acf62359abb4182966.png"},{"id":106093184,"identity":"dd8c0221-bb93-4dcb-b4ce-3dd9e891d0c1","added_by":"auto","created_at":"2026-04-03 11:35:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":131544,"visible":true,"origin":"","legend":"\u003cp\u003eSample quality control and unigene annotation of transcriptomics. (A) Correlation heatmap between samples. (B) Annotation status of unigenes in different databases.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/ffda593e9b30af3bcae8f36b.png"},{"id":105952716,"identity":"be612154-6b68-432e-b95b-8a75abdb4762","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":196184,"visible":true,"origin":"","legend":"\u003cp\u003eStatistics of the number of DEGs (A) and transcription factors (B) in different comparison groups.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/0a652116de9f17c7e47f9c18.png"},{"id":105952718,"identity":"1d9abdeb-9a02-4e5e-a138-6ab68c6db542","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":158793,"visible":true,"origin":"","legend":"\u003cp\u003eCo-enrichment of KEGG pathways in transcriptome and metabolome. KEGG co-enrichment analysis of transcriptome and metabolome in ISL vs GSL (A), GSL vs SSL (B), and SSL vs DSL (C). (D) Screening of key differential metabolites.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/d684bb7137291736909d6465.png"},{"id":106093899,"identity":"3a6b7b20-efd6-43fc-a20d-06d5c66f1219","added_by":"auto","created_at":"2026-04-03 11:39:55","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":120801,"visible":true,"origin":"","legend":"\u003cp\u003eCluster dendrogram (A) and module division of DEGs (B).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/0d8076a832cc902757df6049.png"},{"id":105952720,"identity":"b7e82346-4d85-4fa5-ae9f-805eec0ee819","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":310327,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification of hub genes in the module. (A) and (B) represent hub genes in the MEturquoise module; (C) and (D) represent hub genes in the MEyellow module\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/a52e2c3d4397170c17bbcdf4.png"},{"id":106093311,"identity":"eee16ed5-6cf1-4a5c-8aa3-30edc5e3ec95","added_by":"auto","created_at":"2026-04-03 11:36:40","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":424158,"visible":true,"origin":"","legend":"\u003cp\u003eCo-expression network analysis of hub genes, DAMs, phytohormone levels, physiological traits, and SWC. Diamonds represent phytohormones, rectangles represent DAMs, triangles represent hub genes, ellipses represent physiological traits, and inverted triangles represent SWC. Solid lines indicate significantly positive correlations (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), while dashed lines indicate significantly negative correlations (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). MDA, malondialdehyde; NSC, non-structural carbohydrates; ST, starch; SS, soluble sugar; SOD, superoxide dismutase; CAT, catalase; SP, soluble protein; Pro, proline. For detailed information on the correlation network, refer to \u003cstrong\u003eTable S9\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/64596ec12aa8bebd86644d32.png"},{"id":105952722,"identity":"d383b661-6405-4657-9b75-0b165502509b","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":125695,"visible":true,"origin":"","legend":"\u003cp\u003eAdaptive strategies of \u003cem\u003eT. ramosissima\u003c/em\u003e under coppice dune development. MDA, malondialdehyde; NSC, non-structural carbohydrates; Pro, proline; SWC, soil water content. *, significant difference (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05); ns, not significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05). Hormones included zeatin and indole-3-acetate in the leaves of \u003cem\u003eT. ramosissima\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/f2663a462b7a864592afe0b8.png"},{"id":106405542,"identity":"0f00c1e2-6157-4373-a806-a71998a62b84","added_by":"auto","created_at":"2026-04-08 09:27:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3032888,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/2e1b7e13-3d5c-48f0-9fa0-64b1d4b96e91.pdf"},{"id":106094243,"identity":"60b124f6-231c-4de9-b7d2-02f53b466937","added_by":"auto","created_at":"2026-04-03 11:41:53","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":19920,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/9d0614b2c796883a3a191c10.docx"},{"id":106401993,"identity":"f885ff33-b1f0-4b94-948e-924f4d56bc14","added_by":"auto","created_at":"2026-04-08 09:10:34","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":29562,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/3c981f64a05747ac935cc943.docx"},{"id":105952712,"identity":"35e464d7-837e-4bde-adb1-53db29d3bac2","added_by":"auto","created_at":"2026-04-01 19:05:35","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24675,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.xls","url":"https://assets-eu.researchsquare.com/files/rs-9072853/v1/e6c6a958cec0c7831f249784.xls"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated transcriptomic and metabolomic analyses uncover the key pathways of Tamarix ramosissima in adaptation to coppice dune development","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGlobal climate change has intensified the spatiotemporal heterogeneity and regional asymmetry of precipitation, profoundly altering the fundamental processes of the global water cycle \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Arid regions face increasingly severe challenges, including shifts in precipitation patterns, elevated evaporative demand, and sustained declines in soil water availability \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. These changes drive groundwater depletion and land desertification, threatening vegetation survival and ecosystem stability \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Water scarcity coupled with soil impoverishment constitutes a primary constraint on desert plant growth \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. However, coppice dunes can mitigate these stresses by creating a \u0026ldquo;fertile island effect\u0026rdquo;, which improves local soil moisture, nutrient availability, and microtopography, thereby providing relatively favorable microhabitats for desert shrubs \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. To cope with water stress during the accumulation and development of coppice dune, desert plants typically activate complex antioxidant defense systems. These include enzymatic antioxidants like superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), as well as non-enzymatic substances such as proline (Pro), reduced glutathione, and ascorbic acid, which collectively scavenge excessive reactive oxygen species (ROS) to maintain cellular membrane stability and integrity \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo cope with drought stress and reduce tissue water loss, plants can synthesize osmoprotectants such as Pro, soluble protein (SP), and soluble sugar (SS), thereby lowering cellular osmotic potential, maintaining cell turgor, and facilitating water uptake \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Moreover, under continuous drought stress, plant photosynthesis is inhibited, and the synthesis of non-structural carbohydrates (NSC) is also restricted. When the rate of carbon consumption exceeds the capacity of carbon assimilation, carbon sources become gradually depleted, potentially exposing plants to the risk of carbon starvation and restricting normal physiological processes such as growth and osmotic adjustment \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. To balance the dual demands of carbon fixation and water conservation, plants employ adaptive resource allocation strategies. For instance, \u003cem\u003eNitraria sibirica\u003c/em\u003e and \u003cem\u003ePinus densiflora\u003c/em\u003e reallocate resources from growth to defense mechanisms under drought conditions \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Besides, Phytohormones, serving as central signaling molecules, orchestrate these physiological and metabolic adjustments to enhance drought tolerance \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Therefore, analyzing the integrated physiological and biochemical responses of desert plants is essential for elucidating their adaptation mechanisms to arid environments.\u003c/p\u003e \u003cp\u003eRecent advances in high-throughput sequencing have accelerated research into plant stress resistance. Integrated transcriptomic and metabolomic analyses have emerged as powerful tools for deciphering the underlying molecular mechanisms \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Specifically, Transcriptomics reveals the genetic regulation of metabolite biosynthesis, transport, and signaling \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, whereas metabolomics identifies and quantifies small-molecule metabolites, linking them to physiological changes \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Consequently, their combined analysis can reconstruct the complex regulatory network of \"gene expression\u0026mdash;metabolite accumulation\u0026mdash;phenotypic response\", enabling comprehensive elucidation of plant adaptation to adverse environments \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. This integrated strategy has been widely applied to study drought adaptation in desert plants such as \u003cem\u003eHaloxylon ammodendron\u003c/em\u003e, \u003cem\u003eHaloxylon persicum\u003c/em\u003e, \u003cem\u003eSalix psammophila\u003c/em\u003e, and \u003cem\u003eTamarix taklamakanensis\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. However, Species-specific genetic backgrounds drive distinct adaptive mechanisms. For instance, \u003cem\u003eH. ammodendron\u003c/em\u003e and \u003cem\u003eH. persicum\u003c/em\u003e enhance drought tolerance by upregulating pathways related to glycolysis/gluconeogenesis and amino acid synthesis \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In contrast, drought represses photosynthesis in \u003cem\u003eNitraria sibirica\u003c/em\u003e through the downregulation of genes encoding key components, including photosystem II (e.g., \u003cem\u003ePsbP\u003c/em\u003e, \u003cem\u003ePsbQ\u003c/em\u003e, \u003cem\u003ePsbR\u003c/em\u003e, \u003cem\u003ePsbY\u003c/em\u003e, \u003cem\u003ePsb27\u003c/em\u003e), photosystem I (e.g., \u003cem\u003ePsaD\u003c/em\u003e, \u003cem\u003ePsaF\u003c/em\u003e, \u003cem\u003ePsaG\u003c/em\u003e, \u003cem\u003ePsaH\u003c/em\u003e, \u003cem\u003ePsaK\u003c/em\u003e, \u003cem\u003ePsaO\u003c/em\u003e), photosynthetic electron transport (\u003cem\u003ePetF\u003c/em\u003e), and light-harvesting antenna proteins \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Meanwhile, \u003cem\u003eAmmopiptanthus nanus\u003c/em\u003e enhances drought resistance via ABA signaling transduction, achieved by downregulating \u003cem\u003ePYR/PYL\u003c/em\u003e and \u003cem\u003ePP2C\u003c/em\u003e genes and promoting ABA accumulation \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Collectively, these studies lay a crucial foundation for understanding the drought response mechanisms of desert plants.\u003c/p\u003e \u003cp\u003e \u003cem\u003eT. ramosissima\u003c/em\u003e, a keystone windbreak and sand-fixing shrub in arid regions, forms distinctive coppice dunes through long-term wind-sand interactions and plays a pivotal role in soil and water conservation, desertification control, and biodiversity maintenance \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The formation of these dunes is an extremely protracted process, often spanning centuries to over a millennium, during which dune heights increase from tens of centimeters to tens of meters. Based on morphological characteristics, the development of \u003cem\u003eTamarix\u003c/em\u003e coppice dunes typically proceeds through four stages: initial, growth, stable, and decline \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Notably, at the decline stage of coppice dunes, \u003cem\u003eT. ramosissima\u003c/em\u003e exhibits dwarfism, self-thinning, and degradation, ultimately losing its sand-fixing capacity \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. This transformation turns the dunes into sources of sandstorms, threatening both ecosystem integrity and human well-being. Consequently, in the context of global climate change, deciphering the physiological and molecular adaptation of \u003cem\u003eT. ramosissima\u003c/em\u003e to dune development is therefore critical for desert ecosystem conservation. Current research on \u003cem\u003eTamarix\u003c/em\u003e coppice dunes has primarily focused on soil nutrients, water-use strategies, and photosynthetic responses \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. However, the associated physiological metabolism, gene regulatory networks, and metabolite accumulation patterns in \u003cem\u003eT. ramosissima\u003c/em\u003e throughout dune development remain largely uncharacterized.\u003c/p\u003e \u003cp\u003eTherefore, this study focused on \u003cem\u003eT. ramosissima\u003c/em\u003e inhabiting coppice dunes at different developmental stages in the southwestern Gurbantunggut Desert. By integrating physiological trait analysis with transcriptomics and metabolomics, we elucidated the adaptive mechanisms underlying its response to dune development. Specifically, we addressed the following two questions: (1) What is the relationship between the physiological traits of \u003cem\u003eT. ramosissima\u003c/em\u003e and soil water content during this process? (2) What are the molecular bases of \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s adaptation to coppice dune development? Our findings advance the understanding of the physiological and molecular regulatory mechanisms behind \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s adaptation to dune development and provide valuable genetic resources for breeding drought-tolerant plants.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study site\u003c/h2\u003e \u003cp\u003eThe Gurbantunggut Desert (84\u0026deg;50'\u0026ndash;91\u0026deg;20' E, 44\u0026deg;15'\u0026ndash;46\u0026deg;50' N), located in the central Junggar Basin of Xinjiang, covers an area of approximately 4.88\u0026times;10⁴ km\u0026sup2; \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. It is dominated by fixed and semi-fixed dunes, which account for about 97% of its total area, making it the largest desert of this type in China \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. The region experiences a typical temperate continental climate characterized by hot summers and cold, snowy winters, with a stable snow cover period lasting 100\u0026ndash;150 days. The annual average temperature ranges from 6 to 10 ℃, while annual precipitation averages between 70 and 150 mm, far below the annual potential evaporation, which exceeds 2,000 mm. Vegetation coverage is relatively high, ranging from 40% to 50%, and includes over 200 species of drought-tolerant and ephemeral plants \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Dominant species consist of xerophytic and super-xerophytic shrubs, such as \u003cem\u003eHaloxylon ammodendron\u003c/em\u003e, \u003cem\u003eHaloxylon persicum\u003c/em\u003e, \u003cem\u003eEremosparton songoricum\u003c/em\u003e, and \u003cem\u003eAgriophyllum squarrosum\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Plot set up and sample collection\u003c/h2\u003e \u003cp\u003eWith local department permission, we established a 5 km \u0026times; 5 km experimental plot in the Mosuowan Desert Area (44\u0026deg;55\u0026prime; N, 86\u0026deg;12\u0026prime; E), at the southwestern edge of the Gurbantunggut Desert \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Using established dune classification criteria, we adopted the space-for-time substitution method and selected four developmental stages of \u003cem\u003eT. ramosissima\u003c/em\u003e coppice dunes: initial, growth, stable, and decline \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. For each stage, three replicate dunes were chosen, totaling 12 coppice dunes. Mature, intact, and pest-free leaf samples of \u003cem\u003eT. ramosissima\u003c/em\u003e were collected from the east-oriented middle canopy of the selected dunes. Sampling took place between 07:00 and 10:00 local time on July 12, 2024. All samples were immediately flash-frozen in liquid nitrogen and then transported to the laboratory for storage at -80 ℃ for subsequent analysis. We also measured the soil water content (SWC) at 0\u0026ndash;500 cm depth in coppice dunes of each developmental stage. Results showed that SWC decreased continuously as dune development progressed \u003cb\u003e(Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e. In addition, a meteorological station within 5 km of the study area confirmed that no precipitation occurred in the 37 days before sampling. This ensured that sampling took place under extreme aridity and high temperatures, minimizing the confounding effects of short-term climatic variability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Physiological indicator determination\u003c/h2\u003e \u003cp\u003eFollowing the method of Chang and Lv \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, after 0.1 g of plant leaf tissue was weighed, the activities of SOD, CAT, and POD were determined using the nitroblue tetrazolium (NBT) reduction, spectrophotometric, and guaiacol methods, respectively; the contents of Pro, SS, SP, and MDA were quantified using the sulfosalicylic acid, anthrone colorimetric, Coomassie brilliant blue (G-250), and thiobarbituric acid (TBA) methods, respectively. Starch (ST) content was measured by acid hydrolysis followed by anthrone colorimetric quantification and conversion to starch equivalents. Non-structural carbohydrates (NSC) content was calculated as the sum of SS and ST \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. All assays were performed with commercial kits (Grace Biotechnology Co., Ltd., Suzhou, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Metabolomic analysis\u003c/h2\u003e \u003cp\u003eApproximately 50 mg of frozen leaf tissue was ground at 45 Hz for 10 min, followed by sonication in an ice-water bath for 10 min and centrifugation at 12,000 rpm (4\u0026deg;C) for 15 min. The supernatant was collected, vacuum-dried, and then reconstituted in the extraction solution. The mixture was vortexed for 30 s, sonicated for 10 min in an ice-water bath, and centrifuged again. The final supernatant was used for LC-MS/MS analysis. Raw data files were processed using Progenesis QI software for peak extraction and alignment. Metabolites were identified by searching against the integrated METLIN database and public repositories, with confirmation based on theoretical fragment matching. They were subsequently annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG Database), the Human Metabolome Database (HMDB Database), and the Lipid Metabolites and Pathways Strategy (LIPID MAPS). Differentially accumulated metabolites (DAMs) were screened based on the following criteria: a variable importance in projection (VIP) value\u0026thinsp;\u0026gt;\u0026thinsp;1.0 from orthogonal partial least squares-discriminant analysis (OPLS-DA), fold change\u0026thinsp;\u0026ge;\u0026thinsp;1, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Transcriptomic analysis\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted using the Polysaccharide-Polyphenol Plant Total RNA Extraction Kit (Tiangen, China). mRNA libraries were constructed and sequenced on the Illumina NovaSeq Xplus platform. Raw reads were filtered to remove adapters and low-quality bases, yielding clean reads. De novo transcriptome assembly was performed using Trinity software \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. The assembled transcripts were clustered to remove redundancy using TGICL, generating a set of unigenes. Functional annotation of the unigenes was performed using BLAST searches against multiple databases, including NR, Swiss-Prot, COG, KOG, eggNOG, KEGG, GO, and Pfam. Transcription factors (TFs) were predicted using iTAK software \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Gene expression levels were quantified using the FPKM metric. Differentially expressed genes (DEGs) were identified with the DESeq2 package, applying thresholds of |log\u003csub\u003e2\u003c/sub\u003eFC| \u0026ge; 1 and False Discovery Rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Quantitative Real-Time PCR (qRT-PCR) validation\u003c/h2\u003e \u003cp\u003eA total of 12 DEGs associated with drought stress were randomly selected for quantitative real-time PCR (qRT-PCR) validation. Total RNA was extracted using a total plant RNA extraction kit (FOREGENE, China), and first-strand cDNA was synthesized with a corresponding reverse transcription kit (FOREGENE, China). qRT-PCR assays were performed using SYBR Green I Master Mix (FOREGENE, China) with \u003cem\u003eActin\u003c/em\u003e serving as the reference gene. The primer sequences used are listed in \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e. Relative expression levels were calculated using the 2\u003csup\u003e⁻ΔΔCT\u003c/sup\u003e method based on three independent biological replicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses of physiological data were performed using IBM SPSS Statistics 26. One-way analysis of variance (ANOVA) was conducted, followed by Duncan\u0026rsquo;s multiple-range test for post hoc comparisons, with a significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Graphs were constructed using Origin 2024. Hub genes within key co-expression modules were identified with the degree algorithm in the cytoHubba plugin for Cytoscape 3.7.1. Venn diagrams were generated using TBtools. All other bioinformatics analyses were performed on an online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.biocloud.net/\u003c/span\u003e\u003cspan address=\"https://www.biocloud.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Leaf physiological traits\u003c/h2\u003e \u003cp\u003eLeaf physiological and biochemical traits of \u003cem\u003eT. ramosissima\u003c/em\u003e varied significantly across the developmental stages of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. SP and Pro contents were significantly higher at the decline stage of coppice dunes compared to the initial and growth stages of coppice dunes \u003cb\u003e(\u003c/b\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, C\u003cb\u003e)\u003c/b\u003e. In contrast, SS content was highest at the growth stage of coppice dunes and lowest at the decline stage of coppice dunes \u003cb\u003e(\u003c/b\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. ST content of \u003cem\u003eT. ramosissima\u003c/em\u003e exhibited a gradual decrease with dune development, reaching its lowest level at the decline stage of coppice dunes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which represented a 52.6% reduction from the initial stage of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. NSC content was significantly higher at initial (24.68 mg/g) and growth (24.37 mg/g) stages of coppice dunes than at stable and decline stages of coppice dunes \u003cb\u003e(\u003c/b\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. Regarding antioxidant capacity, SOD activity peaked at growth and stable stages of coppice dunes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and was lowest at the decline stage of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI\u003cb\u003e)\u003c/b\u003e. In contrast, CAT activity showed the opposite trend, being highest at the decline stage of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH\u003cb\u003e)\u003c/b\u003e. MDA content was highest in plants at the decline stage of coppice dunes (27.66 nmol/g; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating the most severe membrane lipid peroxidation under environmental stress \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. These results indicate that the development of coppice dunes significantly affects the physiological characteristics of \u003cem\u003eT. ramosissima\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Metabolomic analysis\u003c/h2\u003e \u003cp\u003ePrincipal Component Analysis (PCA) revealed clear separation among the four dune developmental stages, with biological replicates closely clustered within the 95% confidence ellipse \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Furthermore, hierarchical clustering analysis demonstrated distinct, stage-specific patterns of metabolite accumulation across the developmental stages of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. DAMs statistics\u003c/h2\u003e \u003cp\u003eAcross all pairwise comparisons encompassing the four dune developmental stages, a total of 4,504 DAMs were identified \u003cb\u003e(Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e)\u003c/b\u003e. Specifically, 1,981 DAMs (1,076 upregulated, 905 downregulated), 547 DAMs (248 upregulated, 299 downregulated), 987 DAMs (423 upregulated, 564 downregulated), 867 DAMs (260 upregulated, 607 downregulated), 795 DAMs (284 upregulated, 511 downregulated), and 755 DAMs (459 upregulated, 296 downregulated) were identified in the pairwise comparisons of ISL vs GSL, ISL vs SSL, ISL vs DSL, GSL vs SSL, GSL vs DSL, and SSL vs DSL, respectively. Notably, the number of DAMs in \u003cem\u003eT. ramosissima\u003c/em\u003e gradually decreased across the comparisons of ISL vs GSL, GSL vs SSL, and SSL vs DSL, indicating that coppice dune development suppresses the metabolic regulatory capacity of \u003cem\u003eT. ramosissima\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Phytohormone content changes\u003c/h2\u003e \u003cp\u003eBased on previous reports linking specific metabolites to drought response, we focused on analyzing changes in plant hormone levels among drought-related DAMs. Venn analysis was performed on DAMs involved in the plant hormone signal transduction pathway. The results demonstrated that zeatin and indole-3-acetate were commonly identified across three comparison groups: ISL vs GSL, GSL vs SSL, and SSL vs DSL \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. In contrast, Dihydrozeatin was exclusively shared between the ISL vs GSL and SSL vs DSL groups \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Subsequently, the abundance dynamics of these three hormones were visualized to illustrate their accumulation patterns. We found that zeatin and indole-3-acetate levels exhibited a \u0026ldquo;rise\u0026ndash;fall\u0026ndash;rise\u0026rdquo; pattern across the dune developmental stages \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, D\u003cb\u003e)\u003c/b\u003e. Moreover, dihydrozeatin levels increased from the initial stage to the growth stage and from the stable stage to the decline stage \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Notably, all three hormones reached their peak concentrations at the decline stage of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-D\u003cb\u003e)\u003c/b\u003e. These results suggest that \u003cem\u003eT. ramosissima\u003c/em\u003e actively modulates its endogenous hormone homeostasis to activate stress-responsive signaling pathways, thereby adapting to the changing environment during coppice dune development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Transcriptome sequencing\u003c/h2\u003e \u003cp\u003eTranscriptome sequencing generated 72.52 Gb of high-quality clean data, with Q30 scores exceeding 95.26% and GC content above 43.19%, confirming high sequencing accuracy \u003cb\u003e(Table S4)\u003c/b\u003e. De novo assembly yielded 99,886 unigenes with an N50 length of 2,038 bp, indicating good transcriptome continuity. High consistency among biological replicates was confirmed by Pearson correlation coefficients (R\u0026sup2; \u0026gt; 0.95; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Functional annotation of unigenes\u003c/h2\u003e \u003cp\u003eAmong the assembled unigenes, 45,428 (45.48% of total) were successfully annotated against at least one of the eight public databases, while 7,036 unigenes obtained annotations from all databases \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. The eggNOG database provided the highest number of unique annotations, whereas the Gene Ontology (GO) database contributed the fewest exclusive annotations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.7. DEGs statistics\u003c/h2\u003e \u003cp\u003eAcross all pairwise comparisons encompassing the four dune developmental stages, a total of 24,881 DEGs were identified. Among of 15,302 DEGs (12,915 upregulated, 2,387 downregulated), 9,243 DEGs (6,978 upregulated, 2,265 downregulated), 14,325 DEGs (11,653 upregulated, 2,672 downregulated), 15,594 DEGs (3,370 upregulated, 12,224 downregulated), 15,974 DEGs (7,128 upregulated, 8,846 downregulated), and 15,504 DEGs (10,897 upregulated, 4,607 downregulated) were identified in the pairwise comparisons of ISL vs GSL, ISL vs SSL, ISL vs DSL, GSL vs SSL, GSL vs DSL, and SSL vs DSL, respectively \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Notably, upregulated DEGs predominated in comparisons involving ISL vs GSL and SSL vs DSL, whereas downregulated genes were markedly more abundant in GSL vs SSL. This pattern suggests that the progression from the growth to the stable stage of coppice dune is associated with a broad suppression of core metabolic processes. Transcription factor (TF) prediction identified hundreds of differentially expressed TFs in each comparison, with total counts ranging from 373 to 634 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. The C2H2 and bHLH families were consistently the most abundant among these TFs across all comparisons, indicating their pivotal roles in regulating \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s response to coppice dune development.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.8. qRT-PCR validation\u003c/h2\u003e \u003cp\u003eThe reliability of the RNA-seq expression data was validated by qRT-PCR analysis of 12 randomly selected DEGs related to drought stress. The results exhibited a high correlation (R\u0026sup2; \u0026gt; 0.94) between the two methods \u003cb\u003e(Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e, confirming the high consistency and robustness of the transcriptomic dataset.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.9. Integrated transcriptomic and metabolomic analysis identifies key pathways\u003c/h2\u003e \u003cp\u003eIntegrated transcriptomic and metabolomic analysis consistently revealed three co-enriched pathways across ISL vs GSL, ISL vs SSL, and ISL vs DSL, including glutathione metabolism (ko00480), ABC transporters (ko02010), and glycerophospholipid metabolism (ko00564) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u0026ndash;C\u003cb\u003e)\u003c/b\u003e. This highlights their crucial roles in \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s adaptation to the development of coppice dunes. DEGs expression within these pathways displayed distinct stage-specific patterns. In the glutathione metabolism pathway, most genes encoding glutathione S-transferase (16 upregulated, 3 downregulated), dehydroascorbate reductase (2 upregulated), and glutathione peroxidase (7 upregulated) were upregulated in ISL vs GSL; most were downregulated in GSL vs SSL (glutathione S-transferase: 4 upregulated, 14 downregulated; dehydroascorbate reductase: 2 downregulated; glutathione peroxidase: 3 upregulated, 7 downregulated); and re-upregulated in SSL vs DSL (glutathione S-transferase: 16 upregulated, 12 downregulated; dehydroascorbate reductase: 2 upregulated, 1 downregulated; glutathione peroxidase: 4 upregulated, 2 downregulated) (for detailed gene counts, see \u003cb\u003eTable S5\u003c/b\u003e). Correspondingly, the GSH/GSSG ratio (reduced-to-oxidized glutathione ratio) decreased from GSL to SSL but increased from SSL to DSL, reflecting dynamic shifts in cellular redox state \u003cb\u003e(Table S5)\u003c/b\u003e. Similarly, in both the ABC transporters and glycerophospholipid metabolism pathways, the predominant expression pattern for most genes was upregulated in ISL vs GSL, downregulated in GSL vs SSL, and subsequently re-upregulated in SSL vs DSL \u003cb\u003e(Table S6 and S7)\u003c/b\u003e. Venn analysis of metabolites associated with these pathways identified 17 key differential metabolites \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD, \u003cb\u003eTable S8)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.10. Hub gene identification via weighted gene co-expression network analysis (WGCNA)\u003c/h2\u003e \u003cp\u003eTo identify key gene modules linked to coppice dune development, we performed WGCNA by correlating DEGs expression matrices with the abundance of 17 key DAMs. Based on expression patterns, DEGs were clustered into eight distinct modules \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e, and a heatmap visualized the correlation strengths between these gene modules and the DAMs \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Among them, the MEturquoise and MEyellow modules showed the most significant correlations with the DAMs. Four drought response hub genes were identified based on gene connectivity within modules and the published literature. Of these, two were derived from the MEturquoise module \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA, B\u003cb\u003e)\u003c/b\u003e, while the remaining two originated from the MEyellow module \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC, D\u003cb\u003e)\u003c/b\u003e. These were \u003cem\u003eTRINITY_DN1805_c0_g1\u003c/em\u003e (\u003cem\u003eSAP4-like\u003c/em\u003e), \u003cem\u003eTRINITY_DN740_c1_g1 (EXO70B1)\u003c/em\u003e, \u003cem\u003eTRINITY_DN2662_c2_g1\u003c/em\u003e (\u003cem\u003eMAPKK5-like\u003c/em\u003e), and \u003cem\u003eTRINITY_DN4872_c1_g2 (bHLH47-like\u003c/em\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.11. Co-expression network analysis of molecular levels, physiological traits, and SWC\u003c/h2\u003e \u003cp\u003eA co-expression network was constructed based on Pearson correlation analysis among the screened DAMs, hub genes, phytohormone levels, physiological traits, and SWC. Strong correlations were observed, notably between hub genes and DAMs, as well as between DAMs and key physiological traits \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, \u003cb\u003eTable S9)\u003c/b\u003e. Furthermore, SWC exhibited a significant negative correlation with Pro, zeatin, dihydrozeatin, and indole-3-acetate (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but a significant positive correlation with ST (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). This pattern underscores the profound influence of soil water content on the physiological status of \u003cem\u003eT. ramosissima\u003c/em\u003e. MDA content was strongly positively correlated with Pro (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). It strongly negatively correlated with SS (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that increased membrane lipid peroxidation triggers Pro accumulation and SS consumption to alleviate oxidative damage. In addition, NSC content was strongly negatively correlated with SP, Pro, and MDA (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). It strongly positively correlated with SS and ST (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that there was a tight metabolic coupling between NSC and other stress-responsive compounds. Notably, ST content exhibited a significant negative correlation with zeatin, dihydrozeatin, and indole-3-acetate (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting a potential trade-off between starch consumption and the signaling or action of these growth-related hormones during adaptation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Physiological metabolic changes in T. ramosissima during coppice dune development\u003c/h2\u003e \u003cp\u003eThe formation and development of coppice dunes are mainly regulated by soil water content \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Our data show that SWC decreased gradually as coppice dunes developed \u003cb\u003e(Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e. Correspondingly, SP and Pro contents were lowest at the initial and growth stages of coppice dunes and highest at the decline stage of coppice dunes. Notably, NSC exhibited highly significant negative correlations with SP and Pro. These findings suggest that \u003cem\u003eT. ramosissima\u003c/em\u003e reallocates limited NSC resources away from growth and toward defense to adapt to the development of coppice dunes, prioritizing amino acid synthesis and transport, which in turn drives the accumulation of SP and Pro, thereby preventing water loss and maintaining osmotic balance \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. In contrast, SS content was lowest at the decline stage of coppice dunes, a finding that differs from reports in \u003cem\u003eCalligonum leucocladum\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. This discrepancy may reflect a species-specific strategy in which SS in \u003cem\u003eT. ramosissima\u003c/em\u003e shifts from osmotic regulation to energy provision as dune development progresses and drought intensifies \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eChanges in NSC content can reflect plants\u0026rsquo; carbon supply status and their adaptive strategies to environmental changes \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. Specifically, ST is an important component of NSC and serves as a long-term energy storage mechanism \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. In this study, we found that NSC content was lowest at the decline stage of coppice dunes. This result may stem from multiple factors: (i) stomatal closure under severe drought limiting photosynthetic carbon fixation \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e; (ii) NSC consumption for drought defense mechanisms \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e; and (iii) prioritization of resource allocation to the construction and storage of below-ground traits, which serve as a mobilizable energy reserve for growth and development after the alleviation of drought stress \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Correspondingly, field observations confirmed that \u003cem\u003eT. ramosissima\u003c/em\u003e failed to flower at the decline stage of coppice dunes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. This observed impaired reproductive capacity is likely due to insufficient NSC reserves, resulting from reduced photochemical efficiency under stress \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Finally, we also found that ST was significantly positively correlated with SWC, indicating that a decrease in SWC promoted the consumption and decomposition of ST to meet plants\u0026rsquo; energy demand.\u003c/p\u003e \u003cp\u003eAbiotic stress typically triggers excessive ROS accumulation, leading to oxidative damage to cellular membranes, proteins, and nucleic acids \u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. MDA, a product of membrane lipid peroxidation, serves as a key indicator of the extent of ROS-induced damage, while antioxidant enzymes function to prevent excessive ROS accumulation \u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e. In this study, the highest MDA content was observed in \u003cem\u003eT. ramosissima\u003c/em\u003e at the decline stage of coppice dunes. This elevation is likely attributed to two main reasons. On the one hand, SWC was at its lowest during this stage, which induced ROS production in leaves and subsequently triggered lipid peroxidation of membrane lipid \u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. On the other hand, the extensive dieback of \u003cem\u003eT. ramosissima\u003c/em\u003e on dunes led to the lowest canopy density, rendering the plants more susceptible to photoinhibition and resulting in the highest MDA content \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. To reduce oxidative damage, \u003cem\u003eT. ramosissima\u003c/em\u003e enhanced CAT activity, contributing to ROS homeostasis. However, a strong positive correlation was observed between Pro and MDA, with a negative correlation observed with SWC \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, suggesting that the enzymatic antioxidant system alone may be insufficient for timely ROS scavenging. Meanwhile, the concurrent increase in Pro likely serves dual purposes: osmotic adjustment and direct antioxidant defense, thereby helping stabilize ROS levels \u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Nevertheless, persistent drought stress ultimately overwhelms these protective mechanisms, leading to significant cellular damage, as reflected by elevated MDA content \u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e4.2.\u003c/b\u003e Endogenous hormone changes in T. ramosissima during coppice dune development\u003c/h2\u003e \u003cp\u003eZeatin, dihydrozeatin, and indole-3-acetate play crucial roles in regulating plant growth and development \u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. Among cytokinins, zeatin is the most active and ubiquitous \u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e. Zeatin and dihydrozeatin have both been shown to promote the division and differentiation of plant cells \u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e, whereas indole-3-acetate enhances plant height, increases branch number, and promotes biomass accumulation \u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e. Consistent with their known regulatory roles, our study revealed that \u003cem\u003eT. ramosissima\u003c/em\u003e dynamically regulated the levels of zeatin, dihydrozeatin, and indole-3-acetate throughout the development of coppice dunes. Specifically, during the transition from the initial to the growth stage of coppice dunes, these hormones accumulated \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. It is likely due to improvements in the rhizosphere microenvironment, such as the increase in coppice dunes volume and height, which provides extensive growth space for plant root systems, enhances water and nutrient uptake, and supports the development of larger aboveground biomass. Simultaneously, facilitates the temporary retention of additional moisture, while the formation of a biological soil crust reduces soil water evaporation \u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e. In addition, the \"fertile island\" effect promotes soil nutrient enrichment \u003csup\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e. These changes promote elevated hormone levels and increase aboveground biomass \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Conversely, from the growth to the stable stage of coppice dunes, the contents of zeatin and indole-3-acetate in \u003cem\u003eT. ramosissima\u003c/em\u003e decreased \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. This shift coincides with continuously declining SWC and may reflect a strategic reallocation of resources from vigorous vegetative growth towards maintenance and defense \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Notably, from the stable to the decline stage of coppice dunes, the contents of zeatin, dihydrozeatin, and indole-3-acetate in \u003cem\u003eT. ramosissima\u003c/em\u003e increased. This may be closely related to the dwarfism and withered branches caused by drought stress in \u003cem\u003eT. ramosissima\u003c/em\u003e. These morphological adjustments reduce overall water demand and may alter internal hormone homeostasis or signaling, ultimately serving as a survival mechanism to prolong viability under extreme stress. In addition, both SWC and ST content showed significant negative correlations with zeatin, dihydrozeatin, and indole-3-acetate, indicating that decreased SWC can act as a stress signal to promote hormone accumulation and trigger plant stress resistance mechanisms. Meanwhile, the growth-promoting effects of these endogenous hormones require ST consumption to meet energy demands.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Key metabolic pathways in T. ramosissima\u0026rsquo;s adaptation to coppice dune development\u003c/h2\u003e \u003cp\u003eThis study provides the first integrated transcriptomic and metabolomic profile of \u003cem\u003eT. ramosissima\u003c/em\u003e across the developmental stages of coppice dunes, generating 72.52 Gb of high-quality sequencing data that constitutes a valuable resource for \u003cem\u003eTamarix\u003c/em\u003e functional genomics. Our analysis found that glutathione metabolism, ABC transporters, and glycerophospholipid metabolism are key pathways co-enriched with both DEGs and DAMs, highlighting their central role in \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s adaptation to coppice dune development \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Notably, these pathways are highly conserved, aligning with core mechanisms reported in other plant species under drought stress \u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. This suggests a fundamental adaptive strategy across aridland plants.\u003c/p\u003e \u003cp\u003eDuring the transition from the initial to the growth stage of coppice dunes, SWC began to decline. In response, \u003cem\u003eT. ramosissima\u003c/em\u003e upregulated most genes in the glutathione metabolism pathway (e.g., encoding glutathione S-transferase, dehydroascorbate reductase, and glutathione peroxidase) to enhance redox homeostasis, stabilize the mitochondrial electron transport chain, and mitigate early oxidative stress. Furthermore, it activated the ABC transporters pathway (particularly ABCB, ABCC, and ABCG subfamilies), promoting the transport of secondary metabolites and hormones to support shoot and leaf morphogenesis \u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. We also found that levels of L‑proline and hydroxyproline associated with the ABC transporters pathway were upregulated, further corroborating their vital role in maintaining osmotic balance under drought stress \u003cb\u003e(Table S8)\u003c/b\u003e. In contrast, deoxyguanosine and D‑ribose were downregulated, indicating that drought exacerbates the risk of ROS-induced DNA damage \u003cb\u003e(Table S8)\u003c/b\u003e. The glycerophospholipid metabolism pathway was also induced, leading to upregulation of genes that facilitate cell division, membrane biosynthesis, and signal transduction, thereby supporting rapid growth and enhancing drought tolerance \u003csup\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/sup\u003e. As dunes progressed from the growth to the stable stage of coppice dunes, SWC continued to decrease. Reflecting a strategic shift, most DEGs in the three core pathways were downregulated. This may be because \u003cem\u003eT. ramosissima\u003c/em\u003e can preferentially allocate resources to other defense mechanisms that better ensure its survival. From the stable to the decline stage of coppice dunes, both SWC and NSC content decreased to their minimum levels, accompanied by substantial accumulation of MDA and an elevated GSH/GSSG ratio. Under these conditions, the plants upregulated the three metabolic pathways to repair membrane damage, enhance antioxidant capacity, and transport stress-related substances, thereby resisting drought stress.\u003c/p\u003e \u003cp\u003eIn summary, \u003cem\u003eT. ramosissima\u003c/em\u003e dynamically regulated the expression of key genes and metabolites in core metabolic pathways across different developmental stages of coppice dunes, ultimately enabling adaptation to microhabitat changes in arid environments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Hub genes mediating T. ramosissima\u0026rsquo;s drought response\u003c/h2\u003e \u003cp\u003eFour hub genes associated with \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s response to coppice dune development were identified via WGCNA \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The \u003cem\u003eTRINITY_DN2662_c2_g1\u003c/em\u003e (\u003cem\u003eMAPKK5-like\u003c/em\u003e) and \u003cem\u003eTRINITY_DN4872_c1_g2\u003c/em\u003e (\u003cem\u003ebHLH47-like\u003c/em\u003e) were identified in the MEturquoise module. Investigations in potato have revealed that overexpression of \u003cem\u003eStMAPKK5\u003c/em\u003e significantly increases relative water content, antioxidant enzyme activity, and Pro accumulation, while reducing MDA content, thereby enhancing drought tolerance \u003csup\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/sup\u003e. Furthermore, virus-induced gene silencing (VIGS)-mediated silencing of \u003cem\u003eGhMAPKK5\u003c/em\u003e in cotton accelerates wilting under salt and drought stress. In contrast, overexpression of \u003cem\u003eGhMAPKK5\u003c/em\u003e in \u003cem\u003eA. thaliana\u003c/em\u003e promotes root growth and seed germination \u003csup\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e. These findings suggest that \u003cem\u003eMAPKK5-like\u003c/em\u003e and \u003cem\u003ebHLH47-like\u003c/em\u003e may also contribute to improved drought tolerance in \u003cem\u003eT. ramosissima\u003c/em\u003e. Similarly, \u003cem\u003eTRINITY_DN1805_c0_g1\u003c/em\u003e (\u003cem\u003eSAP4-like\u003c/em\u003e) and \u003cem\u003eTRINITY_DN740_c1_g1\u003c/em\u003e (\u003cem\u003eEXO70B1\u003c/em\u003e) were identified from the MEyellow module. Prior research has demonstrated that overexpression of \u003cem\u003eZmSAP8\u003c/em\u003e and \u003cem\u003eMdSAP15\u003c/em\u003e enhances drought stress tolerance in \u003cem\u003eArabidopsis thaliana\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e. Consistently, in \u003cem\u003eA. thaliana\u003c/em\u003e, \u003cem\u003eExo70B1\u003c/em\u003e and \u003cem\u003eExo70B2\u003c/em\u003e positively regulate abscisic acid (ABA)- and mannitol-induced stomatal closure; overexpression of \u003cem\u003eVviExo70B\u003c/em\u003e in \u003cem\u003eVitis vinifera\u003c/em\u003e callus and \u003cem\u003eA. thaliana\u003c/em\u003e improves tolerance to drought and NaCl stress while increasing ABA sensitivity \u003csup\u003e[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e. Accordingly, we hypothesize that \u003cem\u003eSAP4-like\u003c/em\u003e and \u003cem\u003eEXO70B1\u003c/em\u003e may exert analogous functions in \u003cem\u003eT. ramosissima\u003c/em\u003e\u0026rsquo;s adaptation to water deficit. These results indicate that the four identified hub genes hold promise as candidate genes for enhancing drought tolerance in \u003cem\u003eT. ramosissima\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Limitations","content":"\u003cp\u003eThis study has several limitations that need to be explicitly acknowledged. First, plant roots play a key role in water and nutrient uptake under drought stress. However, this study mainly focused on leaf samples of \u003cem\u003eT. ramosissima\u003c/em\u003e and did not focus on root samples. Second, although WGCNA has revealed the potential role of hub genes in drought resistance regulation in depth, the present study did not conduct in situ functional validation experiments (e.g., gene overexpression, silencing, or knockout) in \u003cem\u003eT. ramosissima\u003c/em\u003e, nor did it perform heterologous expression validation in model plants (e.g., \u003cem\u003eA. thaliana\u003c/em\u003e), which limits the translational applicability of the research results. To address these limitations, future studies should integrate root transcriptome and metabolome analyses to provide a more comprehensive understanding of whole-plant adaptive strategies; second, overexpress or silence the identified hub genes and explore their effects on drought-related phenotypes.\u003c/p\u003e"},{"header":"6 Conclusions","content":"\u003cp\u003e(1) From the initial to the growth stage of coppice dunes, SWC gradually decreased, while the MDA content in \u003cem\u003eT. ramosissima\u003c/em\u003e increased. In response, \u003cem\u003eT. ramosissima\u003c/em\u003e resisted drought stress by enhancing SP and Pro contents and CAT activity.\u003c/p\u003e \u003cp\u003e(2) The decrease in SWC can promote the accumulation of zeatin, dihydrozeatin, and indole-3-acetate in \u003cem\u003eT. ramosissima\u003c/em\u003e, thereby accelerating starch consumption to meet plant growth demands.\u003c/p\u003e \u003cp\u003e(3) \u003cem\u003eT. ramosissima\u003c/em\u003e mainly coordinates gene expression and metabolite accumulation in the ABC transporters, glycerophospholipid metabolism, and glutathione metabolism pathways to adapt to coppice dune development.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAll abbreviations are defined upon first use in the manuscript.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eW.G. and H.Z. carried out experiments. Z.W. and J.Z. developed the research ideas and designed the experiments. Z.W. acquired funding and revised the manuscript. Y.X. and B.Z. contributed to the field data collection. W.G. wrote the manuscript with contributions from all other authors. The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe authors thank the Mosuowan Desert Research Station, the Xinjiang Special Environment Species Protection and Regulation Biology Laboratory (Xinjiang, China) for their support in conducting this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by the National Natural Science Foundation of China (32560395), the Natural Science Foundation project of Xinjiang Uygur Autonomous Region (2024D01A84), and the 2025 Bortala Prefecture Grass Germplasm Resources Census Entrusted Project (Bid Item Three) (CYZZ2025003).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Statement:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhang W, Furtado K, Wu P, Zhou T, Chadwick R, Marzin C, et al. 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Environmental and Experimental Botany. 2023;206:105175. https://doi.org/10.1016/j.envexpbot.2022.105175.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Transcriptome, Metabolome, Tamarix ramosissima, Coppice dune","lastPublishedDoi":"10.21203/rs.3.rs-9072853/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9072853/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cem\u003e Tamarix ramosissima \u003c/em\u003eis\u003cem\u003e \u003c/em\u003ea crucial windbreak and sand-fixing shrub species in the arid deserts of northwest China, where it helps stabilize the ecosystem by trapping dust and enriching soil nutrients. In this study, we systematically investigated the molecular mechanisms underlying \u003cem\u003eT. ramosissima\u003c/em\u003e’s transition through the four developmental stages (initial, growth, stable, and decline) of coppice dunes through integrated physiological, transcriptomic, and metabolomic analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e From the initial to the growth stage of coppice dunes, soil water content (SWC) gradually decreased, whereas the malondialdehyde (MDA) content in \u003cem\u003eT. ramosissima\u003c/em\u003eincreased. \u003cem\u003eT. ramosissima\u003c/em\u003e could resist drought stress by enhancing soluble protein (SP) and proline (Pro) contents and catalase (CAT) activity. In addition, the decrease in SWC can promote the accumulation of zeatin, dihydrozeatin, and indole-3-acetate in \u003cem\u003eT. ramosissima\u003c/em\u003e, thereby accelerating starch consumption to meet plant growth demands. Transcriptome and metabolome analyses revealed that \u003cem\u003eT. ramosissima\u003c/em\u003e primarily coordinates gene expression and metabolite accumulation through the ABC transporters, glycerophospholipid metabolism, and glutathione metabolism pathways to adapt to coppice dune development; meanwhile, four hub genes identified by weighted gene co-expression network analysis (WGCNA) are promising candidates for improving drought tolerance in this species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This study reveals that \u003cem\u003eT. ramosissima\u003c/em\u003e can adapt to coppice dune development by coordinating gene expression, metabolite accumulation, and physiological regulations. The results provide an important theoretical basis for ecological restoration in arid regions.\u003c/p\u003e","manuscriptTitle":"Integrated transcriptomic and metabolomic analyses uncover the key pathways of Tamarix ramosissima in adaptation to coppice dune development","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-01 19:05:29","doi":"10.21203/rs.3.rs-9072853/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-15T02:17:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T03:56:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162511959887951287859383484232546326806","date":"2026-04-01T01:33:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"27188698740665745723401880533913848597","date":"2026-03-31T10:58:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295817890050439514216469576756995858315","date":"2026-03-31T03:12:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-30T15:00:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-19T11:15:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T11:11:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-17T10:37:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2026-03-17T09:53:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3700c039-4a2f-4b28-a1df-dae354118280","owner":[],"postedDate":"April 1st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T19:05:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-01 19:05:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9072853","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9072853","identity":"rs-9072853","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}