Temporal Transcriptomic and Lipidomic Analysis Reveals Multi-Omics Dynamic Profiles of Brassica napus Seed Germination

Temporal Transcriptomic and Lipidomic Analysis Reveals Multi-Omics Dynamic Profiles of Brassica napus Seed Germination | 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 Temporal Transcriptomic and Lipidomic Analysis Reveals Multi-Omics Dynamic Profiles of Brassica napus Seed Germination Bo Zhang, Junyan Wu, Li Ma, Haiqing Liu, Wancang Sun, Jianfeng Duan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9166678/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Lipids constitute a major component of Brassica napus seeds. During seed germination, lipid mobilization serves as a critical energy source for seedling establishment, which directly impacts germination vigor and the subsequent growth potential of seedlings. Although lipid mobilization is essential for rapeseed germination, the time-dependent coordination between transcriptional regulation and lipid conversion remains largely unclear, and the corresponding molecular regulatory network still needs to be systematically explored. Results We conducted an integrated transcriptomic and lipidomic analysis on dry B. napus seeds and germinating seeds at 6, 12, 24, and 48 hours after imbibition. The results revealed distinct stage-specific characteristics of gene expression and lipid metabolism during germination. In the early imbibition stage, differentially expressed genes (DEGs) were primarily enriched in biological processes related to water transport, stress response, and signal transduction, whereas significant changes in lipid metabolism were observed to be relatively delayed. During the initiation of germination, triacylglycerols (TAGs) underwent rapid degradation, accompanied by a significant up-regulation of genes involved in the β-oxidation and gluconeogenesis pathways. In the late germination stage, genes responsible for membrane lipid synthesis were sharply up-regulated, which induced extensive membrane lipid remodeling. Conclusion This study is the first to depict the dynamic multi-omics profile during B. napus seed germination, systematically illustrating the global molecular and metabolic features of B. napus seeds at different imbibition stages. It also clarifies the expression patterns of characteristic genes and lipid metabolites at each stage of germination. These findings further deepen our systematic understanding of the regulatory mechanisms governing B. napus seed germination, and provide valuable theoretical support as well as candidate gene resources for the breeding of high-yield and high-quality B. napus varieties. Lipids Seed germination Transcriptomic and Lipidomic Brassica napus.L Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Seed germination, a key early event in the plant life cycle, directly governs crop emergence, seedling uniformity, and subsequent growth potential, exerting profound effects on the final yield and quality of crops [ 1 , 2 ] . As an important oilseed crop worldwide, Brassica napus L. seeds are rich in lipids, serving as a vital source of edible vegetable oil, animal feed, and bioenergy [ 3 , 4 ] . In contrast to cereal crops, stored lipid mobilization and metabolism serve as a major source of energy for B. napus seed germination [ 5 , 6 ] . Dynamic lipid degradation, transport and transformation processes are key prerequisites for successful seed germination and the seamless establishment of seedlings [ 7 ] . Uncovering the ‌regulatory mechanism‌ of lipid metabolism during seed germination can thus provide a ‌theoretical basis‌ for the genetic improvement and ‌accelerated breeding‌ of oilseed crops. Triacylglycerols (TAGs) represent the primary storage lipid in B. napus seeds and play two core roles during germination. On one hand, stored lipids are catabolized via a cascade of metabolic reactions to generate energy substrates, which supply the energy required for seed imbibition, radicle emergence, and early seedling growth [ 8 ] . On the other hand, intermediate metabolites from lipid metabolism act as precursors for the synthesis and remodeling of cell membranes. These processes are critical for maintaining cellular structural integrity and fluidity, which in turn ensures the proper execution of essential physiological processes such as cell division and differentiation. [ 9 ] . Current understanding of the molecular regulatory mechanisms underlying seed germination remains partial, with several core pathways and key genes identified to mediate this process. In the hormone signaling pathway, GA promotes the expression of germination-related genes and breaks seed dormancy, while ABA represses germination [ 10 – 12 ] . In the lipid metabolic pathway, lipid hydrolysis, β-oxidation and gluconeogenesis act synergistically to convert stored lipids into energy and carbon sources, thus fueling seed germination [ 13 , 14 ] . In this study, we set multiple consecutive time points and integrated transcriptomic and lipidomic analyses to characterize the dynamic temporal and synergistic changes in gene expression and lipid metabolic profiles during B. napus seed imbibition and germination. We further identified core genes and characteristic lipid molecules associated with different germination stages, as well as core nodes potentially involved in mediating seed germination. These findings may provide a preliminary theoretical basis for the genetic improvement of seed germination traits in B. napus . Methods Plant Materials and Sample Collection In this study, B. napus seeds (cultivar LY80) with a genetically stable background were freshly harvested in the same year, fully dried, and then hermetically stored at 4 ℃. Prior to germination, plump, intact seeds of uniform size were disinfected with 75% ethanol, rinsed thoroughly with sterile water for five times, and then placed in Petri dishes lined with double layers of filter paper for germination in a constant-temperature incubator at 25 ℃ in the dark. Samples were collected at 0 h (dry seeds), 6 h, 12 h, 24 h and 48 h after seed imbibition, with approximately 0.2 g of mixed seeds designated as one independent biological replicate and three biological replicates prepared for each time point. All samples were snap-frozen in liquid nitrogen and stored at -80 ℃ for subsequent transcriptomic and metabolomic analyses. RNA-sequencing (RNA-seq) analysis In this study, Total RNA was isolated and checked for integrity using an Agilent 2100 Bioanalyzer. cDNA libraries were constructed and sequenced on an Illumina NovaSeq 6000 to generate 150‑bp paired‑end reads. Clean reads were mapped to the B. napus reference genome, and DEGs were identified using DESeq2 with Benjamini–Hochberg correction. Genes with padj = 1 were defined as significantly DEGs in this study. KEGG (Kyoto Encyclopedia of Genes and Genomes) annotations, the enrichment analysis of differentially expressed genes (DEGs) were performed using cluster Profiler (3.8.1). Lipid Extraction and UHPLC-MS/MS analyses Total lipids were extracted from rapeseed seeds via a modified MTBE method. In brief, 100 mg liquid nitrogen-ground seed powder was vortexed with 0.75 mL methanol, blended with 2.5 mL MTBE and shaken for 60 min at room temperature. Then 0.625 mL chromatography-grade water was added for phase separation, and the mixture was left standing for 10 min [15] . The separated aqueous phase was re-extracted with 1 mL of a mixed solvent (MTBE/methanol/water, 10:3:2.5, v/v/v). The combined organic phases were dried and redissolved in 100 μL of isopropanol for storage, and then subjected to analysis by LC-MS/MS.UHPLC-MS/MS analyses were performed using a Vanquish UHPLC system (Thermo Fisher, Germany) and an Orbitrap Q ExactiveTM HF mass spectrometer (Thermo Fisher, Germany). Samples were injected onto a ThermoAccucore C30 column (150×2.1mm, 2.6μm) using a 20-min linear gradient at a flow rate of 0.35mL/min. The column was maintained at 40 °C. Mobile phase A was acetonitrile–water (6:4) with 10 mM ammonium acetate and 0.1% formic acid; phase B was acetonitrile–isopropanol (1:9) with the same additives. The gradient program was: 30% B (0–2 min), 43% B (5 min), 55% B (5.1 min), 70% B (11 min), 99% B (16 min), and re-equilibrated to 30% B at 18.1 min [16] . Q ExactiveTM HF mass spectrometer was operated in positive[negative] polarity mode with sheath gas :40 psi, sweep gas: 0 L/min, auxiliary gasrate: 10 L/min[7 L/min], spray voltage: 3.5 kV, capillary temperature: 320℃, heater temperature: 350℃, S-LensRF level: 50, scan range: 114–1700 m/z, automatic gain control target: 3e6, normalized collisionenergy: 22eV; 24 eV; 28eV [22 eV；24 eV；28 eV], Injection time: 100 ms, Isolation window:1m/z, automatic gaincontrol target (MS2): 2e5, dynamic exclusion: 6s. Lipidomic data analysis The raw data files generated by UHPLC-MS/MS were processed using the Lipidsearch. Principal components analysis (PCA) and Partial least squares discriminant analysis (PLS‐DA)were performed at metaX (a flexible and comprehensive software for processing metabolomicsdata). We applied univariate analysis (t-test) to calculate the statistical significance (P-value). Themetabolites with VIP > 1 and P-value< 0.05 and fold change≥ 2 or FC≤ 0.5 were considered tobe differential metabolites. Volcano plots were used to filter metabolites of interest which based on Log2(FC) and -log10(P-value) of metabolites.For clustering heat maps, the data were normalized using z-scores of the intensity areas ofdifferential metabolites and were ploted by Pheatmap package in R language. The correlationbetween differential metabolites were analyzed by cor () in R language (method = pearson).Statistically significant of correlation between differential metabolites were calculated bycor.mtest()in in R language. P-value < 0.05 was considered as statistically significant andcorrelation plots were ploted by corrplot package in R language. RNA Extraction and Quantitative RT-PCR Total RNA was extracted from 0.2 g rapeseed powder with RNAiso Plus. RNA purity was quantified using a NanoDrop 200, and 2 μg RNA was reverse-transcribed into cDNA. qRT-PCR was performed with Actin as the internal reference. Three biological and technical replicates were set, and relative expression levels were determined via the comparative 2−ΔΔCt threshold method [17] . Results Seed morphology and water content of after imbibition To clarify the temporal characteristics of B. napus seed imbibition and germination, we divided the process into sequential stages based on morphological observation and water content determination(Fig. 1 ). Dry seeds had a water content of 6.82%, which increased rapidly to 28.57% within 6 h, with slight seed swelling but intact seed coat and no radicle protrusion. From 6–12 h, water absorption slowed, reaching 39.24% at 12 h (Fig. 1 C), accompanied by continued swelling, softened seed coat and embryo expansion without seed coat rupture. Between 12–24 h, water content stabilized at 35.11%–42.38% (Fig. 1 D), with radicle protrusion and slight seed coat cracking. After 24 h, water content remained stable, with rapid radicle elongation to at 48 h, hypocotyl stretching and complete seed coat rupture (Fig. 1 F). Temporal characteristics of seed imbibition lay a fundamental foundation for subsequent omics detection and analysis. Global Dynamic Changes of Transcriptome During Seed Imbibition and Germination To systematically explore the transcriptional dynamics during B. napus seed imbibition and germination, transcriptome sequencing was performed on seed samples at 0 h, 6 h, 12 h, 24 h, and 48 h after imbibition, with three biological replicates per time point. Quality assessment revealed that the Q30 score for all sequencing libraries exceeded 97.36%, and the GC content ranged from 46.29% to 47.04%, indicating high sequencing accuracy and reliability, which met the requirements for subsequent bioinformatics analysis(Table 1 ). Meanwhile, transcriptome sequencing reads were aligned to the B. napus reference genome. The Total_map (≥ 91.75%) and Unique_map (≥ 84.59%) of all samples fell within a reasonable high-value range with good alignment efficiency, demonstrating high reliability of the sequencing data and its suitability for subsequent analyses. Principal Component Analysis (PCA) was adopted to assess the overall differences and repeatability of transcriptomic patterns among samples at different germination stages. The results showed that samples of the same time point were closely clustered together, reflecting good reproducibility of biological replicates. Notably, samples of different time points were clearly separated along the first principal component (PC1, explaining 63.71% of the total variation)(Figure S1 ), which indicated that the transcriptional profiles changed significantly with the progression of seed imbibition and germination, and the samples were well distinguished by the time sequence, laying a foundation for the subsequent analysis of differential gene expression. Table 1 Quality and genome alignment statistics of transcriptome data Sample Clean_reads Error_rate Q20 Q30 GC_pct Total_map Unique_map Im0R1 68807008 0.01 99.44 97.65 47.04 63748432(92.65%) 58491777(85.01%) Im0R2 71868122 0.01 99.39 97.47 46.67 66516572(92.55%) 60790905(84.59%) Im0R3 71232200 0.01 99.36 97.47 46.73 65579636(92.06%) 60256477(84.59%) Im6R1 75799360 0.01 99.39 97.48 46.96 69910950(92.23%) 65035249(85.8%) Im6R2 74211060 0.01 99.39 97.54 46.76 68278888(92.01%) 63402952(85.44%) Im6R3 75960730 0.01 99.37 97.36 46.92 69885929(92.0%) 64409897(84.79%) Im12R1 75916102 0.01 99.42 97.54 46.45 69896072(92.07%) 65302548(86.02%) Im12R2 76203644 0.01 99.38 97.49 46.29 69916393(91.75%) 65546390(86.01%) Im12R3 74881814 0.01 99.42 97.54 46.38 68977426(92.12%) 64707700(86.41%) Im24R1 75852410 0.01 99.41 97.47 46.69 70150592(92.48%) 66070476(87.1%) Im24R2 74776434 0.01 99.42 97.6 46.64 69196973(92.54%) 65068678(87.02%) Im24R3 76766098 0.01 99.45 97.53 46.69 71101624(92.62%) 66878307(87.12%) Im48R1 73803716 0.01 99.44 97.58 46.99 68631698(92.99%) 64762903(87.75%) Im48R2 71675682 0.01 99.41 97.53 46.96 66525494(92.81%) 62620014(87.37%) Im48R3 74436288 0.01 99.41 97.5 47.02 69119002(92.86%) 65291130(87.71%) In this study, differentially expressed genes (DEGs) among different time points were identified using the criteria of |log2(fold change)| ≥ 1 and adjusted P-value < 0.05. The number of DEGs varied with imbibition time: compared with the 0 h dry seed control, the numbers at 6 h, 12 h, 24 h, and 48 h exhibited an increasing trend(Fig. 2A)(Table S1 ). A Venn diagram analysis was performed to clarify the overlap of DEGs among different time points(Fig. 2B), and the results showed that only 404 DEGs were commonly expressed across all four comparison groups (Im6h vs Im0h, Im12h vs Im6h, Im24h vs Im12h, Im48h vs Im24h), indicating that most DEGs were specifically expressed at different germination stages. Hierarchical clustering analysis of all DEGs showed that transcriptional patterns were highly similar between dry seeds and seeds at 6 h of imbibition, whereas the clustering results at all other time points differed considerably from one another, which further confirms that transcriptional changes are time-dependent during imbibition(Fig. 2C). . Figure 2. Analysis of gene expression in B. napus seeds at different imbibition stages. (A) Statistics of the number of significantly altered transcripts between successive stages in rapeseed seeds after imbibition. (B) Venn diagram analysis showing the overlap of differentially expressed genes (DEGs) between successive stages in rapeseed seeds after imbibition. (C) Hierarchical clustering heatmap of expressed genes at different stages in B. napus seeds after imbibition.the ordinate shows the FPKM-normalized values of differentially expressed genes; the redder the color, the higher the expression level, and the bluer the color, the lower the expression level. To reveal the biological roles of DEGs during seed imbibition and germination, we performed GO functional classification and KEGG pathway enrichment analysis for DEGs identified at each sampling stage. GO enrichment analysis revealed stage-specific enrichment of DEGs during seed imbibition: DEGs at 6 h were mainly enriched in water transport, water stimulus response and cell wall organization-related biological processes; 12 h DEGs in protein folding, ribosome biogenesis and RNA processing; 24 h DEGs in lipid catabolism and energy metabolism; and 48 h DEGs were significantly enriched in cell division, cell elongation and hormone-mediated signaling pathways(Figure S2). KEGG pathway enrichment analysis also highlighted distinct metabolic and signaling dynamics across stages. At 6 h, the most significantly enriched pathways were MAPK signaling, ABC transporters and phenylpropanoid biosynthesis, reflecting early stress responses and secondary metabolism(Fig. 3 A). By 12 h, ribosome biogenesis, porphyrin metabolism and sulfur metabolism dominated, indicating active protein synthesis and fundamental metabolic activation(Fig. 3 B). At 24 h, starch and sucrose metabolism, glutathione metabolism and DNA replication were prominent, supporting the transition to active growth(Fig. 3 C). By 48 h, intensive carbon metabolism, including starch and sucrose metabolism and pentose and glucuronate interconversions, along with phenylpropanoid biosynthesis and secondary metabolite production, was observed, underpinning cell expansion and organogenesis(Fig. 3 D). Collectively, these results illustrate a dynamic transcriptional and metabolic reprogramming process that drives seed imbibition and the initiation of germination. Global Dynamic Changes of Lipidome During Seed Imbibition and Germination To systematically characterize the lipidomic dynamics during B. napus seed imbibition and germination, lipidomic profiling was performed on the same seed samples as transcriptomic analysis, with three biological replicates per time point. A total of 1733 lipid molecules were identified across all samples, belonging to 15 major lipid classes, among which Triacylglycerol (TG) accounted for the highest proportion (16.40%), followed by Phosphatidylcholine (PC, 12.47%) and Diacylglycerol (DG, 9.82%)(Fig. 4 A). PCA was conducted to evaluate the similarity of lipidomic profiles among samples, and the results showed that biological replicates of the same time point were closely clustered. Samples of different germination stages were clearly separated along PC1, which explained 46.62% of the total variation, suggesting significant temporal changes in lipid composition during seed imbibition and germination(Fig. 4 B). Additionally, KEGG pathway annotation of all identified metabolites revealed that lipid metabolism was the most enriched pathway, containing 1253 annotated metabolites, followed by global and overview maps and the digestive system, highlighting the central role of lipid metabolism during seed imbibition and germination(Fig. 4 C). Lipidmaps annotation demonstrated that glycerophosphocholines (GP01, PC) were the most abundant lipid subclass, followed by glycerophosphoethanolamines (GP02) and glycerophosphates (GP10)(Fig. 4 D), Glycerolipidsand sphingolipids were also detected, confirming the dominance of phospholipids in membrane structure and the role of glycerolipids as storage and energy sources. The hierarchical clustering heatmap (Fig. 5 A) revealed distinct temporal patterns in lipid metabolite abundance across imbibition stages, with clear clusters of lipids showing increasing or decreasing abundance over time, reflecting dynamic lipid remodeling during seed imbibition and germination, Differential lipids are enriched in different imbibition stages(Table S2). K-means clustering (Fig. 5 B) further grouped these differential lipids into four subclusters: Subcluster 1 (110 metabolites) showed continuous accumulation, Subcluster 2 (450 metabolites) gradually increased and peaked at 24 h, Subcluster 3 (126 metabolites) remained relatively stable, and Subcluster 4 (99 metabolites) exhibited a sustained decrease, consistent with the breakdown of storage lipids to fuel germination; together, these findings illustrate the coordinated, stage-specific lipid metabolic changes that underpin seed imbibition and germination, aligning closely with our transcriptomic observations. To dissect the temporal dynamics of lipid metabolism during seed imbibition and germination, we performed KEGG pathway annotation of lipid metabolites across four key time points. The analysis revealed a progressive activation of lipid metabolism: at 6 h (Figure. 6A), lipid metabolism was moderately represented (210 metabolites) alongside active glycan biosynthesis and core metabolic networks, reflecting the initial phase of water uptake and stress response; by 12 h (Figure. 6B), lipid metabolism activity temporarily declined (15 metabolites) as the seed prioritized core metabolic maintenance; at 24 h (Figure. 6C), lipid metabolism reactivated (18 metabolites) to support membrane repair and early growth; and by 48 h (Figure. 6D), it emerged as the most dominant pathway (92 metabolites), which aligns with transcriptomic observations of enhanced lipid catabolism to provide energy and metabolic precursors for the transition to active germination. This temporal progression demonstrates a tightly coordinated metabolic response that underpins seed imbibition and germination, with strong consistency between lipidomic and transcriptomic data. WGCNA analysis of DEGs To identify the potential regulatory network related to lipid metabolism and seed germination in B. napus , weighted gene co-expression network analysis (WGCNA) was performed. Genes with low expression were filtered out, and the remaining genes were used to construct a scale-free network. A total of 10 distinct co-expression modules were identified by hierarchical clustering(Fig. 7 A). Module–trait correlation analysis showed that the MEblue module was strongly positively correlated with the catabolism of energy-storing substances such as lipids and carbohydrates, while The black module was associated with growth processes including membrane lipid biosynthesis(Fig. 7 B). The inter-module correlation heatmap illustrated the relationships among the identified co-expression modules. Most modules exhibited weak to moderate correlations with one another, indicating that they participate in distinct biological processes(Fig. 7 C). qRT-PCR Validation of Transcriptomic Data To confirm the credibility of transcriptome data, eight genes involved in lipid metabolism were selected for qRT-PCR detection(Fig. 8 ). These genes exhibited either significant upregulation or downregulation across imbibition stages, including those showing marked decreases in early imbibition (BnaA08G0155600ZS, BnaA03G0274900ZS) and those displaying increases over time (BnaA05G0136600ZS). The qRT-PCR expression profiles of these genes were fully consistent with their transcriptomic profiles, a strong correlation that supports the robustness of our transcriptomic analysis and the validity of the stage-specific transcriptional changes observed during seed imbibition. Discussion The Early Stage of Seed Germination is an Active Transcriptional Preparation Stage In the rapid imbibition stage (0–6 h), DEGs identified by transcriptomic analysis were mainly enriched in biological processes such as water transport, response to water stimulus, and cell wall organization. The early imbibition stage was accompanied by initial lipid metabolic remodeling; however, transcriptional regulation at this stage appeared to focus more on laying a structural and environmental foundation for subsequent lipid metabolism and seed germination, rather than on active lipid catabolism.The activation of these DEGs may be closely associated with the rapid water absorption and swelling of B. napus seeds, a physiological process that is particularly critical for this oilseed crop. Unlike cereal crops, B. napus seed germination relies predominantly on stored lipids for energy supply, and the normal progression of early imbibition may directly determine whether subsequent lipid mobilization and metabolism can proceed smoothly [ 17 – 19 ] .Specifically, genes related to water transport may promote the rapid penetration of water into seed cells, which not only helps break the dormant state of dry seeds but also may activate the activity of hydrolases that are prerequisites for subsequent lipid hydrolysis [ 20 , 21 ] . Potential Temporal Regulation of TAG Degradation and Energy Supply Conversion Data from both transcriptomics and lipidomics indicated that there may be a precise temporal coordination mechanism between biochemical pathways such as β-oxidation and gluconeogenesis during B. napus seed germination, and this mechanism might ensure the continuous supply of energy and carbon skeletons required for seed germination and seedling establishment. As the main storage lipid in B. napus seeds, triacylglycerols (TAGs) serve as the core energy source during germination, the germination and early seedling establishment of B. napus are highly dependent on the efficient mobilization and metabolic conversion of TAGs, making the putative precise temporal regulation of TAG degradation particularly critical [ 22 – 24 ] . Our results showed that the stepwise degradation of TAGs and their subsequent metabolic conversion are likely regulated by temporal programs at both the transcriptional and metabolic levels, which was well illustrated by the dynamic changes in KEGG pathway annotations across different imbibition stages.Specifically, at the early imbibition stage (0–6 h), transcriptomic analysis indicated that DEGs were mainly enriched in water transport and cell wall organization processes, while lipidomic profiles and KEGG annotations (Fig. 3 A) showed only initial lipid metabolic remodeling without active TAG degradation. This suggests that the transcriptional regulation at this stage prioritizes the establishment of a stable physiological environment for subsequent TAG mobilization, rather than immediate energy supply conversion [ 25 ] . 3.3 Enhancing Seed Germination Quality to Improve Yield Seed germination is the foundational stage of the plant life cycle, directly determining crop emergence rate, seedling uniformity, and subsequent growth potential, which in turn affects final crop yield and quality [ 26 , 27 ] . For B. napus , an important oil crop and alternative protein source worldwide, the efficiency of seed germination and early seedling establishment is not only closely related to its yield and product quality but also plays a vital role in maintaining the stability of global oil supply and food security, especially under the context of increasing population pressure and deteriorating environmental conditions [ 3 , 28 , 29 ] . For B. napus , an important oil crop and alternative protein source worldwide, the efficiency of seed germination and early seedling establishment is not only closely related to its yield and product quality but also plays a vital role in maintaining the stability of global oil supply and food security, especially under the context of increasing population pressure and deteriorating environmental conditions [ 28 ] . From the perspective of rapeseed breeding practice, enhancing seed germination quality through molecular breeding strategies is a direct and effective approach to improve yield. The core genes and characteristic lipid metabolic markers identified by integrated multi-omics analysis can be used as potential molecular targets for breeding rapeseed varieties with superior germination performance [ 29 ] . Enhancement of seed germination quality can effectively elevate the field emergence rate, optimize the population structure, and improve the efficiency of resource utilization, thereby increasing the per unit area yield of B. napus without the need for cultivated land expansion. Conclusions This study systematically presents the global molecular and metabolic characteristics of B. napus seed germination at different imbibition stages via integrated transcriptomic and lipidomic analyses, clarifying the expression patterns of characteristic genes and lipid metabolites in each stage. It further deepens the systematic understanding of the regulatory mechanisms underlying B. napus seed germination, and provides theoretical support and candidate gene resources for high-yield and high-quality rapeseed breeding. Abbreviations TG: Triacylglycerol PC: Phosphatidylcholine DG: Diacylglycerol CL: Cardiolipin Cer: Ceramide PE: Phosphatidylethanolamine PI: Phosphatidylinositol PG: Phosphatidylglycerol PA: Phosphatidic acid FA: Fatty acid PS: Phosphatidylserine MGDG: Monogalactosyldiacylglycerol DGDG: Digalactosyldiacylglycerol PMt: Phosphatidylmethanol / Phytomelatonin PFAA: Perfluoroalkyl acid / Polyunsaturated fatty acid LPC: Lysophosphatidylcholine SQDG: Sulfoquinovosyldiacylglycerol GO: Gene Ontology KEGG: Kyoto Encyclopedia of Genes and Genomes WGCNA Weighted Gene Co-Expression Network Analysis Declarations Acknowledgements Not applicable Author Contributions: BZ conceived the project and research plans; BZ, JW and LM performed the experiments; BZ, LM and HL analyzed the data; BZ wrote the article; BZ, JD and WS critically revised the manuscript. Funding: This work is supported by the Technology Fund Project (24JRRM025). Availability of data and material All transcriptomic and lipidomic data generated in this study have been deposited in the National Center for Biotechnology Information (NCBI) public databases to ensure free and open access for all researchers. The transcriptomic sequencing data are available in the Sequence Read Archive (SRA) database under the accession number [SRR37226466, SRR37226465, SRR37226464, SRR37226463, SRR37226462, SRR37226461, SRR37226460, SRR37226459, SRR37226458, SRR37226457, SRR37226456, SRR37226455, SRR37226454, SRR37226453, SRR37226452]. All data can be accessed freely upon publication to facilitate related research on B. napus seed germination and lipid metabolism, and to provide support for rapeseed genetic improvement and breeding. Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare no competing interests. References Sharma EM, Majee. Seed germination variability: why do genetically identical seeds not germinate at the same time? J Exp Bot. 2023;74:3462–75. Begum K, Shammi NHM. Selective biotic stressors’ action on seed germination: A review. Plant Sci. 2024;346:112156. Tan Z, Han X, Dai C, Lu S, He H, Yao X, Chen P, Yang C, Zhao L, Yang Q-Y, Zou J, Wen J, Hong D, Liu C, Ge X, Fan C, Yi B, Zhang C, Ma C, Liu K, Shen J, Tu J, Yang G, Fu T. GuoH. Zhao, Functional genomics of Brassica napus: Progress, challenges, and perspectives. J Integr Plant Biol. 2024;66:484–509. Gu J, Guan Z, Jiao Y, LiuD K, Hong. The story of a decade: Genomics, functional genomics, and molecular breeding in Brassica napus. Plant Commun. 2024;5:100884. Gu J, Hou D, Li Y, Chao H, Zhang K, Wang H, Xiang J, Raboanatahiry N. WangM. Li, Integration of proteomic and genomic approaches to dissect seed germination vigor in Brassica napus seeds differing in oil content. BMC Plant Biol. 2019;19:21. Gu J, Chao H, Gan L, Guo L, Zhang K, Li Y, Wang H, Li NRM. Proteomic Dissection of Seed Germination and Seedling Establishment in Brassica napus. Front Plant Sci. 2016;7:1482. Gómez-Maqueo X, Soriano D, Chávez-Esquivel EA, Alvarado-López S, Martínez-Barajas E, Flores-Ortíz CM, Benech-ArnoldA RL. Gamboa-deBuen, Different response to priming in Ceiba aesculifolia seeds is associated to the initial transcriptome landscape and to differential regulation of ABA and lipid metabolism. Environ Exp Bot. 2022;204:105094. Ding Y, Xing L, Xu J, Jiang T, Tang X, Wang Y, Huang S, Hao W, Zhou X, Xie YZCG. Genome-wide exploration of the GDSL-type esterase/lipase gene family in rapeseed reveals several BnGELP proteins active during early seedling development. Front Plant Sci. 2023;14:1139972. Lu G, Tian Z, Chen P, Liang Z, Zeng X, Zhao Y, Li C, Yan T. HangL. Jiang, Comprehensive Morphological and Molecular Insights into Drought Tolerance Variation at Germination Stage in Brassica napus Accessions. Plants. 2024;13:3296. Kozaki AT, Aoyanagi. Molecular Aspects of Seed Development Controlled by Gibberellins and Abscisic Acids. Int J Mol Sci. 2022;23:1876. Quesada V. Advances in the Molecular Mechanisms of Abscisic Acid and Gibberellins Functions in Plants 2.0. Int J Mol Sci. 2022;23:8524. Klajn N, Kapczyńska K, Pasikowski P, Glazińska P, Kugiel H, KęsyW J, Wojciechowski. Regulatory Effects of ABA and GA on the Expression of Conglutin Genes and LAFL Network Genes in Yellow Lupine (Lupinus luteus L.) Seeds. Int J Mol Sci. 2023;24:12380. Xiang F, Liu W-C, Liu X, Song Y, Zhang Y, Zhu X, Wang P, Song SGC-P. Direct balancing of lipid mobilization and reactive oxygen species production by the epoxidation of fatty acid catalyzed by a cytochrome P450 protein during seed germination. New Phytol. 2023;237:2104–17. Labat V, Louis-Mondésir C, Hentati S, Totozafy JC, Collet B, Gohon Y, Davanture M, Gromova M, Rajjou L. MameriT. Chardot, Modifications in lipids and storage proteins composition during germination of chia seeds (Salvia hispanica L). Food Chem. 2025;489:144682. Qin M, Zhu Q, Lai W, Ma Q, Liu C, Chen X, Zhang Y, Wang Z. ChenH. Yan, Insights into the prognosis of lipidomic dysregulation for death risk in patients with coronary artery disease. Clin Translational Med. 2020;10:e189. Tang H-Y, Wang C-H, Ho H-Y, Wu P-T, Hung C-L, Huang C-Y, Wu P-R. YehM.-L. Cheng, Lipidomics reveals accumulation of the oxidized cholesterol in erythrocytes of heart failure patients. Redox Biol. 2018;14:499–508. Zhang Y, Li D, Dirk LMA, DownieT AB, Zhao. ZmAGA1 Hydrolyzes RFOs Late during the Lag Phase of Seed Germination, Shifting Sugar Metabolism toward Seed Germination Over Seed Aging Tolerance. J Agric Food Chem. 2021;69:11606–15. Munz E, Rolletschek H, Oeltze-Jafra S, Fuchs J, Guendel A, Neuberger T, Ortleb S. JakobL. Borisjuk, A functional imaging study of germinating oilseed rape seed. New Phytol. 2017;216:1181–90. Sun L, Yuan Z, Wang D, Li J, Shi J, Hu Y, Yu J, Chen X, Chen S. LiangD. Zhang, Carbon Starved Anther modulates sugar and ABA metabolism to protect rice seed germination and seedling fitness. Plant Physiol. 2021;187:2405–18. Footitt S, Clewes R, Feeney M. Finch-SavageL. Frigerio, Aquaporins influence seed dormancy and germination in response to stress. Plant Cell Environ. 2019;42:2325–39. Xu F, Yoshida H, Chu C, Sun MMJ. Seed dormancy and germination in rice: Molecular regulatory mechanisms and breeding. Mol Plant. 2025;18:960–77. Claver A, Luján MÁ, Escuín JM, Schilling M, Jouhet J, Savirón M, López MV, Picorel R, Jarne C. V.L. CebollaM. Alfonso, Transcriptomic and lipidomic analysis of the differential pathway contribution to the incorporation of erucic acid to triacylglycerol during Pennycress seed maturation. Frontiers in Plant Science 2024 Volume 15–2024 . Li Y, Xu J, Li G, Wan S, Batistič O, Sun M, Zhang Y, Qi RSB. Protein S-acyl transferase 15 is involved in seed triacylglycerol catabolism during early seedling growth in Arabidopsis. J Exp Bot. 2019;70:5205–16. Chen K, Yin Y, Ding Y, Li HCM. Characterization of Oil Body and Starch Granule Dynamics in Developing Seeds of Brassica napus. Int J Mol Sci. 2023;24:4201. Chandrasekaran UA, Liu. Stage-specific metabolization of triacylglycerols during seed germination of Sacha Inchi (Plukenetia volubilis L). J Sci Food Agric. 2015;95:1764–6. Dueñas C Jr., Slamet-LoedinA I. Macovei, Transcriptomics View over the Germination Landscape in Biofortified Rice. Genes 2021 12 ,2013. Sybilska EA, Daszkowska-Golec. A complex signaling trio in seed germination: Auxin-JA-ABA. Trends Plant Sci. 2023;28:873–5. Yuan P, Zhou G, Yu M, Hammond JP, Liu H, Hong D, Cai H, Ding G, Wang S, Xu F, Shi CWL. Trehalose-6-phosphate synthase 8 increases photosynthesis and seed yield in Brassica napus. Plant J. 2024;118:437–56. Ihien Katche EAS, Mason. Resynthesized Rapeseed (Brassica napus): Breeding and Genomics. CRC Crit Rev Plant Sci. 2023;42:65–92. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFiles.zip Supplementary Materials: Figure S1: Quality Control and Quantitative Analysis of ribonucleic acid sequencing(RNA-Seq) Sequencing Data. Figure S2: GO enrichment of differentially expressed lipids at different stages of seed imbibition. Table S1: The list of DEGs at different imbibition stages of B. napus seeds Table S2: The list of DEMs at different imbibition stages of B. napus seeds Table S3: The list of abbreviations and primers used for qRT-PCR. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 May, 2026 Reviews received at journal 22 Apr, 2026 Reviewers agreed at journal 18 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers invited by journal 08 Apr, 2026 Editor assigned by journal 08 Apr, 2026 Editor invited by journal 30 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 26 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9166678","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623584353,"identity":"a6e4beee-a62d-41b4-b9a8-9b8968ef795c","order_by":0,"name":"Bo Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDACCSBmbGCQY5N/fPBBQkUN8VqM+RjSkg0enDlGvJbEeQw5ZpIPW5gJ65Cf3fzs4dcdNoxtDAfMKhIb2Bj427sT8GphnHPM3Fj2TBozG2ND2o3EHTIMEmfObsCrhVkiwUxasu0wGxszw7EbiWfYGAwkcvFrYZNI/wbSwsPGxthWkNjGTFgLjwTQ1x/bDkuw8TCzMRClRUIip0ya8UyaAZsEG9CRZ47xEPSL/Iz0bZI/d9jUz5/B//Hjj4oaOf72XvxaQICZB9mlBJWDAOMPopSNglEwCkbBiAUA1xJEfdFPGDIAAAAASUVORK5CYII=","orcid":"","institution":"Gansu Agricultural University Qingyang Winter Rapeseed Science and Technology Yard","correspondingAuthor":true,"prefix":"","firstName":"Bo","middleName":"","lastName":"Zhang","suffix":""},{"id":623584354,"identity":"4ce2e581-7e0c-49c9-804b-14bbd323f4ea","order_by":1,"name":"Junyan Wu","email":"","orcid":"","institution":"State Key Laboratory of Aridland Crop Science/ College of Agronomy","correspondingAuthor":false,"prefix":"","firstName":"Junyan","middleName":"","lastName":"Wu","suffix":""},{"id":623584355,"identity":"08f7cfc5-228f-4138-9252-30dcff1f41af","order_by":2,"name":"Li Ma","email":"","orcid":"","institution":"State Key Laboratory of Aridland Crop Science/ College of Agronomy","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Ma","suffix":""},{"id":623584356,"identity":"c9fce340-7ce6-440a-ad66-a0706c4af4f8","order_by":3,"name":"Haiqing Liu","email":"","orcid":"","institution":"Longdong University","correspondingAuthor":false,"prefix":"","firstName":"Haiqing","middleName":"","lastName":"Liu","suffix":""},{"id":623584358,"identity":"002a179e-a5b8-4b6b-b807-cdb0f2187c6c","order_by":4,"name":"Wancang Sun","email":"","orcid":"","institution":"State Key Laboratory of Aridland Crop Science/ College of Agronomy","correspondingAuthor":false,"prefix":"","firstName":"Wancang","middleName":"","lastName":"Sun","suffix":""},{"id":623584360,"identity":"0c5328e1-ae99-41c0-ba55-38cc2dc94113","order_by":5,"name":"Jianfeng Duan","email":"","orcid":"","institution":"Qingyang Agricultural Ecological Environmental Protection Management Station","correspondingAuthor":false,"prefix":"","firstName":"Jianfeng","middleName":"","lastName":"Duan","suffix":""}],"badges":[],"createdAt":"2026-03-19 08:08:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9166678/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9166678/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107093374,"identity":"d8acbfee-93a0-4728-8dfe-5022490ec009","added_by":"auto","created_at":"2026-04-16 16:33:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":896713,"visible":true,"origin":"","legend":"\u003cp\u003eMorphological characteristics of \u003cem\u003eB. napus\u003c/em\u003e seeds at different imbibition stages. (A), (B), (C), (D) and (E) represent the morphology of seeds after 0 h, 6 h, 12 h, 24 h and 48 h of imbibition, respectively. (F),Comparison of water content in \u003cem\u003eB. napus\u003c/em\u003e seeds at different imbibition stages.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/ec71187a2c30b64c4ba4b1e8.jpg"},{"id":107093376,"identity":"35991aa2-93a7-4e9c-b2c2-805d484c47bd","added_by":"auto","created_at":"2026-04-16 16:33:30","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":551496,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of gene expression in B. napus seeds at different imbibition stages. (A) Statistics of the number of significantly altered transcripts between successive stages in rapeseed seeds after imbibition. (B) Venn diagram analysis showing the overlap of differentially expressed genes (DEGs) between successive stages in rapeseed seeds after imbibition. (C) Hierarchical clustering heatmap of expressed genes at different stages in B. napus seeds after imbibition.the ordinate shows the FPKM-normalized values of differentially expressed genes; the redder the color, the higher the expression level, and the bluer the color, the lower the expression level.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/7e01c13801829800de8bb214.jpg"},{"id":107480902,"identity":"86cc78ae-67d4-4ae9-b03c-7fea17443f2a","added_by":"auto","created_at":"2026-04-22 02:14:18","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":628742,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG enrichment analysis of DEGs at different imbibition stages in B. napus seeds.(A), (B), (C), and (D) represent the KEGG pathway enrichment results of DEGs at 6 h, 12 h, 24 h, and 48 h of seed imbibition, respectively.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/d58cff0c801925e15b18122a.jpg"},{"id":107093378,"identity":"6f1607fb-2c85-466f-a1d5-2fdc8f64d548","added_by":"auto","created_at":"2026-04-16 16:33:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1195921,"visible":true,"origin":"","legend":"\u003cp\u003elipidomics analysis of B. napus seeds after imbibition.(A)Variations in lipid subclass levels in B. napus seeds during imbibition. (B)PCA analysis of all lipidomic samples from B. napus seeds after imbibition.(C)KEGG analysis of the identified lipid compounds.(D)Annotation of the eight major lipid classes and their subclasses for the identified lipids using the lipid maps database.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/d4b026d23c830fad97090ada.jpg"},{"id":107093382,"identity":"176c6043-6e79-4871-8252-158bbfd9fa90","added_by":"auto","created_at":"2026-04-16 16:33:30","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":824987,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential analysis of lipid compounds in B. napus seeds at different imbibition stages. (A)Clustering analysis of all differential lipid compounds in B. napus seeds after imbibition.(B)K-means analysis of differential lipid compounds in B. napus seeds after imbibition\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/b7f6bb4406a7d4f7f7990985.jpg"},{"id":107484228,"identity":"e936c38c-1ebd-40a5-9237-a9d7fe76994e","added_by":"auto","created_at":"2026-04-22 02:31:10","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1156780,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG enrichment of differentially expressed lipids at different stages of seed imbibition.(A), (B), (C), and (D) represent the KEGG pathway enrichment results of differentially expressed lipids at 6 h, 12 h, 24 h, and 48 h of seed imbibition, respectively.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/fa0e2b5110d64ef07715efd3.jpg"},{"id":107093380,"identity":"fb547ae4-60e6-4fe6-8c0a-5c0c764d5e04","added_by":"auto","created_at":"2026-04-16 16:33:30","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1778978,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of WGCNA in B. napus. (A) Gene clustering dendrogram and module division. (B) Number of genes in each module and correlation coefficients between modules and lipid metabolic traits. Red and blue in the color scale represent positive and negative correlations, respectively. (C) Bar plot of module significance (MS) for lipid metabolism-related traits.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/dcc68e2bab640ef09044ec76.jpg"},{"id":107481769,"identity":"993146e3-7ccf-497c-91cc-21c88d9becbf","added_by":"auto","created_at":"2026-04-22 02:19:52","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":736969,"visible":true,"origin":"","legend":"\u003cp\u003eExpression level analysis of differentially expressed genes from the transcriptome in B. napus seeds after imbibition. Data are the means ± standard error(n = 3). Asterisks indicate the P value determined using a Student's t test (*P\u0026lt;0.05, **P\u0026lt;0.01,***P\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/c133f56b0bc8b3ec9a245ea4.jpg"},{"id":107486857,"identity":"b9b36cc0-51c2-46d8-b49e-7c80b7ab44ed","added_by":"auto","created_at":"2026-04-22 02:39:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8157290,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/3866dd00-9a4f-4ab3-b6ea-c52ddc609e5b.pdf"},{"id":107482841,"identity":"e5094632-8bbb-43bc-9820-0e108b39a3bf","added_by":"auto","created_at":"2026-04-22 02:25:07","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14475600,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S1: \u003c/strong\u003eQuality Control and Quantitative Analysis of ribonucleic acid sequencing(RNA-Seq) Sequencing Data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure S2: \u003c/strong\u003eGO enrichment of differentially expressed lipids at different stages of seed imbibition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S1: \u003c/strong\u003eThe list of DEGs at different imbibition stages of\u003cem\u003e B. napus\u003c/em\u003e seeds\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S2: \u003c/strong\u003eThe list of DEMs at different imbibition stages of\u003cem\u003e B. napus\u003c/em\u003e seeds\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S3: \u003c/strong\u003eThe list of abbreviations and primers used for qRT-PCR.\u003c/p\u003e","description":"","filename":"SupplementaryFiles.zip","url":"https://assets-eu.researchsquare.com/files/rs-9166678/v1/0549ff5ac89cab125082ecfd.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Temporal Transcriptomic and Lipidomic Analysis Reveals Multi-Omics Dynamic Profiles of Brassica napus Seed Germination","fulltext":[{"header":"Background","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eSeed germination, a key early event in the plant life cycle, directly governs crop emergence, seedling uniformity, and subsequent growth potential, exerting profound effects on the final yield and quality of crops\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. As an important oilseed crop worldwide, \u003cem\u003eBrassica napus\u003c/em\u003e L. seeds are rich in lipids, serving as a vital source of edible vegetable oil, animal feed, and bioenergy\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In contrast to cereal crops, stored lipid mobilization and metabolism serve as a major source of energy for \u003cem\u003eB. napus\u003c/em\u003e seed germination\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Dynamic lipid degradation, transport and transformation processes are key prerequisites for successful seed germination and the seamless establishment of seedlings\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Uncovering the \u0026zwnj;regulatory mechanism\u0026zwnj; of lipid metabolism during seed germination can thus provide a \u0026zwnj;theoretical basis\u0026zwnj; for the genetic improvement and \u0026zwnj;accelerated breeding\u0026zwnj; of oilseed crops.\u003c/p\u003e \u003cp\u003eTriacylglycerols (TAGs) represent the primary storage lipid in \u003cem\u003eB. napus\u003c/em\u003e seeds and play two core roles during germination. On one hand, stored lipids are catabolized via a cascade of metabolic reactions to generate energy substrates, which supply the energy required for seed imbibition, radicle emergence, and early seedling growth\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. On the other hand, intermediate metabolites from lipid metabolism act as precursors for the synthesis and remodeling of cell membranes. These processes are critical for maintaining cellular structural integrity and fluidity, which in turn ensures the proper execution of essential physiological processes such as cell division and differentiation.\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCurrent understanding of the molecular regulatory mechanisms underlying seed germination remains partial, with several core pathways and key genes identified to mediate this process. In the hormone signaling pathway, GA promotes the expression of germination-related genes and breaks seed dormancy, while ABA represses germination\u003csup\u003e[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. In the lipid metabolic pathway, lipid hydrolysis, β-oxidation and gluconeogenesis act synergistically to convert stored lipids into energy and carbon sources, thus fueling seed germination\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we set multiple consecutive time points and integrated transcriptomic and lipidomic analyses to characterize the dynamic temporal and synergistic changes in gene expression and lipid metabolic profiles during \u003cem\u003eB. napus\u003c/em\u003e seed imbibition and germination. We further identified core genes and characteristic lipid molecules associated with different germination stages, as well as core nodes potentially involved in mediating seed germination. These findings may provide a preliminary theoretical basis for the genetic improvement of seed germination traits in \u003cem\u003eB. napus\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003ePlant Materials and Sample Collection\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn this study,\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eB. napus\u003c/em\u003e seeds (cultivar LY80) with a genetically stable background were freshly harvested in the same year, fully dried, and then hermetically stored at 4 ℃. Prior to germination, plump, intact seeds of uniform size were disinfected with 75% ethanol, rinsed thoroughly with sterile water for five times, and then placed in Petri dishes lined with double layers of filter paper for germination in a constant-temperature incubator at 25 ℃ in the dark.\u003c/p\u003e\n\u003cp\u003eSamples were collected at 0 h (dry seeds), 6 h, 12 h, 24 h and 48 h after seed imbibition, with approximately 0.2 g of mixed seeds designated as one independent biological replicate and three biological replicates prepared for each time point. All samples were snap-frozen in liquid nitrogen and stored at -80 ℃ for subsequent transcriptomic and metabolomic analyses.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRNA-sequencing (RNA-seq) analysis\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, Total RNA was isolated and checked for integrity using an Agilent 2100 Bioanalyzer. cDNA libraries were constructed and sequenced on an Illumina NovaSeq 6000 to generate 150‑bp paired‑end reads. Clean reads were mapped to the B. napus reference genome, and DEGs were identified using DESeq2 with Benjamini\u0026ndash;Hochberg correction. Genes with padj \u0026lt;= 0.05 and |log2 (fold change)| \u0026gt;= 1 were defined as significantly DEGs in this study. KEGG (Kyoto Encyclopedia of Genes and Genomes) annotations, the enrichment analysis of differentially expressed genes (DEGs) were performed using cluster Profiler (3.8.1).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLipid Extraction and UHPLC-MS/MS analyses\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTotal lipids were extracted from rapeseed seeds via a modified MTBE method. In brief, 100 mg liquid nitrogen-ground seed powder was vortexed with 0.75 mL methanol, blended with 2.5 mL MTBE and shaken for 60 min at room temperature. Then 0.625 mL chromatography-grade water was added for phase separation, and the mixture was left standing for 10 min\u003csup\u003e[15]\u003c/sup\u003e. The separated aqueous phase was re-extracted with 1 mL of a mixed solvent (MTBE/methanol/water, 10:3:2.5, v/v/v). The combined organic phases were dried and redissolved in 100 \u0026mu;L of isopropanol for storage, and then subjected to analysis by LC-MS/MS.UHPLC-MS/MS analyses were performed using a Vanquish UHPLC system (Thermo Fisher, Germany) and an Orbitrap Q ExactiveTM HF mass spectrometer (Thermo Fisher, Germany). Samples were injected onto a ThermoAccucore C30 column (150\u0026times;2.1mm, 2.6\u0026mu;m) using a 20-min linear gradient at a flow rate of 0.35mL/min. The column was maintained at 40 \u0026deg;C. Mobile phase A was acetonitrile\u0026ndash;water (6:4) with 10 mM ammonium acetate and 0.1% formic acid; phase B was acetonitrile\u0026ndash;isopropanol (1:9) with the same additives. The gradient program was: 30% B (0\u0026ndash;2 min), 43% B (5 min), 55% B (5.1 min), 70% B (11 min), 99% B (16 min), and re-equilibrated to 30% B at 18.1 min\u003csup\u003e[16]\u003c/sup\u003e. Q ExactiveTM HF mass spectrometer was operated in positive[negative] polarity mode with sheath gas :40 psi, sweep gas: 0 L/min, auxiliary gasrate: 10 L/min[7 L/min], spray voltage: 3.5 kV, capillary temperature: 320℃, heater temperature: 350℃, S-LensRF level: 50, scan range: 114\u0026ndash;1700 m/z, automatic gain control target: 3e6, normalized collisionenergy: 22eV; 24 eV; 28eV [22 eV；24 eV；28 eV], Injection time: 100 ms, Isolation window:1m/z, automatic gaincontrol target (MS2): 2e5, dynamic exclusion: 6s.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLipidomic data analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data files generated by UHPLC-MS/MS were processed using the Lipidsearch. Principal components analysis (PCA) and Partial least squares discriminant analysis (PLS‐DA)were performed at metaX (a flexible and comprehensive software for processing metabolomicsdata). We applied univariate analysis (t-test) to calculate the statistical significance (P-value). Themetabolites with VIP \u0026gt; 1 and P-value\u0026lt; 0.05 and fold change\u0026ge; 2 or FC\u0026le; 0.5 were considered tobe differential metabolites. Volcano plots were used to filter metabolites of interest which based on Log2(FC) and -log10(P-value) of metabolites.For clustering heat maps, the data were normalized using z-scores of the intensity areas ofdifferential metabolites and were ploted by Pheatmap package in R language. The correlationbetween differential metabolites were analyzed by cor () in R language (method = pearson).Statistically significant of correlation between differential metabolites were calculated bycor.mtest()in in R language. P-value \u0026lt; 0.05 was considered as statistically significant andcorrelation plots were ploted by corrplot package in R language.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRNA Extraction and Quantitative RT-PCR\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from 0.2 g rapeseed powder with RNAiso Plus. RNA purity was quantified using a NanoDrop 200, and 2 \u0026mu;g RNA was reverse-transcribed into cDNA. qRT-PCR was performed with Actin as the internal reference. Three biological and technical replicates were set, and relative expression levels were determined via the comparative 2\u0026minus;\u0026Delta;\u0026Delta;Ct threshold method\u003csup\u003e[17]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSeed morphology and water content of after imbibition\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo clarify the temporal characteristics of \u003cem\u003eB. napus\u003c/em\u003e seed imbibition and germination, we divided the process into sequential stages based on morphological observation and water content determination(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Dry seeds had a water content of 6.82%, which increased rapidly to 28.57% within 6 h, with slight seed swelling but intact seed coat and no radicle protrusion. From 6\u0026ndash;12 h, water absorption slowed, reaching 39.24% at 12 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), accompanied by continued swelling, softened seed coat and embryo expansion without seed coat rupture. Between 12\u0026ndash;24 h, water content stabilized at 35.11%\u0026ndash;42.38% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), with radicle protrusion and slight seed coat cracking. After 24 h, water content remained stable, with rapid radicle elongation to at 48 h, hypocotyl stretching and complete seed coat rupture (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Temporal characteristics of seed imbibition lay a fundamental foundation for subsequent omics detection and analysis.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGlobal Dynamic Changes of Transcriptome During Seed Imbibition and Germination\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo systematically explore the transcriptional dynamics during \u003cem\u003eB. napus\u003c/em\u003e seed imbibition and germination, transcriptome sequencing was performed on seed samples at 0 h, 6 h, 12 h, 24 h, and 48 h after imbibition, with three biological replicates per time point. Quality assessment revealed that the Q30 score for all sequencing libraries exceeded 97.36%, and the GC content ranged from 46.29% to 47.04%, indicating high sequencing accuracy and reliability, which met the requirements for subsequent bioinformatics analysis(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Meanwhile, transcriptome sequencing reads were aligned to the \u003cem\u003eB. napus\u003c/em\u003e reference genome. The Total_map (\u0026ge;\u0026thinsp;91.75%) and Unique_map (\u0026ge;\u0026thinsp;84.59%) of all samples fell within a reasonable high-value range with good alignment efficiency, demonstrating high reliability of the sequencing data and its suitability for subsequent analyses. Principal Component Analysis (PCA) was adopted to assess the overall differences and repeatability of transcriptomic patterns among samples at different germination stages. The results showed that samples of the same time point were closely clustered together, reflecting good reproducibility of biological replicates. Notably, samples of different time points were clearly separated along the first principal component (PC1, explaining 63.71% of the total variation)(Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), which indicated that the transcriptional profiles changed significantly with the progression of seed imbibition and germination, and the samples were well distinguished by the time sequence, laying a foundation for the subsequent analysis of differential gene expression.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuality and genome alignment statistics of transcriptome data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClean_reads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eError_rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGC_pct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal_map\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUnique_map\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm0R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68807008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e63748432(92.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58491777(85.01%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm0R2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71868122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66516572(92.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60790905(84.59%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm0R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71232200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e65579636(92.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e60256477(84.59%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm6R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75799360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69910950(92.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65035249(85.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm6R2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74211060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68278888(92.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e63402952(85.44%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm6R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75960730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69885929(92.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e64409897(84.79%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm12R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75916102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69896072(92.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65302548(86.02%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm12R2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76203644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69916393(91.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65546390(86.01%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm12R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74881814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68977426(92.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e64707700(86.41%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm24R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75852410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e70150592(92.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e66070476(87.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm24R2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74776434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69196973(92.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65068678(87.02%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm24R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76766098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e71101624(92.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e66878307(87.12%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm48R1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73803716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68631698(92.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e64762903(87.75%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm48R2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71675682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66525494(92.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e62620014(87.37%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIm48R3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74436288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69119002(92.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e65291130(87.71%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this study, differentially expressed genes (DEGs) among different time points were identified using the criteria of |log2(fold change)| \u0026ge; 1 and adjusted P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The number of DEGs varied with imbibition time: compared with the 0 h dry seed control, the numbers at 6 h, 12 h, 24 h, and 48 h exhibited an increasing trend(Fig.\u0026nbsp;2A)(Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). A Venn diagram analysis was performed to clarify the overlap of DEGs among different time points(Fig.\u0026nbsp;2B), and the results showed that only 404 DEGs were commonly expressed across all four comparison groups (Im6h vs Im0h, Im12h vs Im6h, Im24h vs Im12h, Im48h vs Im24h), indicating that most DEGs were specifically expressed at different germination stages. Hierarchical clustering analysis of all DEGs showed that transcriptional patterns were highly similar between dry seeds and seeds at 6 h of imbibition, whereas the clustering results at all other time points differed considerably from one another, which further confirms that transcriptional changes are time-dependent during imbibition(Fig.\u0026nbsp;2C).\u003c/p\u003e \u003cp\u003e.\u003c/p\u003e \u003cp\u003eFigure 2. Analysis of gene expression in \u003cem\u003eB. napus\u003c/em\u003e seeds at different imbibition stages. (A) Statistics of the number of significantly altered transcripts between successive stages in rapeseed seeds after imbibition. (B) Venn diagram analysis showing the overlap of differentially expressed genes (DEGs) between successive stages in rapeseed seeds after imbibition. (C) Hierarchical clustering heatmap of expressed genes at different stages in \u003cem\u003eB. napus\u003c/em\u003e seeds after imbibition.the ordinate shows the FPKM-normalized values of differentially expressed genes; the redder the color, the higher the expression level, and the bluer the color, the lower the expression level.\u003c/p\u003e \u003cp\u003eTo reveal the biological roles of DEGs during seed imbibition and germination, we performed GO functional classification and KEGG pathway enrichment analysis for DEGs identified at each sampling stage. GO enrichment analysis revealed stage-specific enrichment of DEGs during seed imbibition: DEGs at 6 h were mainly enriched in water transport, water stimulus response and cell wall organization-related biological processes; 12 h DEGs in protein folding, ribosome biogenesis and RNA processing; 24 h DEGs in lipid catabolism and energy metabolism; and 48 h DEGs were significantly enriched in cell division, cell elongation and hormone-mediated signaling pathways(Figure S2). KEGG pathway enrichment analysis also highlighted distinct metabolic and signaling dynamics across stages. At 6 h, the most significantly enriched pathways were MAPK signaling, ABC transporters and phenylpropanoid biosynthesis, reflecting early stress responses and secondary metabolism(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). By 12 h, ribosome biogenesis, porphyrin metabolism and sulfur metabolism dominated, indicating active protein synthesis and fundamental metabolic activation(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). At 24 h, starch and sucrose metabolism, glutathione metabolism and DNA replication were prominent, supporting the transition to active growth(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). By 48 h, intensive carbon metabolism, including starch and sucrose metabolism and pentose and glucuronate interconversions, along with phenylpropanoid biosynthesis and secondary metabolite production, was observed, underpinning cell expansion and organogenesis(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Collectively, these results illustrate a dynamic transcriptional and metabolic reprogramming process that drives seed imbibition and the initiation of germination.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGlobal Dynamic Changes of Lipidome During Seed Imbibition and Germination\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo systematically characterize the lipidomic dynamics during \u003cem\u003eB. napus\u003c/em\u003e seed imbibition and germination, lipidomic profiling was performed on the same seed samples as transcriptomic analysis, with three biological replicates per time point. A total of 1733 lipid molecules were identified across all samples, belonging to 15 major lipid classes, among which Triacylglycerol (TG) accounted for the highest proportion (16.40%), followed by Phosphatidylcholine (PC, 12.47%) and Diacylglycerol (DG, 9.82%)(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). PCA was conducted to evaluate the similarity of lipidomic profiles among samples, and the results showed that biological replicates of the same time point were closely clustered. Samples of different germination stages were clearly separated along PC1, which explained 46.62% of the total variation, suggesting significant temporal changes in lipid composition during seed imbibition and germination(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, KEGG pathway annotation of all identified metabolites revealed that lipid metabolism was the most enriched pathway, containing 1253 annotated metabolites, followed by global and overview maps and the digestive system, highlighting the central role of lipid metabolism during seed imbibition and germination(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Lipidmaps annotation demonstrated that glycerophosphocholines (GP01, PC) were the most abundant lipid subclass, followed by glycerophosphoethanolamines (GP02) and glycerophosphates (GP10)(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), Glycerolipidsand sphingolipids were also detected, confirming the dominance of phospholipids in membrane structure and the role of glycerolipids as storage and energy sources.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe hierarchical clustering heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA) revealed distinct temporal patterns in lipid metabolite abundance across imbibition stages, with clear clusters of lipids showing increasing or decreasing abundance over time, reflecting dynamic lipid remodeling during seed imbibition and germination, Differential lipids are enriched in different imbibition stages(Table S2). K-means clustering (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) further grouped these differential lipids into four subclusters: Subcluster 1 (110 metabolites) showed continuous accumulation, Subcluster 2 (450 metabolites) gradually increased and peaked at 24 h, Subcluster 3 (126 metabolites) remained relatively stable, and Subcluster 4 (99 metabolites) exhibited a sustained decrease, consistent with the breakdown of storage lipids to fuel germination; together, these findings illustrate the coordinated, stage-specific lipid metabolic changes that underpin seed imbibition and germination, aligning closely with our transcriptomic observations.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo dissect the temporal dynamics of lipid metabolism during seed imbibition and germination, we performed KEGG pathway annotation of lipid metabolites across four key time points. The analysis revealed a progressive activation of lipid metabolism: at 6 h (Figure. 6A), lipid metabolism was moderately represented (210 metabolites) alongside active glycan biosynthesis and core metabolic networks, reflecting the initial phase of water uptake and stress response; by 12 h (Figure. 6B), lipid metabolism activity temporarily declined (15 metabolites) as the seed prioritized core metabolic maintenance; at 24 h (Figure. 6C), lipid metabolism reactivated (18 metabolites) to support membrane repair and early growth; and by 48 h (Figure. 6D), it emerged as the most dominant pathway (92 metabolites), which aligns with transcriptomic observations of enhanced lipid catabolism to provide energy and metabolic precursors for the transition to active germination. This temporal progression demonstrates a tightly coordinated metabolic response that underpins seed imbibition and germination, with strong consistency between lipidomic and transcriptomic data.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWGCNA analysis of DEGs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo identify the potential regulatory network related to lipid metabolism and seed germination in \u003cem\u003eB. napus\u003c/em\u003e, weighted gene co-expression network analysis (WGCNA) was performed. Genes with low expression were filtered out, and the remaining genes were used to construct a scale-free network. A total of 10 distinct co-expression modules were identified by hierarchical clustering(Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Module\u0026ndash;trait correlation analysis showed that the MEblue module was strongly positively correlated with the catabolism of energy-storing substances such as lipids and carbohydrates, while The black module was associated with growth processes including membrane lipid biosynthesis(Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). The inter-module correlation heatmap illustrated the relationships among the identified co-expression modules. Most modules exhibited weak to moderate correlations with one another, indicating that they participate in distinct biological processes(Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eqRT-PCR Validation of Transcriptomic Data\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo confirm the credibility of transcriptome data, eight genes involved in lipid metabolism were selected for qRT-PCR detection(Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These genes exhibited either significant upregulation or downregulation across imbibition stages, including those showing marked decreases in early imbibition (BnaA08G0155600ZS, BnaA03G0274900ZS) and those displaying increases over time (BnaA05G0136600ZS). The qRT-PCR expression profiles of these genes were fully consistent with their transcriptomic profiles, a strong correlation that supports the robustness of our transcriptomic analysis and the validity of the stage-specific transcriptional changes observed during seed imbibition.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe Early Stage of Seed Germination is an Active Transcriptional Preparation Stage\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the rapid imbibition stage (0\u0026ndash;6 h), DEGs identified by transcriptomic analysis were mainly enriched in biological processes such as water transport, response to water stimulus, and cell wall organization. The early imbibition stage was accompanied by initial lipid metabolic remodeling; however, transcriptional regulation at this stage appeared to focus more on laying a structural and environmental foundation for subsequent lipid metabolism and seed germination, rather than on active lipid catabolism.The activation of these DEGs may be closely associated with the rapid water absorption and swelling of \u003cem\u003eB. napus\u003c/em\u003e seeds, a physiological process that is particularly critical for this oilseed crop. Unlike cereal crops, \u003cem\u003eB. napus\u003c/em\u003e seed germination relies predominantly on stored lipids for energy supply, and the normal progression of early imbibition may directly determine whether subsequent lipid mobilization and metabolism can proceed smoothly \u003csup\u003e[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.Specifically, genes related to water transport may promote the rapid penetration of water into seed cells, which not only helps break the dormant state of dry seeds but also may activate the activity of hydrolases that are prerequisites for subsequent lipid hydrolysis\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e .\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePotential Temporal Regulation of TAG Degradation and Energy Supply Conversion\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eData from both transcriptomics and lipidomics indicated that there may be a precise temporal coordination mechanism between biochemical pathways such as β-oxidation and gluconeogenesis during \u003cem\u003eB. napus\u003c/em\u003e seed germination, and this mechanism might ensure the continuous supply of energy and carbon skeletons required for seed germination and seedling establishment. As the main storage lipid in \u003cem\u003eB. napus\u003c/em\u003e seeds, triacylglycerols (TAGs) serve as the core energy source during germination, the germination and early seedling establishment of \u003cem\u003eB. napus\u003c/em\u003e are highly dependent on the efficient mobilization and metabolic conversion of TAGs, making the putative precise temporal regulation of TAG degradation particularly critical\u003csup\u003e[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Our results showed that the stepwise degradation of TAGs and their subsequent metabolic conversion are likely regulated by temporal programs at both the transcriptional and metabolic levels, which was well illustrated by the dynamic changes in KEGG pathway annotations across different imbibition stages.Specifically, at the early imbibition stage (0\u0026ndash;6 h), transcriptomic analysis indicated that DEGs were mainly enriched in water transport and cell wall organization processes, while lipidomic profiles and KEGG annotations (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) showed only initial lipid metabolic remodeling without active TAG degradation. This suggests that the transcriptional regulation at this stage prioritizes the establishment of a stable physiological environment for subsequent TAG mobilization, rather than immediate energy supply conversion\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.3 Enhancing Seed Germination Quality to Improve Yield\u003c/em\u003e \u003c/p\u003e \u003cp\u003eSeed germination is the foundational stage of the plant life cycle, directly determining crop emergence rate, seedling uniformity, and subsequent growth potential, which in turn affects final crop yield and quality\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. For \u003cem\u003eB. napus\u003c/em\u003e, an important oil crop and alternative protein source worldwide, the efficiency of seed germination and early seedling establishment is not only closely related to its yield and product quality but also plays a vital role in maintaining the stability of global oil supply and food security, especially under the context of increasing population pressure and deteriorating environmental conditions\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. For \u003cem\u003eB. napus\u003c/em\u003e, an important oil crop and alternative protein source worldwide, the efficiency of seed germination and early seedling establishment is not only closely related to its yield and product quality but also plays a vital role in maintaining the stability of global oil supply and food security, especially under the context of increasing population pressure and deteriorating environmental conditions\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. From the perspective of rapeseed breeding practice, enhancing seed germination quality through molecular breeding strategies is a direct and effective approach to improve yield. The core genes and characteristic lipid metabolic markers identified by integrated multi-omics analysis can be used as potential molecular targets for breeding rapeseed varieties with superior germination performance\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Enhancement of seed germination quality can effectively elevate the field emergence rate, optimize the population structure, and improve the efficiency of resource utilization, thereby increasing the per unit area yield of \u003cem\u003eB. napus\u003c/em\u003e without the need for cultivated land expansion.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study systematically presents the global molecular and metabolic characteristics of \u003cem\u003eB. napus\u003c/em\u003e seed germination at different imbibition stages via integrated transcriptomic and lipidomic analyses, clarifying the expression patterns of characteristic genes and lipid metabolites in each stage. It further deepens the systematic understanding of the regulatory mechanisms underlying \u003cem\u003eB. napus\u003c/em\u003e seed germination, and provides theoretical support and candidate gene resources for high-yield and high-quality rapeseed breeding.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTG: Triacylglycerol\u003c/p\u003e\n\u003cp\u003ePC: Phosphatidylcholine\u003c/p\u003e\n\u003cp\u003eDG: Diacylglycerol\u003c/p\u003e\n\u003cp\u003eCL: Cardiolipin\u003c/p\u003e\n\u003cp\u003eCer: Ceramide\u003c/p\u003e\n\u003cp\u003ePE: Phosphatidylethanolamine\u003c/p\u003e\n\u003cp\u003ePI: Phosphatidylinositol\u003c/p\u003e\n\u003cp\u003ePG: Phosphatidylglycerol\u003c/p\u003e\n\u003cp\u003ePA: Phosphatidic acid\u003c/p\u003e\n\u003cp\u003eFA: Fatty acid\u003c/p\u003e\n\u003cp\u003ePS: Phosphatidylserine\u003c/p\u003e\n\u003cp\u003eMGDG: Monogalactosyldiacylglycerol\u003c/p\u003e\n\u003cp\u003eDGDG: Digalactosyldiacylglycerol\u003c/p\u003e\n\u003cp\u003ePMt: Phosphatidylmethanol / Phytomelatonin\u003c/p\u003e\n\u003cp\u003ePFAA: Perfluoroalkyl acid / Polyunsaturated fatty acid\u003c/p\u003e\n\u003cp\u003eLPC: Lysophosphatidylcholine\u003c/p\u003e\n\u003cp\u003eSQDG: Sulfoquinovosyldiacylglycerol\u003c/p\u003e\n\u003cp\u003eGO: Gene Ontology\u003c/p\u003e\n\u003cp\u003eKEGG: Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003eWGCNA Weighted Gene Co-Expression Network Analysis\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBZ conceived the project and research plans; BZ, JW and LM performed the experiments; BZ, LM and HL analyzed the data; BZ wrote the article; BZ, JD and WS critically revised the manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work is supported by the Technology Fund Project (24JRRM025).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll transcriptomic and lipidomic data generated in this study have been deposited in the National Center for Biotechnology Information (NCBI) public databases to ensure free and open access for all researchers. The transcriptomic sequencing data are available in the Sequence Read Archive (SRA) database under the accession number [SRR37226466, SRR37226465, SRR37226464, SRR37226463, SRR37226462, SRR37226461, SRR37226460, SRR37226459, SRR37226458, SRR37226457, SRR37226456, SRR37226455, SRR37226454, SRR37226453, SRR37226452]. All data can be accessed freely upon publication to facilitate related research on \u003cem\u003eB. napus\u003c/em\u003e seed germination and lipid metabolism, and to provide support for rapeseed genetic improvement and breeding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSharma EM, Majee. Seed germination variability: why do genetically identical seeds not germinate at the same time? J Exp Bot. 2023;74:3462\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBegum K, Shammi NHM. Selective biotic stressors\u0026rsquo; action on seed germination: A review. Plant Sci. 2024;346:112156.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan Z, Han X, Dai C, Lu S, He H, Yao X, Chen P, Yang C, Zhao L, Yang Q-Y, Zou J, Wen J, Hong D, Liu C, Ge X, Fan C, Yi B, Zhang C, Ma C, Liu K, Shen J, Tu J, Yang G, Fu T. GuoH. Zhao, Functional genomics of Brassica napus: Progress, challenges, and perspectives. J Integr Plant Biol. 2024;66:484\u0026ndash;509.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu J, Guan Z, Jiao Y, LiuD K, Hong. The story of a decade: Genomics, functional genomics, and molecular breeding in Brassica napus. Plant Commun. 2024;5:100884.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu J, Hou D, Li Y, Chao H, Zhang K, Wang H, Xiang J, Raboanatahiry N. WangM. Li, Integration of proteomic and genomic approaches to dissect seed germination vigor in Brassica napus seeds differing in oil content. BMC Plant Biol. 2019;19:21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu J, Chao H, Gan L, Guo L, Zhang K, Li Y, Wang H, Li NRM. Proteomic Dissection of Seed Germination and Seedling Establishment in Brassica napus. Front Plant Sci. 2016;7:1482.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eG\u0026oacute;mez-Maqueo X, Soriano D, Ch\u0026aacute;vez-Esquivel EA, Alvarado-L\u0026oacute;pez S, Mart\u0026iacute;nez-Barajas E, Flores-Ort\u0026iacute;z CM, Benech-ArnoldA RL. Gamboa-deBuen, Different response to priming in Ceiba aesculifolia seeds is associated to the initial transcriptome landscape and to differential regulation of ABA and lipid metabolism. Environ Exp Bot. 2022;204:105094.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDing Y, Xing L, Xu J, Jiang T, Tang X, Wang Y, Huang S, Hao W, Zhou X, Xie YZCG. Genome-wide exploration of the GDSL-type esterase/lipase gene family in rapeseed reveals several BnGELP proteins active during early seedling development. Front Plant Sci. 2023;14:1139972.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu G, Tian Z, Chen P, Liang Z, Zeng X, Zhao Y, Li C, Yan T. HangL. Jiang, Comprehensive Morphological and Molecular Insights into Drought Tolerance Variation at Germination Stage in Brassica napus Accessions. Plants. 2024;13:3296.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKozaki AT, Aoyanagi. Molecular Aspects of Seed Development Controlled by Gibberellins and Abscisic Acids. Int J Mol Sci. 2022;23:1876.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuesada V. Advances in the Molecular Mechanisms of Abscisic Acid and Gibberellins Functions in Plants 2.0. Int J Mol Sci. 2022;23:8524.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlajn N, Kapczyńska K, Pasikowski P, Glazińska P, Kugiel H, KęsyW J, Wojciechowski. Regulatory Effects of ABA and GA on the Expression of Conglutin Genes and LAFL Network Genes in Yellow Lupine (Lupinus luteus L.) Seeds. Int J Mol Sci. 2023;24:12380.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiang F, Liu W-C, Liu X, Song Y, Zhang Y, Zhu X, Wang P, Song SGC-P. Direct balancing of lipid mobilization and reactive oxygen species production by the epoxidation of fatty acid catalyzed by a cytochrome P450 protein during seed germination. New Phytol. 2023;237:2104\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLabat V, Louis-Mond\u0026eacute;sir C, Hentati S, Totozafy JC, Collet B, Gohon Y, Davanture M, Gromova M, Rajjou L. MameriT. Chardot, Modifications in lipids and storage proteins composition during germination of chia seeds (Salvia hispanica L). Food Chem. 2025;489:144682.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQin M, Zhu Q, Lai W, Ma Q, Liu C, Chen X, Zhang Y, Wang Z. ChenH. Yan, Insights into the prognosis of lipidomic dysregulation for death risk in patients with coronary artery disease. Clin Translational Med. 2020;10:e189.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang H-Y, Wang C-H, Ho H-Y, Wu P-T, Hung C-L, Huang C-Y, Wu P-R. YehM.-L. Cheng, Lipidomics reveals accumulation of the oxidized cholesterol in erythrocytes of heart failure patients. Redox Biol. 2018;14:499\u0026ndash;508.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Li D, Dirk LMA, DownieT AB, Zhao. ZmAGA1 Hydrolyzes RFOs Late during the Lag Phase of Seed Germination, Shifting Sugar Metabolism toward Seed Germination Over Seed Aging Tolerance. J Agric Food Chem. 2021;69:11606\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMunz E, Rolletschek H, Oeltze-Jafra S, Fuchs J, Guendel A, Neuberger T, Ortleb S. JakobL. Borisjuk, A functional imaging study of germinating oilseed rape seed. New Phytol. 2017;216:1181\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun L, Yuan Z, Wang D, Li J, Shi J, Hu Y, Yu J, Chen X, Chen S. LiangD. Zhang, Carbon Starved Anther modulates sugar and ABA metabolism to protect rice seed germination and seedling fitness. Plant Physiol. 2021;187:2405\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFootitt S, Clewes R, Feeney M. Finch-SavageL. Frigerio, Aquaporins influence seed dormancy and germination in response to stress. Plant Cell Environ. 2019;42:2325\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu F, Yoshida H, Chu C, Sun MMJ. Seed dormancy and germination in rice: Molecular regulatory mechanisms and breeding. Mol Plant. 2025;18:960\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClaver A, Luj\u0026aacute;n M\u0026Aacute;, Escu\u0026iacute;n JM, Schilling M, Jouhet J, Savir\u0026oacute;n M, L\u0026oacute;pez MV, Picorel R, Jarne C. V.L. CebollaM. Alfonso, Transcriptomic and lipidomic analysis of the differential pathway contribution to the incorporation of erucic acid to triacylglycerol during Pennycress seed maturation. \u003cem\u003eFrontiers in Plant Science\u003c/em\u003e 2024 \u003cem\u003eVolume 15\u0026ndash;2024\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Xu J, Li G, Wan S, Batistič O, Sun M, Zhang Y, Qi RSB. Protein S-acyl transferase 15 is involved in seed triacylglycerol catabolism during early seedling growth in Arabidopsis. J Exp Bot. 2019;70:5205\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen K, Yin Y, Ding Y, Li HCM. Characterization of Oil Body and Starch Granule Dynamics in Developing Seeds of Brassica napus. Int J Mol Sci. 2023;24:4201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChandrasekaran UA, Liu. Stage-specific metabolization of triacylglycerols during seed germination of Sacha Inchi (Plukenetia volubilis L). J Sci Food Agric. 2015;95:1764\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDue\u0026ntilde;as C Jr., Slamet-LoedinA I. Macovei, Transcriptomics View over the Germination Landscape in Biofortified Rice. \u003cem\u003eGenes\u003c/em\u003e 2021 \u003cem\u003e12\u003c/em\u003e,2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSybilska EA, Daszkowska-Golec. A complex signaling trio in seed germination: Auxin-JA-ABA. Trends Plant Sci. 2023;28:873\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan P, Zhou G, Yu M, Hammond JP, Liu H, Hong D, Cai H, Ding G, Wang S, Xu F, Shi CWL. Trehalose-6-phosphate synthase 8 increases photosynthesis and seed yield in Brassica napus. Plant J. 2024;118:437\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIhien Katche EAS, Mason. Resynthesized Rapeseed (Brassica napus): Breeding and Genomics. CRC Crit Rev Plant Sci. 2023;42:65\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lipids, Seed germination, Transcriptomic and Lipidomic, Brassica napus.L","lastPublishedDoi":"10.21203/rs.3.rs-9166678/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9166678/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLipids constitute a major component of \u003cem\u003eBrassica napus\u003c/em\u003e seeds. During seed germination, lipid mobilization serves as a critical energy source for seedling establishment, which directly impacts germination vigor and the subsequent growth potential of seedlings. Although lipid mobilization is essential for rapeseed germination, the time-dependent coordination between transcriptional regulation and lipid conversion remains largely unclear, and the corresponding molecular regulatory network still needs to be systematically explored.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe conducted an integrated transcriptomic and lipidomic analysis on dry \u003cem\u003eB. napus\u003c/em\u003e seeds and germinating seeds at 6, 12, 24, and 48 hours after imbibition. The results revealed distinct stage-specific characteristics of gene expression and lipid metabolism during germination. In the early imbibition stage, differentially expressed genes (DEGs) were primarily enriched in biological processes related to water transport, stress response, and signal transduction, whereas significant changes in lipid metabolism were observed to be relatively delayed. During the initiation of germination, triacylglycerols (TAGs) underwent rapid degradation, accompanied by a significant up-regulation of genes involved in the β-oxidation and gluconeogenesis pathways. In the late germination stage, genes responsible for membrane lipid synthesis were sharply up-regulated, which induced extensive membrane lipid remodeling.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study is the first to depict the dynamic multi-omics profile during \u003cem\u003eB. napus\u003c/em\u003e seed germination, systematically illustrating the global molecular and metabolic features of \u003cem\u003eB. napus\u003c/em\u003e seeds at different imbibition stages. It also clarifies the expression patterns of characteristic genes and lipid metabolites at each stage of germination. These findings further deepen our systematic understanding of the regulatory mechanisms governing \u003cem\u003eB. napus\u003c/em\u003e seed germination, and provide valuable theoretical support as well as candidate gene resources for the breeding of high-yield and high-quality \u003cem\u003eB. napus\u003c/em\u003e varieties.\u003c/p\u003e","manuscriptTitle":"Temporal Transcriptomic and Lipidomic Analysis Reveals Multi-Omics Dynamic Profiles of Brassica napus Seed Germination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-16 16:33:25","doi":"10.21203/rs.3.rs-9166678/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-14T08:34:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T05:29:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"34440355495941130738144838607206576168","date":"2026-04-18T10:08:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273289778479265714058125319122522357430","date":"2026-04-16T22:30:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T02:15:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-09T01:34:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-30T17:07:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T02:26:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2026-03-27T02:21:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2f3ab51c-988a-4d74-962e-a55474fe0fd8","owner":[],"postedDate":"April 16th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-14T08:34:17+00:00","index":56,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T16:33:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-16 16:33:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9166678","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9166678","identity":"rs-9166678","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}