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Article

Integrated Analysis of Hormone Metabolomics and Transcriptomics Reveals the Differential Mechanism of Ginger (Zingiber officinale Roscoe) Rhizome Bulking

by
Kai Wang
1,2,
Yao Lv
1,2,
Song Gao
3,
Yuwen Kong
1,2,
Miaohong Liu
1,2,
Zijing Chen
1,2,* and
Kun Xu
1,2,*
1
College of Horticulture Science and Engineering, Shandong Agricultural University, Tai’an 271002, China
2
Key Laboratory of Biology and Genetic Improvement of Horticultural Crops in Huanghuai Region, Ministry of Agriculture and Rural Affairs, Tai’an 271002, China
3
College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou 225012, China
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(4), 779; https://doi.org/10.3390/agronomy15040779
Submission received: 22 February 2025 / Revised: 14 March 2025 / Accepted: 20 March 2025 / Published: 22 March 2025
(This article belongs to the Section Crop Breeding and Genetics)
Browse Figures
Versions Notes

Abstract

:
As a product and reproductive organ of ginger (Zingiber officinale Roscoe), the degree of rhizome bulking is a key factor in determining the yield and economic value of ginger. There are few studies on the regulatory mechanism of rhizome bulking in ginger. This study aims to identify the key hormone that regulates ginger rhizome bulking and to screen for critical hormone-associated genes. As research subjects, two ginger accessions—large (L) with a thickened rhizome and small (S) with a slender rhizome—were derived from the same parent plant. The ploidy differences between the two determine variations in gene dosage as well as differential expression patterns. The levels of eight hormones in the rhizome of L and S during different growth stages were analyzed. Differentially expressed genes (DEGs) were identified by combining third-generation transcriptome sequencing technology (PacBio SMART) with quantitative real time PCR (qRT-PCR). Through screening methods such as Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), auxin, cytokinin, and salicylic acid were identified as the key differential hormones across various growth periods. Among these, changes in IAA level showed a positive correlation with rhizome bulking. Among them, change in IAA levels was positively correlated with the degree of rhizome bulking. Transcriptome analysis combined with qRT-PCR revealed that the auxin response factor genes ZoARF7 and ZoARF23 are likely to act as positive regulators of rhizome bulking. This study provides a theoretical foundation for elucidating the molecular mechanisms underlying hormone-mediated rhizome bulking in ginger.

1. Introduction

Ginger (Zingiber officinale Roscoe) is an annual crop in northern China, and its use as an economical crop has important applications in the food, medical, and chemical industries [1,2,3]. The rhizome, serving as both the productive and reproductive organ of ginger, directly impacts ginger yield and economic value through its growth and development, making it the subject of significant research [4]. The rhizome of ginger, along with the tubers of potatoes (Solanum tuberosum L.) and the storage roots of sweet potatoes (Ipomoea batatas L.), belong to the category of underground storage organs. Their bulking process is co-regulated by both environmental factors and genetic components [5]. Current research on the bulking of ginger rhizomes has primarily focused on physiological aspects, specifically investigating the effects of external factors such as light and mineral elements on rhizome bulking [6,7]. In contrast, studies on the genetic and molecular regulatory mechanisms underlying rhizome bulking remain limited. In crops such as potatoes and sweet potatoes, plant hormones, as critical regulators of underground storage organ development, have been extensively studied [8]. These findings provide valuable references for investigating the mechanisms underlying rhizome bulking in ginger.
Endogenous hormones play a key role in regulating the bulking of plant product organs, and the development of plant organs is regulated by the biosynthesis and signaling processes of endogenous hormones [9,10]. The CCAAT box-binding factor IbNF-YA1 targets binding to the promoter of IbYUCCA4, a key gene for auxin synthesis, and activates its transcription to increase the level of indole-3-acetic acid (IAA) in sweet potato tubers, promoting the growth of tubers at the early stage but inhibiting their bulking at the later stage [11]. SRD1 (MADS-box protein) activates the proliferation of the formation layer and secondary xylem to achieve the initial bulking of sweet potato tuberous roots, a process that also depends on the regulation of auxin [12]. Gibberellins (GAs) often play a negative role in the formation of product organs [13,14,15]. GA degradation gene StGA2ox1 overexpression lines had higher gibberellin levels than silenced lines, and higher gibberellin levels inhibited the bulking of potato tubers [16]. Brassinolide (BR) functions to improve crop yield and stress tolerance, and the expression of BvBZR, key factor genes in the BR signaling pathway, were positively correlated with the bulking of sugar beet (Beta vulgaris L.) primary roots and sugar accumulation [17]. In potatoes, BR promotes cell bulking and tuber development by activating the receptor StBRI1, which upregulates the activity of plasma membrane proton ATPase 2 (PHA2) [18]. The abscisic acid (ABA) signaling transcription factor StABL1 regulates StGA2o1 to affect potato tuber bulking [19]. Expression levels of the ABA response factor BjABR1 are positively correlated with the degree of mustard (Brassica juncea var. tumida Tsen et Lee) stem bulking [20]. Other hormones have also been reported, such as the silencing of the Carotenoid Cleavage Dioxygenase 8 (CCD8) gene, key in the SL biosynthetic pathway, which results in the dwarfing of the potato plant, increased branching, and the inhibition of tuber development [21].
In ginger, the roles of different plant hormone in rhizome bulking remain controversial, with inconsistent findings reported across studies. Previous studies have demonstrated that the levels of GA, IAA, zeatin (ZT), and jasmonic acid (JA) are positively correlated with rhizome bulking [22]. Some studies have indicated that the levels of IAA, ABA, and JA are positively correlated with rhizome bulking in ginger, whereas ZT and GA exhibit negative correlations with this process [23]. On the other hand, studies on the genetic and molecular regulatory mechanisms underlying rhizome bulking in ginger remain limited. Cao et al. and Ren et al. identified 10 and 11 candidate genes potentially involved in ginger rhizome bulking, respectively, by performing transcriptome sequencing on ginger rhizomes at different growth stages and validating the results through quantitative real-time PCR (qRT-PCR) [4,22]. Among the identified genes, in addition to auxin response factor (ARF), these candidates encompass multiple gene families such as basic helix–loop–helix (bHLH), WRKY transcription factor (WRKY), NAM/ATAF/CUC (NAC), and MYB (myeloblastosis), with diverse functional potentials implicated in rhizome bulking. Elucidating the roles of plant hormones in ginger rhizome bulking and identifying key genes regulating this process remain central objectives in current ginger research. Given the consensus and controversies surrounding the roles of plant hormones, we hypothesize that one or two key regulatory hormones govern the bulking process of ginger rhizomes. By prioritizing these hormones, we aim to refine the candidate pool of hormone-associated genes for targeted screening. To streamline the identification of key differential hormones and associated genes, this study selected two distinct ginger varieties with markedly divergent rhizome bulking capacities as experimental materials. Following preliminary phenotyping to confirm their morphological divergence, hormonal profiling (targeting eight major classes of plant hormones) was conducted on rhizomes at different developmental periods. Transcriptome sequencing was conducted on rhizome samples collected during the peak bulking stage (the rhizome bulking stage) of ginger, followed by the screening of differentially expressed genes (DEGs) and validation through qRT-PCR. The elucidation of key hormones and associated genes governing ginger rhizome bulking will significantly advance our understanding of the hormonal regulatory mechanisms underlying this process, providing critical theoretical foundations for future research.

2. Materials and Methods

2.1. Plant Materials

The experiment was carried out in the Horticultural Experiment Station of Shandong Agricultural University in 2023. The ginger used in the experiment was all planted in cultivation bags with a diameter of 40 cm and a height of 25 cm. There was one ginger plant in each bag, and the cultivation substrate was a mixture of coconut coir and peat (1:1.5, v/v). This study selected two ginger varieties, large ginger material (L) and small ginger material (S) (Figure 1), as research subjects. The VM0-generation L and S were derived from the same ginger plant (Figure 1A), which originated from a natural variation of the ‘Shannong No. 1’ ginger cultivar. The right side of the rhizome is designated as L, which maintains the characteristic hypertrophy of the ‘Shannong No. 1’ cultivar rhizome. The left side of the rhizome is designated as S, characterized by stunted rhizome growth and a reduced bulking level compared to L. The experimental populations of both the L and S cultivars consisted of 90 test plants each. Sampling was conducted at four distinct growth phases of ginger: the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage. The phenological phases of ginger growth and corresponding sampling time points were defined as follows: the seedling stage (6–15), the tillering stage (8–15), the rhizome bulking stage (9–15), and the harvest stage (10–15). For sampling, three plants were randomly selected from each cultivar to serve as three biological replicates.

2.2. Phenotypic Identification

The growth parameters at harvest maturity were quantified in three successive generations of the variant materials, with five plants per cultivar randomly selected for the systematic measurement of morpho-physiological traits. Ploidy determination in ginger was conducted using apical unexpanded leaves collected during the seedling stage (6–15), with the diploid cultivar ‘Laiwu small ginger’ serving as the control [24]. Ploidy analysis maintained methodological fidelity to the protocol developed by Liu et al. [25], with the core experimental workflow summarized below. Leaf tissues were rapidly fragmented using double-edged razor blades in a lysis buffer, followed by filtration through a 300-mesh nylon mesh. The nuclei suspension was subsequently stained with propidium iodide (Solarbio, Beijing, China). Following processing, ploidy determination was performed using a BD FACSAria III flow cytometer (BD Biosciences, San Jose, CA, USA). Chromosomal observation in cytogenetic variant materials was performed using the root tip squashing technique, with ginger root tips collected during the seedling stage (6–15). Following tissue maceration, chromosome-specific staining, and microscopic preparation, chromosomal visualization was conducted under a Nikon Eclipse Ni-U research microscope (Nikon, Tokyo, Japan) equipped with a DS-Ri2 digital camera system, enabling high-resolution karyotypic documentation for chromosomal enumeration and structural aberration analysis. Ultimately, karyotype analysis of ginger chromosomes was performed using the ImageJ software (version 1.8.0), with the entire experimental and karyotyping procedures aligning with the methodology described by Xin [26].

2.3. Metabolome Analysis of Ginger Rhizome Hormones

Rhizomes from four periods of L and S were used as the test materials, and the four periods were as follows: the seedling stage (6–15), the tillering stage (8–15), the rhizome bulking stage (9–15), and the harvest stage (10–15). Quantitative analysis of eight classes of phytohormones—auxins, cytokinins, gibberellins, abscisic acid, ethylene, jasmonic acid, salicylic acid, and strigolactones—encompassing 88 hormonal metabolites was performed. The procedures for hormone extraction, Liquid Chromatography–Tandem Mass Spectrometry (LC-MS/MS) operation, and data analysis were conducted following the method established by Shen et al. [27].

2.4. Transcriptome Analysis and qRT-PCR Validation

In order to explore the molecular mechanism of the difference in rhizome bulking degrees between the ginger variant materials L and S at the transcriptome level, transcriptome sequencing was performed on the rhizomes of the variant materials during the rhizome bulking stage (9–15). The transcriptome sequencing work was completed by Novogene Company (Beijing, China). Primer design for the target genes was accomplished using Primer Premier 5.0. RNA extraction and cDNA synthesis were performed using an RNA Isolation Kit (Vazyme, Nanjing, China) and a cDNA Synthesis Kit (Vazyme, Nanjing, China), respectively. qRT-PCR was conducted using the ABI Q6 RealTime PCR system. ZoRPII was used as an internal reference gene [28]. The relative expression levels of the target genes were calculated using the 2−ΔΔCT method. The relevant primer information can be found in Table A1.

2.5. Statistical Analysis

The data of different parameters were analyzed using an independent samples t-test in the SPSS statistical software (version 27.0). The homogeneity of variances was first verified using Levene’s test. Significant differences between the two experimental groups (expressed as the mean value ± standard deviation) were determined based on t-test results at p < 0.05. Asterisks denote statistically significant differences between the groups determined by the independent samples t-test (one asterisk denotes p < 0.05 and two asterisks denote p < 0.01). As key parameters of Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), the Coefficient of Determination X matrix (R2X) and the Coefficient of Determination Y matrix (R2Y) reflect the model’s ability to fit the original data and classification results, respectively. The Predictive Coefficient of Determination (Q2) reflects the model’s predictive ability, and the model is considered valid when Q2 > 0.5. Plotting was performed using Excel 2016 and heatmaps were constructed using Heml 1.0 software.

3. Results

3.1. Analysis of Growth Parameters and Ploidy Determination in Ginger

Growth indicators and cell ploidy, as critical plant phenotypic traits, show significant differences between groups L and S, as demonstrated in Table 1 and Figure 2. The number of branches in S was 2.40~3.01 times that of L, whereas the fresh weight of the rhizome was only 48.19%~53.60% times that of L. In addition to this, L and S showed significant differences in plant height, stem diameter, and the fresh weight of rhizomes, leaves, and roots (Table 1, p < 0.01). L had both diploid and tetraploid cells belonging to the mixoploid (Figure 2B), while S was diploid (Figure 2C). The integrated analysis of growth indicators and ploidy levels revealed that S exhibited significant variations in both morphological phenotypes and genetic architecture compared to L.

3.2. Karyotype Analysis of Ginger

To validate the flow cytometric results and elucidate karyotypic differences between L and S, chromosome counting and karyotype analysis were systematically conducted on both experimental groups. There were two chromosome types, 2n = 2x = 22 and 2n = 4x = 44, in L (Figure 3A,B), which belonged to the mixoploid group. The chromosome number of S was 2n = 2x = 22 (Figure 3C), which belonged to the diploid group. As shown in Table 2, the relative length of the chromosomes in L diploid and tetraploid cells ranged from 6.41% to 11.74% and 6.32% to 11.59%. The arm ratios ranged from 1.37 to 2.11 and 1.30 to 2.46, with the average arm ratios of 1.75 and 1.71 and the mitotic indices ranged from 32.14% to 42.28% and 31.95% to 43.48%. The ratio of the longest chromosome to the shortest chromosome was 1.83, and the karyotype asymmetry index was 63.56% and 62.90%. The relative length of chromosomes in S somatic cells ranged from 6.45% to 11.85%, the arm ratio ranged from 1.36 to 2.59, with an average arm ratio of 1.84, the mitotic index ranged from 31.06% to 42.28%, the ratio of the longest chromosome to the shortest chromosome was 1.84, and the karyotype asymmetry index was 64.45%. The range of L and S mitotic indices was close, both located in the 31~44% interval, and the average arm ratio and karyotype asymmetry coefficient were, in descending order, S cells > L diploid cells > L tetraploid cells. S somatic and L diploid cells have the same karyotype formula of K(2n) = 8 m + 14 sm, while L tetraploid cells have the karyotype formula K(2n) = 24 m + 20 sm. The karyotype classification of chromosomes in both L and S was type 2A. The chromosome counts between L and S validated the flow cytometry results. Comprehensive karyotype analysis integrating multiple parameters demonstrated the identical karyotypic formulas and classifications in the diploid cells of both groups, while tetraploid cells exhibited distinct differences.

3.3. Analysis of Hormone Levels in Ginger Rhizomes

On the basis of clarifying the phenotypic differences between L and S, the study further explores the impact of endogenous hormones on the differences in rhizome bulking. Hormone levels were measured at the seedling stage (6–15), the tillering stage (8–15), the rhizome bulking stage (9–15), and the harvest stage (10–15) using the LC-MS/MS technique, and 32 out of 88 metabolites detected were under the detection limit. Firstly, changes the levels of the five common classes of hormone metabolites were analyzed over four growth periods (Figure 4). During the tillering stage (8–15), ginger is dominated by above-ground growth, rhizome development is relatively slow, and the difference in rhizome size between L and S begins to become apparent (Figure 1F). The levels of indole-3-acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC), and abscisic acid (ABA) in L were 53.21%, 42.20%, and 87.67% higher than those in S, respectively, with significant differences between L and S (p < 0.01). At this time, IAA, ACC, and ABA levels were positively correlated with the degree of rhizome bulking. During the rhizome bulking stage (9–15), the above-ground growth of ginger basically ceased, and the rhizome entered the rapid bulking period. The difference in rhizome bulking between rhizomes of L and S increased further (Figure 1G). The IAA level in the rhizome of L was 201.5% higher than in the rhizome of S, with a significant difference (p < 0.01). The levels of other hormones in the rhizome of S were significantly higher than those in L, and only the IAA levels were positively correlated with the size of the rhizome. During the harvest stage (10–15), the growth of both the above-ground and underground parts of ginger essentially ceased (Figure 1H). At this time, S showed a non-significant difference in IAA levels compared to L, while all other hormone levels showed significant differences. Among the five common hormone classes, the IAA levels were consistently correlated with the rhizome bulking trend. The remaining 51 classes of hormone metabolites are presented in the form of a heat map (Figure 5). Endogenous hormone metabolism was more active during the seedling stage (6–15) as the initial period of rhizome development. At this time, almost all metabolites showed significant difference. During the rhizome bulking stage, metabolites that were significantly higher in S than in L included cytokinins (Kinetin-9glucoside (K9G), 6-Benzyladenine (BAP)) and strigolactone (5-Deoxystrigol). Metabolites significantly elevated in the rhizomes of L compared to S included auxin [3-indoleacetonitrile (IAN) and indole-3-butyric acid (IBA)] and jasmonic acid analogs (3-oxo-2-(2-(Z)-Pentenyl) cyclopentane-1-hexanoic acid, OPC-6) cyclopentane-1-hexanoic acid (OPC-6)]. However, no significant differences in their levels were observed between the tillering stage (8–15) and the harvest stage (10–15). The results of the heatmap show that both auxin and jasmonic acid were positively correlated with the trend of rhizome bulking, while cytokinin and strigolactone were negatively correlated. However, merely relying on the comparison of the hormone level of L and S during different growth periods and the results of the significance analysis of the differences are not sufficient to directly determine that the above-mentioned hormones play a key role in the process of rhizome bulking.

3.4. KEGG Functional Classification and OPLS-DA Analysis of Hormones in Ginger Rhizomes

Based on the differential metabolite results, KEGG pathway enrichment was performed to further identify the hormone metabolic pathways that significantly changed during rhizome bulking in L and S (Figure 6A). During the rhizome bulking stage, there was a higher enrichment of significantly different hormone metabolites for tryptophan metabolism and indole alkaloid biosynthesis, and the hormone most closely linked to this pathway was auxin, which uses tryptophan as a synthetic precursor. The data were analyzed using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) for the tillering stage (8–15), the rhizome bulking stage (9–15), and the harvest stage (10–15), and the samples were efficiently divided into two groups (Figure 6B). At this stage, with R2X = 0.539, R2Y = 0.995, and Q2 = 0.988 (Figure A1), the model demonstrated excellent performance in classification tasks, strong predictive capability, and reliable results. VIP scores provided by OPLS-DA yielded the contribution of metabolites to the classification of samples and also provided a visual representation of the role of metabolites in classification.
The metabolites with a VIP score > 1.75 were ortho-topolin riboside (oTR), 2-Methylthio-cis-zeatin riboside (2MeScZR), cis-Zeatin-9-glucoside (cZ9G), and salicylic acid (SA) (Figure 6C). The only hormone with a VIP score > 1.25 and significantly higher levels in the rhizomes of L than S was IAA. The three categories of plant hormones exhibited significant differences between L and S across three growth periods. Specifically, cytokinin (oTR, 2-MeScZR, and cZ9G) and salicylic acid (SA) showed an inverse correlation with the rhizome bulking trend (Figure 5). By comprehensively analyzing the comparison of hormone levels during different growth periods, the significance analysis of differences, and the KEGG functional classification, and then combining with the OPLS-DA analysis, it is concluded that auxin, cytokinin, and salicylic acid are the key hormones that lead to the differences in rhizome bulking between L and S. This is generally consistent with our initial hypothesis.

3.5. Transcriptome Analysis of Ginger Rhizomes

Building on the identified key differential hormones between L and S, transcriptome-based screening was carried out to pinpoint the differentially expressed genes associated with these hormones. The rhizomes of L and S during the rhizome bulking stage were selected as test materials for transcriptome analysis. A total of 56,610 shared differentially expressed genes (DEGs) were identified between L and S through transcriptome sequencing (Figure 7B). The differential gene screening criteria were based on |log2 (Fold Change)| > 1 and p-value < 0.05. Figure 7A shows that there were 618 heterogeneous genes in L vs. S during the root and rhizome bulking stages, of which 359 were down-regulated and 259 were up-regulated. To further explore the hormone-related differentially expressed genes, statistics were conducted for auxin, strigolactone, salicylic acid, and cytokinin-related genes (Table 3). There were eight genes related to auxin, four genes related to cytokinin, and three genes related to salicylic acid. Combined with the annotation of transcriptome data and comparison with the whole genome sequence of ginger, the results were as follows after eliminating duplicated genes: five auxin-related genes, including four auxin signaling genes (ZoARF7/23/17, ZoGH3.1) and one transporter protein gene (ZoPIN1b), one cytokinin-responsive regulator gene (ZoARR9) and three salicylate signaling genes (ZoPR1, ZoNPR1, and ZoSABP2).

3.6. Quantitative Real-Time PCR of DEGs

QRT-PCR was used to validate the transcriptome results. The results (Figure 8) show a consistent trend with the RNA-seq data, indicating a high accuracy of the transcriptome data. The expression levels of ZoARF7 and ZoARF23 in the rhizome of L were significantly higher than those in S, showing a positive correlation with rhizome bulking at this stage. Conversely, ZoARF17 and ZoGH3.1 exhibited the opposite pattern. To further clarify the change in the expression of ZoARF7/23 at different growth periods, the expression levels of both at four growth periods were examined using qRT-PCR. As shown in Figure 9, the expression level of ZoARF7/23 reached its peak during the rhizome bulking stage (9–15), with significantly higher levels observed in L than in S (p < 0.01) The overall expression showed a firstly increasing and then decreasing trend, which was positively correlated with the trend of the degree of rhizome bulking. The qRT-PCR results revealed that ZoARF7/23, an auxin-related gene, not only exhibited differential expression between L and S but also displayed expression level changes that paralleled the trend of rhizome bulking.

4. Discussion

4.1. The Influence of Chromosomal Ploidy Variation on Rhizome Bulking

The significant and genetically stable difference in rhizome bulking between L and S provides a foundation for analyzing the regulatory mechanism underlying this phenotypic variation. Karyotype analysis revealed that both L and S share identical karyotype classifications, likely attributed to their shared origin from the same parent plant (Figure 1A). Flow cytometry and karyotype analysis further demonstrated that, unlike the mixoploid L (2n = 2x = 22, 2n = 4x = 44), S is a diploid (2n = 2x = 22) with no tetraploid cells. In potatoes, polyploid potatoes exhibit higher gene content compared to diploid potatoes [29], and the weight and size of individual tubers in tetraploid potatoes are greater than those in diploid potatoes [30], which is similar to the situation observed in L and S. Meanwhile, plants of the same species with different ploidy levels exhibit significant differences in endogenous hormone levels [31] and the expression of hormone-related genes [32]. Therefore, variations in rhizome ploidy may affect endogenous hormone levels and the expression of related genes, thereby influencing the degree of rhizome bulking.

4.2. Role of Auxin, Cytokinin, and Salicylic Acid in Rhizome Bulking

Based on hormone level dynamics across growth stages, KEGG pathway enrichment, and OPLS-DA analysis, cytokinins, salicylic acid, and auxin were identified as the primary differential hormones between L and S. As a crucial auxin in plants, the variation in IAA levels has been consistently positively correlated with the degree of rhizome bulking. This observation not only aligns with previous studies on auxin dynamics during ginger rhizome development but is also supported by similar findings in other crops with underground storage organs, such as potato, sugar beet, sweet potato, and cassava (Manihot esculenta) [22,33,34,35,36].
During the seedling stage, both auxin (IAA) and cytokinins (e.g., tZ, oTR) exhibit elevated levels in the rhizomes of L in ginger. This pattern parallels the role of auxin and cytokinin in initiating tuber formation in potatoes [37,38]. However, during the rhizome bulking stage, cytokinin levels exhibit a negative correlation with the degree of rhizome bulking. This contrasts with reports on potatoes and sweet potatoes, where cytokinins are described to play a positive regulatory role in tuber or root bulking [39,40]. The possible reason is that excessively high cytokinin levels inhibit the bulking of rhizomes. As demonstrated in the study by Tao et al., the expression of PCHS-ipt (a cytokinin biosynthesis gene) elevated the cytokinin level in potato stems and leaves but resulted in decreased tuber weight [41]. Auxin may also influence cytokinin levels. Bishopp et al. demonstrated that elevated auxin levels promote the transcription of AHP6, a gene encoding a negative regulator of cytokinin signaling, thereby maintaining cytokinin homeostasis in Arabidopsis roots. Their findings were supported by hormone quantification and transcriptomic analysis [42]. Research on SA has predominantly focused on plant disease resistance and stress tolerance [43,44,45], while its role in regulating storage organ development remains scarcely reported [46]. Auxin and cytokinin may serve as the key hormones modulating the differential regulation of ginger rhizome bulking.

4.3. Potential Influence of ARF Genes on the Bulking of Ginger Rhizomes

Integrated hormone metabolome and transcriptome analysis identified critical differential hormones and their associated differentially expressed genes. The expression levels of ZoARF7 and ZoARF23 not only showed a positive correlation with the rhizome bulking stage but were also consistent with the bulking trend observed across different developmental stages of the rhizomes. ZoARF7 and ZoARF23 are likely to be key genes that positively regulate ginger rhizome bulking. Transcriptome analysis and qRT-PCR validation of rhizomes at different growth stages by Ren et al. and Zhou et al. revealed that ARF is likely involved in regulating rhizome formation [22,47]. Phylogenetic analysis of ARF protein in rice (Oryza sativa L.), Arabidopsis (Arabidopsis thaliana (L.) Heynh.), and potato revealed that ZoARF7 shares high sequence similarity with OsARF7, AtARF1, and StAR7, while ZoARF23 clusters closely with OsARF23, AtARF2, and StARF6 [48,49]. Functional inference of ZoARF7/23 can be deduced through advances in research on their orthologous genes, with these ARFs characterized as putative transcriptional repressors [50]. In rice, the overexpression of OsARF7 confirmed its function in positively regulating root elongation [51]. Through qRT-PCR analysis of potato tuber at different growth periods, it was found that the expression level of StARF6 in stolons and at the initial stage of tuber formation was higher than that in other periods [49]. Previous researchers utilized techniques such as constructing mutants, microscopic observation, and fluorescent probes to discover that a reduction in the expression of OsARF23/24 inhibits the expression of the Rice Morphology Determinant (RMD). This, in turn, suppresses the formation of actin filaments and cell elongation, thereby affecting the distribution gradient of auxin [52]. The aforementioned orthologous genes function as positive regulators in root or stem development and morphogenesis, which is similar to our prediction of ZoARF7/23 function.
However, conflicting findings have been reported. AtARF1/2 exhibits functional redundancy in Arabidopsis, primarily expressed in leaves and floral organs where they promote leaf senescence and floral organ abscission [53]. The heterologous expression of HbARF2 (an ortholog of AtARF2) suppresses pith cell expansion and negatively regulates plant height and stem diameter in tobacco (Nicotiana tabacum L.) [54]. These findings collectively underscore the functional diversity and mechanistic complexity inherent to the ARF gene family. However, the functional characterization of ZoARF7/23 using gain- and/or loss-of-function approaches has been hampered due to the considerable challenges in generating ginger transgenic plants. Therefore, subsequent work will focus on optimizing Agrobacterium infection conditions and selectable markers, as well as refining the ginger regeneration system, to enable the functional validation of ZoARF7 and ZoARF23.

5. Conclusions

This study identified auxin, cytokinin, and salicylic acid as key hormones that regulate ginger rhizome bulking, with IAA levels showing a positive correlation with rhizome bulking. Integrated analysis of transcriptomic profiling and qRT-PCR validation demonstrated that the expression dynamics of auxin response factor genes ZoARF7 and ZoARF23 were aligned with rhizome bulking patterns, suggesting their potential roles as positive regulators of ginger rhizome bulking. However, due to the current technical limitations of the ginger genetic transformation system, the functional validation of ZoARF7 and ZoARF23 could not be conclusively performed. This will become the primary focus of subsequent research efforts. The identification of key hormones and associated genes governing ginger rhizome bulking has not only established a theoretical foundation for elucidating the hormonal regulatory mechanisms underlying rhizome bulking but also provides theoretical support for future molecular breeding strategies in ginger.

Author Contributions

K.W.: Writing—original draft, Validation, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Y.L.: Data curation, Software. S.G.: Methodology, Software. Y.K. and M.L.: Investigation, Methodology, Validation. Z.C.: Resources, Software, Supervision, Validation, Writing—review and editing. K.X.: Funding acquisition, Project administration, Writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (grant No. 2023YFD1600202), the National Natural Science Foundation of China (Grant No. 32302530), and the Agricultural Fine Variety Project in Shandong Province of China (Grant No. 2023LZGCQY003).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Agronomy 15 00779 g0a1
Figure A1. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) permutation test histogram. Note: In the chart, the black arrow points to the positions of the values of R2X, R2Y, and Q2 on the X-axis.
Figure A1. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) permutation test histogram. Note: In the chart, the black arrow points to the positions of the values of R2X, R2Y, and Q2 on the X-axis.
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Table A1. Information on primers related to quantitative real-time PCR.
Table A1. Information on primers related to quantitative real-time PCR.
GenePrimer Sequence (5′ → 3′)Tm (°C)
ZoRPIIF: CTGCTGATGGATACGAATG60.0
R: CTGCCCAAGAGAATGAAAG
ZoARF7F: AACTGCGTGTTGGTGTCAGAGG61.0
R: CCGTAGTGATTGCGTGGGATGC
ZoARF23F: CAGCGGAAATGCGAGGACAGAG60.9
R: GATCGGAGAGAGCAGCGGAAATG
ZoARF17F: GTGGTGGAGGCATTCGGATTGG61.5
R: ACTCTCGCTCCTACGGTCCAAC
ZoGH3.1F: TGTTCGTGAAGTCGGAGGTTTGC61.4
R: TCGTCTGGGCGGTTGAGGAAG
ZoPIN1bF: CCATCAAGAAGGTCGGGCAGAAC61.8
R: CACTCGCAGGCGGCATCAAG
ZoARR9F: TCGGACATGACAAGGCTCAGACC61.4
R: TTGCTATTGCTGCTGCCACTGG
ZoPR1F: GGATCGGGCGACTGCCAAC63.2
R: TCCCACCCACAAGCCCACAG
ZoNPR1F: GAGCATCTCGCCTCCCTCCTC62.5
R: ACATCGGTGGACACGGACAGAG
ZoSABP2F: CGCCGCTTCGTTGACATCCG62.8
R: AGGCTGTGACCGACGAGGAC

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Figure 1. Phenotype of large ginger and small ginger. (A) VM0 generation of large ginger and small ginger, (B) VM1 generation of large ginger and small ginger, (C) VM2 generation of large ginger and small ginger, (D) VM3 generation of large ginger and small ginger, (E) seedling stage (6–15), (F) tillering stage (8–15), (G) rhizome bulking stage (9–15), and (H) harvest stage (10–15).
Figure 1. Phenotype of large ginger and small ginger. (A) VM0 generation of large ginger and small ginger, (B) VM1 generation of large ginger and small ginger, (C) VM2 generation of large ginger and small ginger, (D) VM3 generation of large ginger and small ginger, (E) seedling stage (6–15), (F) tillering stage (8–15), (G) rhizome bulking stage (9–15), and (H) harvest stage (10–15).
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Figure 2. Identification of ploidy of large ginger and small ginger. (A) Diploid control material, (B) mixoploid large ginger (L), and (C) diploid small ginger (S).
Figure 2. Identification of ploidy of large ginger and small ginger. (A) Diploid control material, (B) mixoploid large ginger (L), and (C) diploid small ginger (S).
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Figure 3. Chromosome karyotype of large ginger and small ginger. (A) Karyotype of large ginger (L) diploid cells, (B) karyotype of large ginger (L) tetraploid cells, and (C) karyotype of small ginger (S).
Figure 3. Chromosome karyotype of large ginger and small ginger. (A) Karyotype of large ginger (L) diploid cells, (B) karyotype of large ginger (L) tetraploid cells, and (C) karyotype of small ginger (S).
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Figure 4. The levels of common hormone metabolites in large ginger and small ginger at different growth periods. (A) Indole-3-acetic acid (IAA) levels in rhizomes at different growth periods, (B) gibberellic acid 1 (GA1) levels in rhizomes at different growth periods, (C) abscisic acid (ABA) levels in rhizomes at different growth periods, (D) trans zein (tZ) levels in rhizomes at different growth periods, (E) 1-Aminocyclopropanecarboxylic acid (ACC) in rhizomes at different growth periods. Note: In the figure, asterisks denote statistically significant differences between groups determined by independent samples t-tests (one asterisk denotes p < 0.05, and two asterisks denote p < 0.01). Error bars represent the standard deviation (n = 3). The label ‘Date (month-day)’ indicates the sampling time, with the four sampling time points corresponding to the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage of ginger, respectively.
Figure 4. The levels of common hormone metabolites in large ginger and small ginger at different growth periods. (A) Indole-3-acetic acid (IAA) levels in rhizomes at different growth periods, (B) gibberellic acid 1 (GA1) levels in rhizomes at different growth periods, (C) abscisic acid (ABA) levels in rhizomes at different growth periods, (D) trans zein (tZ) levels in rhizomes at different growth periods, (E) 1-Aminocyclopropanecarboxylic acid (ACC) in rhizomes at different growth periods. Note: In the figure, asterisks denote statistically significant differences between groups determined by independent samples t-tests (one asterisk denotes p < 0.05, and two asterisks denote p < 0.01). Error bars represent the standard deviation (n = 3). The label ‘Date (month-day)’ indicates the sampling time, with the four sampling time points corresponding to the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage of ginger, respectively.
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Figure 5. The levels of hormone metabolites in rhizomes at different growth periods. Note: In the figure, the label ‘month-day’ indicates the sampling time, with the four sampling time points corresponding to the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage of ginger, respectively.
Figure 5. The levels of hormone metabolites in rhizomes at different growth periods. Note: In the figure, the label ‘month-day’ indicates the sampling time, with the four sampling time points corresponding to the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage of ginger, respectively.
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Figure 6. KEGG functional classification and OPLS-DA analysis of hormone metabolites in ginger rhizomes. (A) KEGG pathways enrichment results of differential hormone during rhizome bulking stage, (B) OPLS-DA analysis of hormone in large ginger and small ginger, and (C) VIP scores of hormone in large ginger and small ginger samples based on OPLS-DA analysis. Note: In Figure 6B, LT and ST represent the tillering stage of Large ginger and Small ginger, respectively; LR and SR denote the rhizome bulking stage of Large ginger and Small ginger, respectively; LH and SH indicate the harvest stage of Large ginger and Small ginger, respectively.
Figure 6. KEGG functional classification and OPLS-DA analysis of hormone metabolites in ginger rhizomes. (A) KEGG pathways enrichment results of differential hormone during rhizome bulking stage, (B) OPLS-DA analysis of hormone in large ginger and small ginger, and (C) VIP scores of hormone in large ginger and small ginger samples based on OPLS-DA analysis. Note: In Figure 6B, LT and ST represent the tillering stage of Large ginger and Small ginger, respectively; LR and SR denote the rhizome bulking stage of Large ginger and Small ginger, respectively; LH and SH indicate the harvest stage of Large ginger and Small ginger, respectively.
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Figure 7. Volcano plot and Venn diagram of DEGs during rhizome bulking stage. (A) Volcano plot, (B) Venn diagram of DEGs. Note: Blue dots represent genes with non-significant differential expression (adjusted p-value, padj > 0.05).
Figure 7. Volcano plot and Venn diagram of DEGs during rhizome bulking stage. (A) Volcano plot, (B) Venn diagram of DEGs. Note: Blue dots represent genes with non-significant differential expression (adjusted p-value, padj > 0.05).
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Figure 8. Analysis of gene expression level related to auxin, cytokinin, and salicylic acid. Note: In the figure, asterisks denote statistically significant differences between groups determined by independent samples t-tests (two asterisks denote p < 0.01). Error bars represent the standard deviation (n = 3).
Figure 8. Analysis of gene expression level related to auxin, cytokinin, and salicylic acid. Note: In the figure, asterisks denote statistically significant differences between groups determined by independent samples t-tests (two asterisks denote p < 0.01). Error bars represent the standard deviation (n = 3).
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Figure 9. Analysis of ZoARF7 and ZoARF23 expression at different growth periods. (A) ZoARF7 expression at different growth periods and (B) ZoARF23 expression at different growth periods. Note: In the figure, the label ‘Date (month-day)’ indicates the sampling time, with the four sampling time points corresponding to the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage of ginger, respectively. In the figure, asterisks denote statistically significant differences between groups determined by independent samples t-tests (two asterisks denote p < 0.01). Error bars represent the standard deviation (n = 3).
Figure 9. Analysis of ZoARF7 and ZoARF23 expression at different growth periods. (A) ZoARF7 expression at different growth periods and (B) ZoARF23 expression at different growth periods. Note: In the figure, the label ‘Date (month-day)’ indicates the sampling time, with the four sampling time points corresponding to the seedling stage, the tillering stage, the rhizome bulking stage, and the harvest stage of ginger, respectively. In the figure, asterisks denote statistically significant differences between groups determined by independent samples t-tests (two asterisks denote p < 0.01). Error bars represent the standard deviation (n = 3).
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Table 1. Analysis of growth indicators during harvest stage of large ginger and small ginger.
Table 1. Analysis of growth indicators during harvest stage of large ginger and small ginger.
GenerationPlant
Height		Stem DiameterShoot
Number		Root FWStem FWLeaf FWRhizome FWLeaf Number of the Main Stem
(cm)(mm)(g/Plant)(g/Plant)(g/Plant)(g/Plant)
VM1L94.8 ± 3.912.5 ± 0.416.7 ± 0.6116.0 ± 6.2580.4 ± 48.6226.8 ± 17.51014.9 ± 27.827.3 ± 1.2
S84.4 ± 1.1 **9.4 ± 0.5 **50.3 ± 1.5 **223.5 ± 14.6 **824.3 ± 55.5 **319.2 ± 36.7 **513.7 ± 25.4 **28.0 ± 2.0
VM2L99.8 ± 4.113.2 ± 0.224.7 ± 2.1131.9 ± 6.7604.2 ± 44.7262.9 ± 23.81033.3 ± 36.927.3 ± 1.2
S86.5 ± 3.6 **9.3 ± 0.5 **59.7 ± 3.1 **249.6 ± 12.2 **859.5 ± 36.9 **349.8 ± 33.7 **553.8 ± 34.9 **29.3 ± 1.2
VM3L109.8 ± 7.814.3 ± 1.326.0 ± 1.7129.6 ± 6.2593.6 ± 53.1241.9 ± 16.61101.4 ± 100.825.3 ± 2.3
S86.8 ± 3.7 **10.7 ± 0.9 **62.3 ± 1.5 **254.1 ± 19.3 **855.3 ± 55.5 **346.5 ± 35.3 **530.8 ± 25.4 **25.3 ± 4.2
Note: FW is the abbreviation for fresh weight, Values (mean ± standard deviation) within the same generation followed by an asterisk (**) indicate significant difference at the 1% level.
Table 2. Analysis of karyotype parameters of large ginger and small ginger.
Table 2. Analysis of karyotype parameters of large ginger and small ginger.
VarietyNo.Relative Lengths (%)Arm RatioCentromere Index (%)Chromosomal TypeNo.Relative Lengths (%)Arm RatioCentromere Index (%)Chromosomal
Type		As.K.
(%)		Karyotypic Type
Short ArmLong ArmTotal LengthShort ArmLong ArmTotal Length
LDiploid
cells		14.227.5211.741.7835.95sm73.305.488.781.6637.59m63.562A
24.166.5310.691.5738.91m83.505.088.581.4540.79m
33.566.409.961.8035.74sm92.715.548.252.0532.85sm
43.506.079.571.7436.57sm102.644.627.261.7536.36sm
53.176.349.512.0033.33sm112.713.76.411.3742.28m
62.976.279.242.1132.14sm
Tetraploid cells14.237.3611.591.7436.50sm73.015.888.901.9533.87sm62.902A
24.296.4110.701.4940.11m83.365.168.521.5439.46m
33.017.4210.432.4628.89sm93.484.528.001.3043.48m
43.576.359.911.7835.96sm102.524.206.731.6737.50m
53.136.679.802.1331.95sm112.613.716.321.4241.29m
63.885.229.101.3442.68m
SDiploid cells14.217.6411.851.8235.51sm73.654.988.631.3742.28m64.452A
24.286.6610.941.5639.10m82.386.178.562.5927.87sm
33.446.529.961.9034.51sm93.165.198.351.6437.82m
43.446.179.611.8035.77sm102.384.496.871.8834.69sm
53.096.459.542.0932.36sm112.673.796.451.4241.31m
62.886.389.262.2231.06sm
Note: The relative length (%) = (the length of a single chromosome/the total length of the haploid chromosome set) × 100%, the arm ratio = the length of the long arm/the length of the short arm, the centromere index (%) = (the length of the short arm/the length of the long arm) × 100%, the karyotype asymmetry index (As.K.%) = (the total length of the chromosome long arms/the total length of all chromosomes) × 100%.
Table 3. Differential expression genes (DEGs) related to auxin, cytokinin, and salicylic acid.
Table 3. Differential expression genes (DEGs) related to auxin, cytokinin, and salicylic acid.
Unigene IDAnnotationlog2FoldChangep-Value
Auxin-Related Genes
i3_LQ_ZR_c21855/f1p1/3608auxin response factor 75.17864.64 × 10−8
i2_LQ_ZR_c19192/f1p0/2780auxin response factor 23Inf5.02 × 10−6
i2_LQ_ZR_c59231/f1p0/2020indole-3-acetic acid-amido synthetase GH3.12.10616.73 × 10−6
i2_LQ_ZR_c53301/f1p0/2680auxin efflux carrier component 1b1.93881.03 × 10−5
i3_HQ_ZR_c81940/f26p0/3334auxin response factor 710.4731.81 × 10−5
i6_LQ_ZR_c2184/f1p0/6466auxin response factor 235.09871.82 × 10−5
i3_LQ_ZR_c59597/f1p1/3518auxin response factor 17−2.45217.97 × 10−5
i3_HQ_ZR_c35172/f2p2/3385auxin response factor 71.63620.000132
Cytokinin-Related Genes
i2_LQ_ZR_c20879/f1p8/2289two-component response regulator ARR9−2.60221.73 × 10−6
i0_LQ_ZR_c6058/f1p7/795two-component response regulator ARR9−3.36332.96 × 10−5
i1_LQ_ZR_c33483/f1p0/1060two-component response regulator ARR9−2.18163.86 × 10−6
i1_LQ_ZR_c27791/f1p0/1034two-component response regulator ARR9−2.35561.49 × 10−6
Salicylic Acid-Related Genes
i0_LQ_ZR_c12160/f1p0/670pathogenesis-related protein 1−3.53480.000257
i3_LQ_ZR_c19736/f1p0/3757ankyrin repeat-containing protein NPR1−Inf1.55 × 10−6
i1_LQ_ZR_c22124/f1p3/1057salicylic acid-binding protein 2−1.78172.64 × 10−5
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Wang, K.; Lv, Y.; Gao, S.; Kong, Y.; Liu, M.; Chen, Z.; Xu, K. Integrated Analysis of Hormone Metabolomics and Transcriptomics Reveals the Differential Mechanism of Ginger (Zingiber officinale Roscoe) Rhizome Bulking. Agronomy 2025, 15, 779. https://doi.org/10.3390/agronomy15040779

AMA Style

Wang K, Lv Y, Gao S, Kong Y, Liu M, Chen Z, Xu K. Integrated Analysis of Hormone Metabolomics and Transcriptomics Reveals the Differential Mechanism of Ginger (Zingiber officinale Roscoe) Rhizome Bulking. Agronomy. 2025; 15(4):779. https://doi.org/10.3390/agronomy15040779

Chicago/Turabian Style

Wang, Kai, Yao Lv, Song Gao, Yuwen Kong, Miaohong Liu, Zijing Chen, and Kun Xu. 2025. "Integrated Analysis of Hormone Metabolomics and Transcriptomics Reveals the Differential Mechanism of Ginger (Zingiber officinale Roscoe) Rhizome Bulking" Agronomy 15, no. 4: 779. https://doi.org/10.3390/agronomy15040779

APA Style

Wang, K., Lv, Y., Gao, S., Kong, Y., Liu, M., Chen, Z., & Xu, K. (2025). Integrated Analysis of Hormone Metabolomics and Transcriptomics Reveals the Differential Mechanism of Ginger (Zingiber officinale Roscoe) Rhizome Bulking. Agronomy, 15(4), 779. https://doi.org/10.3390/agronomy15040779

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