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Chrysanthemum × grandiflora leaf and root transcript profiling in response to salinity stress

Abstract

As high soil salinity threatens the growth and development of plants, understanding the mechanism of plants’ salt tolerance is critical. The Chrysanthemum × grandiflora is a newly developed species with a strong salt resistance that possesses multiple genes controlling its quantitative salt resistance. Because of this multigene control, we chose to investigate the plant stress genes overall responses at the transcriptome level. C. grandiflora were treated with a 200 mM NaCl solution for 12 h to study its effect on the roots and leaves via Illumina RNA sequencing. PAL, CYP73A, and 4CL in the phenylpropanoid biosynthesis pathway were upregulated in roots and leaves. In the salicylic acid signal transduction pathway, TGA7 was upregulated in the roots and leaves, while in the jasmonic acid signal transduction pathway, TIFY9 was upregulated in the roots and leaves. In the ion transporter gene, we identified HKT1 that showed identical expression patterns in the roots and leaves. The impact of NaCl imposition for 12 h was largely due to osmotic effect of salinity on C. grandiflora, and most likely the transcript abundance changes in this study were due to the osmotic effect. In order to verify the accuracy of the Illumina sequencing data, we selected 16 DEGs for transcription polymerase chain reaction (qRT-PCR) analysis. qRT-PCR and transcriptome sequencing analysis revealed that the transcriptome sequencing results were reliable.

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Introduction

Soil salinity is a serious global threat to the environment and to agricultural production. Currently, more than 20% of the world’s arable land (1 billion hectares) is affected by salinity, and this number is increasing due to global climate change and poor irrigation and fertilization management. Generally, when the salt content of the soil exceeds 1%, it becomes difficult for plants to grow. Salt stress affects the various stages of plant seed germination, growth, differentiation, and development. The study of plant salt tolerance and the development of salt-tolerant plant varieties are critical for environmentally sustainable development [1, 2]. At present, salt tolerance and the potential mechanisms of salt tolerance of a large number of plant varieties have been studied, such as Arabidopsis [3, 4], tobacco [5], corn [6] and tomato [7]. Research on soybeans [8] and rice [9] have shown that the method of increasing the plant expression of intrinsic salt tolerance genes can effectively enhance their salt tolerance.

Salinity stress has a significant impact on plant growth and development. First, salt stress reduces plant water absorption capacity and inhibits their growth. This is called osmotic stress, in which lowering the soil solution water potential by high level of salts induces an early osmotic stress, whereas ionic imbalance and toxicity occurs after a longer time of stress [10]. If excessive salt enters the transpiration stream of plants, it damages cells in the leaves, thus further affecting plant growth. When the salt level reaches a threshold value, the plant cannot maintain an ion balance, which can also cause secondary reactions such as oxidative stress [11]. Studies have shown that under salt stress conditions, more transcriptome changes were observed in the root tissue than in the leaf tissue of the Chrysanthemum cultivar ‘Jinba’ [12]. Its response to stress was mainly manifested in the downregulation of genes in the leaves and roots. Under drought conditions and salt stress, transcriptome changes were observed more in the leaf tissue compared with the root tissue of Chrysopogon zizanioides. The response to stress in the transcriptome of C. zizanioides was mainly manifested in the upregulation of genes in the leaves and roots [13]. Finally, when comparing root with leaf tissues in Rosa chinensis under drought conditions, the transcriptome underwent more changes in the leaf tissues, with a downregulation of genes in the leaves and roots [14].

Generally, plants respond to salt stress by developing a series of morphological, physiological, biochemical, and molecular regulation mechanisms to ensure normal growth and development. These mechanisms include osmotic regulation, ion homeostasis, signal transduction, and the induction of antioxidant enzyme activity. Salt tolerance is a complex trait controlled by genetic factors. The functions of many salt-responsive genes involve the regulation of ion accumulation, stress signal transduction, transcription regulation, redox reactions, and the accumulation of specific osmolytes [15]. Transgenic plants with different degrees of enhanced salt tolerance can be obtained by controlling the expression of some salt tolerance genes. These genes include HKT (high affinity potassium transporter) [16], AKT (K+ channel gene) [17], NHX (Na+/ H+ antiporter gene) [18], WRKY transcription factor gene [19], NAC transcription factor gene [20], bZIP transcription factor gene [21], and ERF transcription factor gene [22].

The C. grandiflora is a new ground-planted chrysanthemum species selected after natural hybridization and satellite loading based on the introduction of ground cover chrysanthemums (Chrysanthemum morifolium). C. morifolium characterized by its long flowering period, copious dense flowers, bright color, as well as high resistance to stress. This new species has become a popular urban green ground cover plant in recent years [23]. Transcriptome sequencing was used to find C. grandiflora genes that were resistant to abiotic stress, and thus provides a physical foundation to improve plant stress resistance and to provide new stress-resistant materials; both would have a great significance in the study of chrysanthemum germplasm resources. Current studies have shown that when the chrysanthemum is exposed to salt stress, genes encoding proteins related to osmotic regulation, ion transport (Na+, K+, and Ca2+ transport), ROS scavenging, and ABA signaling are all affected in the roots and leaves [12]. Osmotic regulation genes and Ca2+ transport genes overlap in the roots and leaves after salt treatment, which may serve as the main regulator of the plant salt response. These results indicate that the regulation of the transcriptome plays a key role in the morphological and physiological adaptation of chrysanthemum roots and leaves in response to salt stress [12]. In our research, we discovered the key metabolic pathways, a large number of salt-tolerant genes, and the underlying mechanisms of adaptation of C. grandiflora in response to salt stress.

Materials and methods

Plant materials and experimental design

Chrysanthemum×grandiflora is a new chrysanthemum variety cultivated in Northeast Forestry University. It is a new ground-grown chrysanthemum variety group based on the introduction of Chrysanthemum morifolium, after natural hybridization and satellite loading. The stem explants collected from the mother plant were rinsed in tap water for 60 min. The stems were sterilized with 75% ethanol solution for 30 s, rinsed with sterile distilled water for 1 min, and soaked in a 4% sodium hypochlorite solution for 10 min. The stems were then rinsed with sterile, distilled water 5 times, placed on sterile filter paper to absorb the water, and cut open into sections about 2.5 cm long. One or more of the shoots were inoculated in MS medium. When the plant had grown 7–8 cotyledons, the seedlings were transplanted into plastic pots with a diameter of 10 cm, a bottom diameter of 7.3 cm, and a height of 8.5 cm, and the cultivation substrate was humus: vermiculite: perlite (2:1:1, v/v/v), pH 6.65 [24].

In our previous study, it was found that when C. grandiflora was treated with 200 mM NaCl solution concentration, and compared with the control group in the normal growth environment, the treated plants showed an obvious stress response, such as changes in plant morphology, antioxidant enzyme systems, and ion accumulation, and therefore this concentration was used in the current work. When the plants had grown 9–10 leaves, they were treated with 200 mM NaCl. We irrigated with 60 mL of 200 mM NaCl at 8 am. After 12 h of treatment, all the root and leaf samples of the treated and the control groups were taken for transcriptome sequencing. Root and leaf samples were collected at 0, 0.5, 3, 6, and 9 d after plant cultivation to determine the relative water content of leaves, Na+, K+, and H2O2 content and SOD, POD, and CAT activity.

The plant growth media contained 30 g/L sucrose and 0.6% (w/v) agar and was adjusted to pH 5.8–6.0 and autoclaved at 121 °C for 20 min. The plants were grown in plant culture pots (11 cm high × 7 cm diameter, 300 mL) and placed in an air-conditioned incubator with a temperature of 25 °C ± 2 °C, a relative humidity of 50–70% and a G13 fluorescent lamp (Philips, Tianjin, China) as a light source, the light intensity was 75 μmol m− 2 s− 1.

Determination of antioxidant enzyme activity and H2O2 content

From the roots and leaves, 0.1 g fresh weight were taken and the antioxidant enzyme activity was measured on 0, 0.5, 3, 6 and 9 d. The activities of SOD (U/g FW), POD (U/g FW), and CAT (nmol/min/g FW), and the content of H2O2 (μmol/g FW) were determined according to the instructions included in the chemical analysis kit (Solebao Technology Co., Ltd., Beijing, China). Experimental methods are available at https://www.solarbio.com/. One-way anova analysis of variance was performed, and then Dunnett’s test in SPSS26 was used to compare the means of all treatments..

Determination of Na+ and K+ content

The collected root and leaf samples were dried at 80 °C for 2 d. The samples were then ground into powder, and 1 mM HCl was added to the samples to react for 12 h. The volume of the filtered solution was adjusted to 50 mL, and the content of Na+ and K+ was measured using 4210MP-AES (Agilent Technology, USA) [25].

Transcriptome sequence annotation

Based on the original data, we calculated the proportion of unknown nucleotides, and the base (Q20) base recognition accuracy exceeded 99.0%. In order to annotate the reassembled sequence, after cleaning the original reader and processing the poor-quality reader, the assembled transcript was aligned with NCBI (https://www.ncbi.nlm.nih.gov/; June 2021, 1st visit).

Gene expression level analysis

FPKM was used to calculate gene expression levels through density distribution and analysis of the number of selected transcripts, and the expression of all the samples was analyzed. According to the results of FPKM, the correlation between the samples was calculated to determine the stability and reliability of the experimental operation.

Identification and functional annotation of DEGs

The DEGs were mapped to each item in the GO database. The hypergeometric test method was used to detect significantly rich GO annotations. The corrected P value was < 0.05. In addition, the hypergeometric test calculated the number of DEGs at different levels to determine the main pathways involved in salt tolerance. When P < 0.05, the KEGG pathway was significantly enriched [26, 27].

qRT-PCR analysis

For qRT-PCR analysis in the KEGG enrichment pathway, 16 candidate genes, including 8 upregulated genes and 8 downregulated genes, were randomly selected. The Roche LightCycler96® system was used for qRT-PCR. The differential expression analysis of each candidate gene used the 2-CT method, and each candidate gene was repeated three times [28].

Results

Effects of salt stress on the contents of Na+ and K+ and the activities of antioxidant-related enzymes in the roots and leaves of C. grandiflora

After treatment with 200 mM NaCl solution, the growth of C. grandiflora in the control group was significantly better than the growth of those in the treatment group (Fig. 1a). As the treatment time increased, the relative water content of leaves gradually decreased (Table 1). The activity of superoxide dismutase (SOD) in the roots and leaves increased initially and then decreased (Fig. 1b). The SOD activity of the roots and leaves on the sixth day of treatment was significantly higher than the activity at the other time points. The peroxidase (POD) activity in the roots and leaves (Fig. 1c) showed a trend of an initial increase followed by a subsequent decrease. The POD activity of the roots was significantly higher at Day 6 of treatment than at the other time points, and the activity of the leaves was significantly higher than at the other time points at Day 3 of treatment. CAT activity in the roots and leaves showed a trend of an initial increase followed by a subsequent decrease similar to that of POD. CAT activity in the roots at Day 3 and in the leaves at Day 6 were significantly higher than at the other time points in the treatment (Fig. 1d). The H2O2 content in both the roots and the leaves increased over the course of treatment with the most significant content change occurring after Day 3 in the roots and after Day 9 in the leaves (Fig. 1e). The Na+ content in both the leaves and the roots increased as well with the greatest Na+ change occurring in the roots and the leaves at Day 9 of treatment (Fig. 1f). The K+ content showed a downward trend in both the roots and the leaves with the most significant change in K+ concentration occurring after Day 3 for both the leaves and the roots (Fig. 1g). Under salt stress, antioxidant enzyme activities and ion accumulation in the roots and leaves of C. grandiflora began to change after 12 h of 200 mM NaCl treatment, indicating that the expression of salt stress-responsive genes were upregulated. Therefore, we used RNA-seq to analyze the root and leaf samples of C. grandiflora during the 12 h salt stress treatment.

Fig. 1
figure 1

The effect of 200 mM NaCl exposure on the growth, enzymatic antioxidant activities, ion and H2O2 contents of C. grandiflora: (a) growth phenotype, (b) SOD, (c) POD, (d) CAT, (e) H2O2, (f) Na+, (g) and K+. ** (P < 0.01) represents highly significant differences and * (P < 0.05) represents significant differences for the specified treatment based on Dunnett’s test

Table 1 Relative water content of leaves of C. grandiflora leaves under 200 mM NaCl stress. The data are the mean ± standard error

Assembly and transcriptome quality assessment

Twelve samples were sequenced on the Illumina sequencing platform. Among them, there were 558,054,470 original fragments. By removing low-quality areas and adapters, 543,328,476 clean readings remained, Q20 > 97.05% (Table S1). Figure S1 shows the transcriptome’s quality and single gene length distribution.

Transcriptome annotation

Using BLAST to screen data with an E value of <1e-5, there were 31,181 (79.57%) unigenes matching the known genes in the NR database, and 21,333 (54.44%) unigenes matching the Swiss-Prot database (Table S2). The sequence with the highest annotation rate in the NR database (E value <1e-45) was 32.70% (Fig. S2a). Approximately 70.54% of the unigenes were similar to the identified sequence (Fig. S2b). Among the following 6 species, about 94.30% of the single gene annotations matched C. grandiflora, including mugwort (79.55%), sunflower (4.97%), thistle (4.75%), lettuce (3.46%), chrysanthemum (1.08%), and grapes (0.42%) (Fig. S2c).

Unigenes’ EggNOG functional categories annotation

Comparing the unigenes with the eggNOG database, we found that 28,580 unigenes in C. grandiflora could be classified into 24 categories according to the prediction function (Fig. 2). Unknown function is the most annotated category among these eggNOG categories, followed by post-translational modification, protein renewal, chaperone protein, and nuclear structure in that order.

Fig. 2
figure 2

EggNOG functional classification of all unigenes in C. grandiflora

Gene expression and differentially expressed gene analysis

According to the hierarchical clustering analysis of the differentially expressed gene expression pattern, we found that there were more downregulated expressed genes in the samples of C. grandiflora (Fig. 3). Comparing the treatment group with the control group, there were more DEGs in the leaves (Fig. 4a), and the ratio of DEGs in the NR database was 79.57%. A total of 3094 DEGs were obtained from the roots treated for 12 h, and 7880 DEGs were obtained from the leaves treated for 12 h (Fig. 4b). In the roots, there were 1297 upregulated genes, while in the leaves there were upregulated genes.

Fig. 3
figure 3

Differentially expressed gene (DEG) expression analysis: (a) A volcano map of DEGs in S200_R vs SCK_R, and (b) A volcano map of DEGs in S200_L vs SCK_L

Fig. 4
figure 4

Venn diagram analysis of the number of DEGs after 12 h of NaCl treatment: (a) Venn diagram analysis of DEGs annotated in the NR database, and (b) the number of DEGs upregulated and downregulated after 12 h of 200 mM NaCl imposition

DEGs GO annotation enrichment analysis

There was a total of 135,710 genes annotated in the GO database in the C. grandiflora library undergoing salt stress for 12 h. Among them, there were 49,890 unigenes for biological processes; 45,951 unigenes for cell components; and 39,869 unigenes for molecular functions, including nuclear, cytoplasmic, and cytoplasmic genes. The number of DEGs enriched in membranes, membrane components, and the cytosol was the largest (Fig. 5a). A total of 13,245 genes in the root library were annotated in the GO database. Within these genes, there were 5116 unigenes for biological processes; 4159 unigenes for cell components; and 3970 unigenes for molecular functions, including nuclear, plasma membrane, cytoplasm, and membrane components. The number of DEGs enriched in protein binding was the largest (Fig. 5b). There were 33,729 genes in Ye’s library annotated in the GO database. Among them, there were 12,524 unigenes for biological processes; 11,271 unigenes for cell components; and 9934 unigenes for molecular functions, including nuclear, plasma membrane, cytoplasm, and membrane components. The number of DEGs enriched in chloroplasts was the largest (Fig. 5c).

Fig. 5
figure 5

Classification of unigenes of GO annotation of C. grandiflora: (a) S200_R vs SCK_R vs S200_L vs SCK_L, (b) S200_R vs SCK_R, and (c) S200_L vs SCK_L

Enrichment analysis of the KEGG pathway of DEGs

There was a total of 14,059 genes annotated in 140 KEGG pathways in the library of C. grandiflora undergoing salt stress for 12 h. Among these genes, differences could be seen in ribosomes, protein processing in the endoplasmic reticulum, plant hormone signal transduction, spliceosomes, and plant pathogen interaction pathways. The number of expressed genes was the most enriched (Fig. 6a). A total of 1417 genes in the root library were annotated in 120 KEGG pathways. Of these genes, phenylpropane biosynthesis, protein processing in the endoplasmic reticulum, starch and sucrose metabolism, plant hormone signal transduction, and galactose metabolism pathways were abundant in DEGs. The number of sets was the largest (Fig. 6b). There was a total of 3480 genes in Ye’s library annotated in 132 KEGG pathways, among which are DEGs in plant pathogen interactions, plant hormone signal transduction, protein processing in the endoplasmic reticulum, starch and sucrose metabolism, and phenylpropane biosynthesis pathways. The number of enrichments was the largest (Fig. 6c).

Fig. 6
figure 6

Enrichment analysis of the KEGG pathway of DEGs in C. grandiflora: (a) S200_R vs SCK_R vs S200_L vs SCK_L, (b) S200_R vs SCK_R, and (c) S200_L vs SCK_L

Analysis of DEGs of plant salt stress-induced transporters

Although 200 mM NaCl stress for 12 h induced osmotic stress in plants, different ion transporter genes were also modulated, either upregulated or downregulated in the roots and leaves. This is because in order to maintain ion homeostasis and osmotic adjustment under saline conditions, tolerant plants like C. grandiflora modify the ion transporters activities to achieve this task [29]. In this study, the root transport genes HKT1, AKT1, AKT2, NHX2, NHX3, NHX5, and CLC-A were all upregulated, and CLC-B genes were downregulated. In the leaves, the salt stress transporter genes HKT1, CHX17, CHX18, AKT2, and NHX3 were upregulated, and AKT1, CLC-C, and CLC-D were downregulated. We found that the accumulation of Na+ in roots was greater than that in leaves after salt stress, while the accumulation of K+ in leaves was more, indicating that ion transporter genes could limit the transport of Na+ to shoots while maintaining a higher K+ content. The expression and regulation of genes related to ion transport such as HKT, AKT and NHX were changed afterward, so that C. grandiflora. Showed better osmotic regulation ability and maintained high biofilm stability, thus adapting to the salt stress environment (Table 2).

Table 2 Differential genes related to salt stress-induced transporters

Analysis of DEGs in the phenylpropanoid biosynthesis pathway

Phenylpropane compounds play an important role in plant growth, development, and response to adverse stresses. The phenylpropane biosynthesis pathway is important for plant secondary biomass metabolism. All substances containing the phenylpropane skeleton are the direct or indirect products of this pathway, and these compounds play a critical role in the growth, development, and resistance of plants. Phenylpropane biosynthesis also has an important physiological significance in plants, which is mainly manifested by changes in enzyme activity and the differentiation of intermediate products, further transformation products, and cells in plant development. In this study, there were 268 DEGs annotated in the phenylpropanoid biosynthesis pathway in the C. grandiflora samples. In the phenylpropane synthesis pathway in the roots, all 17 of the DEGs were upregulated, including PAL (10), CYP73A (5), and 4CL (2). On the other hand, in the phenylpropane synthesis pathway in the leaves, there were 25 DEGs, of which 24 were upregulated, including PAL (16), CYP73A (5), and 4CL (3). We found that there were more upregulated genes in the leaves, indicating that under conditions of salt stress, phenylpropane biosynthesis in C. grandiflora leaves was more active, thereby providing leaves with more salt stress resistance (Table 3, Fig. 7).

Table 3 Differentially expressed genes in the phenylpropanoid biosynthesis pathway
Fig. 7
figure 7

DEGs in the phenylpropane biosynthesis pathway under 200 mM NaCl stress, (a) Roots, (b) leaves

Analysis of DEGs in the plant hormone signal transduction pathway

Phytohormones are key endogenous factors that mediate plant stress responses, and they play an important role in plant defense and response to environmental stimuli. In the plant hormone signal transduction pathways of this study, a total of 329 DEGs were found. We focused on the salicylic acid and jasmonic acid signal transduction pathways. The results showed that there were 7 DEGs in the salicylic acid signal transduction pathway in the C. grandiflora samples, of which 6 genes were upregulated and 1 gene was downregulated; there were 13 DEGs in the jasmonic acid signal transduction pathway, of which 11 genes were upregulated and 2 genes were downregulated. In the leaves and roots, both signal transduction pathways revealed DEGs that were annotated. TGA7 was upregulated and PR1B1 was downregulated in the salicylic acid signal transduction pathway in the roots. In the jasmonic acid signal transduction pathway, TIFY9 was upregulated, and COI2 was downregulated in the roots. NPR1, NPR2, NPR3, TGAL5, and TGA7 in the salicylic acid signal transduction pathway in the leaves were all upregulated. Similarly, TIFY10B, TIFY9, TIFY10A, TIFY6A, TIFY6B, MYC2, MYC4 and AIB were all upregulated in the jasmonic acid signal transduction pathway in the leaves, yet GH3.5 and COI were downregulated. By comparing the expression patterns of DEGs in the roots and leaves, we found that the number of leaf genes in both the salicylic and jasmonic acid signal transduction pathway was relatively larger than roots. The differential gene expression patterns of the salicylic and jasmonic acid signal transduction pathways in the leaves and roots were similar (Table 4, Fig. 8).

Table 4 Differentially expressed genes of the plant hormone signal transduction pathways
Fig. 8
figure 8

The salicylic acid and jasmonic acid signal transduction pathways: salicylic acid (a) roots, (b) leaves; jasmonic acid (c) roots, (d) leaves

Differentially expressed transcription factor analysis

As transacting factors, transcription factors can bind to cis-acting element regions upstream of the target gene through the protein structure specific DNA binding region, thereby activating the expression of the target gene. This transcription level regulation is the most important way to regulate gene expression. From a protein structure analysis, a transcription factor is composed of a DNA binding region, a transcription regulatory domain, an oligomerization site, and a nuclear localization signal. These functional regions determine a transcription factor structure and characteristics. According to the characteristics of DNA binding regions, transcription factors can be divided into different families. In this study, a total of 1604 transcription factors from 54 families were annotated. Among them, the transcription factor families bHLH, NAC, MYB, ERF, WRKY, and bZIP had the most annotated transcription factors, which were 171, 139, 101, 88, 82, and 75, respectively (Table 5, Fig. 9).

Table 5 Analysis of differentially expressed transcription factors
Fig. 9
figure 9

Heat map of transcription factor family expression

Analysis of gene expression with qRT-PCR

We selected 16 candidate DEGs for transcription polymerase chain reaction (qRT-PCR) analysis to verify the accuracy of the Illumina sequencing data. In the two processing parts, qRT-PCR and RNA-seq analysis showed that the single gene expression trend was basically the same (Fig. S3). The gene expression results revealed that the transcriptome sequencing data reflected the response of the roots and leaves of the C. grandiflora to NaCl stress.

Discussion

Under saline conditions, plants utilize a series of physiological and biochemical responses to cope with the stressful effects [30]. Excessive salt in the growth medium induces osmotic stress and causes plant cells to lose water, while long term salinity stress causes nutrient imbalance and ion toxicity [31]. Salinity-induced oxidative stress is a secondary stress due to the increase in reactive oxygen species that leads to metabolic disorders and a decline in photosynthetic efficiency [32]. Excessive amounts of active oxygen leading to an excessive membrane peroxidation reaction, which produces harmful substances like malondiene. In order to cope with the increase in active oxygen, plants own peroxidation protection enzyme systems (e.g., SOD, POD, and CAT) [13]. In this study, the tissue water content of C. grandiflora showed a downward trend, which indicates a water deficit induction by NaCl imposition at short term salinity, and ionic effect at long term salinity [10]. Osmotic stress reduces the ability of plants to absorb water; this phase is short-lived resulting in stomatal closure and inhibition of cell expansion in the bud [10, 32]. In response to osmotic stress, tolerant plants synthesize and accumulate compatible osmolytes and/or inorganic ions (provided they are compartmentalized into vacuoles to reduce their cytotoxicity) in order to maintain water absorption and turgor pressure, thereby alleviate plant growth inhibition [33,34,35]. In the present study, the accumulation of Na+ in C. grandiflora may contribute to osmotic adjustment, thereby allowing C. grandiflora to adapt to the salinity stress.

The enzyme activities of SOD, POD, and CAT of C. grandiflora initially increased followed by a subsequent decrease with time and with increasing salt concentrations. This response might indicate that after long time and high concentration of salt imposition, antioxidant enzymes’ effectiveness was greatly inhibited to scavenge excessive reactive oxygen species. Alternatively, non-enzymatic antioxidants may increase and take a role to eliminate the hazardous impact of ROS [36].

Studies have shown that under salt stress, Na+ enters the cell through nonselective cation channels and causes plasma membrane depolarization, which in turn activates the outward K+ channel, allowing K+ to flow out of the cell [37]. In this study, with an increase in time under salt stress, the Na+ content gradually increased and the K+ content gradually decreased in the roots and leaves of C. grandiflora, which agrees with the previous studies. There are a large number of ion transporter genes that play important roles in the process of ion transport in plants such as HKT, NHX and AKT [38]. During Na+ transport in plants, HKT is located on the plasma membrane while NHX is located on the vacuolar membrane [39]. HKT is responsible for the recovery of Na+ entering the root xylem into xylem parenchyma cells, thereby reducing the Na+ accumulation of xylem. NHX sequesters Na+ into the vacuoles and thus reducing its ion toxicity for the cytoplasm and other organelles. It is reported that accumulation of Na+ in the vacuoles not only avoid cytoplasmic toxicity, but also is used as an osmolyte to alleviate osmotic stress [40]. Our results revealed that there were more upregulated ion transporter genes in the roots, and we concluded that this upregulation of ion transporter genes is one of the important factors that affects C. grandiflora response and tolerance to salt stress.

According to GO annotations, the largest number of differentially expressed genes were enriched in the nuclear, plasma membrane, cytoplasm, membrane components, and protein binding in the root library. The largest number of differentially expressed genes were enriched in the leaf library for the nuclear, plasma membrane, cytoplasm, membrane components, and in the chloroplasts. We found that the GO annotations with the highest degree of enrichment of DEGs in the roots and leaves were the same. According to the KEGG annotation, in the samples of C. grandiflora, the number of DEGs enriched in the ribosomes and spliceosomes or those genes involved in protein processing in the endoplasmic reticulum, phytohormone signal transduction, and phytopathogen interaction pathways was the largest. We also found the largest number of differentially expressed genes were enriched in the root library for phenylpropane biosynthesis, ER protein processing, starch and sucrose metabolism, plant hormone signaling, and galactose metabolism pathways. Also, the largest number of differentially expressed genes were enriched in the library of plant pathogen interactions, plant hormone signaling, protein processing in the endoplasmic reticulum, starch and sucrose metabolism, and phenylpropane biosynthesis pathways. Transcriptomic and metabolomic analysis have shown that DEGs and differential metabolites obtained in the phenylpropanoid biosynthesis pathway are significantly related under salt stress [41]. Previous studies have found that plant hormones are small chemicals that play a key role in plant growth and development [42]. Stress hormones such as salicylic acid (SA) and jasmonic acid (JA) mediate the balance between salt stress signals and control growth and stress responses. Therefore, we mainly identified the SA and JAs signal transduction pathways in the phenylpropane biosynthesis pathway and the plant hormone signal transduction pathway.

The metabolic pathway of phenylpropane in plants is a very complex metabolic network, which is the main synthesis pathway of important secondary metabolites such as phenols, flavonoids, anthocyanins, and lignins [43]. These secondary metabolites are widely involved in various physiological activities of plants, especially in the response process of plants to biotic and abiotic stresses [44]. In this study, 268 DEGs were annotated in the phenylpropanoid biosynthesis pathway in the C. grandiflora samples. Among them, there were 24 DEGs in the phenylpropane synthesis pathway of the leaves, all of which were upregulated, including PAL, CYP73A and 4CL. In the roots, there were 17 DEGs in the phenylpropane synthesis pathway, all of which were upregulated including PAL, CYP73A and 4CL. PAL is the key rate-limiting enzyme that plays an important role in the plant growth and development, connects plant primary and secondary metabolism, and catalyzes the first reaction of phenylpropane metabolism [45]. In addition, PAL is closely related to the content of secondary metabolites (such as lignin, phytoalexin, flavonoids), and it also plays an important role in the response of plants to biotic and abiotic stress [46]. 4-coumarate:coenzyme A ligase (4CL) is the last key enzyme for the phenylpropane biosynthesis pathway to shift to the downstream branch pathway. It contains cinnamic acid, 4-coumaric acid, caffeic acid, erucic acid, ferulic acid, and 5-hydroxyferulic acid, which are used as substrates to generate corresponding acyl-CoA esters. Chlorogenic acid is then generated under the action of hydroxycinnamoyl coenzyme quinic acid hydroxycinnamate acyltransferase (HQT) [47]. We found that the upregulated expression of genes was closely related to salt tolerance of C. grandiflora: upregulated expression of PAL in the roots and leaves could affect the content of secondary metabolites, and expression of 4CL affects chlorogenic acid. The synthesis of chlorogenic acid is closely related to antioxidants [48]. There were more PAL, CYP73A and 4CL genes involved in phenylpropane biosynthesis in the leaves of C. grandiflora. Therefore, we speculate that the phenylpropane biosynthesis pathway is an important tolerance feature for leaves to defend against salt stress.

Plants use complex signaling pathways to respond to stress. In addition to some other small molecules (such as Ca2+ and ROS), plant hormones can initiate a specific signal cascade after sensing biological and abiotic stress [49]. Fluctuations in the levels of several major hormones such as ABA, ET, SA, and JA, as an early response to stress, initiate metabolic processes that lead to changes in the plant growth patterns. The Nonexpressor of Pathogenesis-Related gene 1 (NPR1) is an activator of plant resistance. NPR1 not only plays a core regulatory role in plant system resistance acquisition and induction of systemic resistance, but also acts as an important regulatory factor for plant basic resistance and resistance determined by disease resistance genes [50]. Transcription factors TGA [51], TIFY [52], and MYC [53] also play an important role in plant resistance to abiotic stresses. This study revealed that a large number of genes related to salt stress were in the signal transduction pathway of plant hormones, and the number of DEGs in the leaves was relatively large. In the SA signal transduction pathway, NPR1, NPR2, NPR3, TGAL5 and TGA7 are upregulated, and TGA7 was upregulated in the roots and leaves; the rest were only upregulated in leaves. TIFY10B, TIFY9, TIFY10A, TIFY6A, TIFY6B, MYC2, MYC4 and AIB are upregulated in the JA signal transduction pathway. Studies have shown that signal recognition is a key step for JA to play a role in plants, and TIFY is a key factor that regulates the signal recognition of JA [54]. When plants activate the JAs signal pathway, MYC2, bHLH and other transcription factors are inhibited by the TIFY protein through ubiquitination [55]. The first step toward activation of this pathway begins when the content of exogenous or endogenous JA increases. With this increase in JA, the JA receptor COI1 binds to the TIFY protein to form a SCFCOI1 complex. The deubiquitinated TIFY protein is degraded by the 26S proteasome, and the MYC2 and bHLH transcription factors are released concurrently, which finally activates the JAs signal pathway. Since TIFY9 was upregulated in the roots and leaves in this study, by comparing gene expression patterns, we found that there were more upregulated genes in the leaves. Therefore, we speculated that TIFY9 in C. grandiflora could play a role in both the roots and the leaves. It is clear that both SA the JA signal transduction pathways are important mechanisms to defend against salt stress in the leaves of C. grandiflora.

Plant transcription factors are members of a vital gene family that are widely present and participate in the regulation of plant growth, development and resistance to stresses. Transcription factors can regulate the expression of stress-responsive genes by combining with specific action elements in downstream gene promoters, thereby directly or indirectly participating in many biological processes of plants, such as cell morphogenesis, metabolism, physiological balance, and signal transduction [56]. Studies have shown that transcription factor families such as bHLH, NAC, MYB, ERF, WRKY, and bZIP regulate several aspects of plant growth, development, secondary metabolism, and stress response [57,58,59,60]. In this study, the transcription factor families bHLH, NAC, MYB, ERF, WRKY and bZIP had the most annotated transcription factors, which suggests that these transcription factor families are strongly participate in salinity tolerance of C. grandiflora.

In summary, transcriptome sequencing showed that salt stress changed the transcription levels of many genes related to multiple regulatory networks, including osmotic regulation, ion transport, reactive oxygen scavenging, and plant hormone signal regulation. Studies demonstrated that there are more DEGs in the roots of the chrysanthemum cv. ‘Jinba’ than in the leaves, and the number of downregulated genes involved in the salt stress response exceeds the number of upregulated genes under salt stress [12]. In addition, the roots of chrysanthemums under salt stress are mainly dominated by the upregulation of genes encoding proteins involved in ion transport, while in the leaves the response is focused on osmotic regulation and Ca2+ transport [11]. Our research showed that there were more DEGs in the leaves of C. grandiflora than in its roots, and more upregulated than downregulated genes in the roots and leaves in response to salt stress. Salinity responses in root include upregulations of genes encoding ionic transporters, thereby changing the osmotic regulation ability of C. grandiflora. Contrary, the leaf response focused on the SA and JAs signal transduction pathways in phenylpropane biosynthesis and plant hormone signal transduction. We propose that this may be a result of the differences in the resistance of plant materials. Similarly, drought and salt stress on Chrysopogon zizanioides resulted in more transcriptome changes in leaf tissues than in root tissues [13]. The results of the previous work are similar to our findings concerns the number of genes and their expression patterns in the roots and leaves of C. grandiflora. Figure 10 shows a molecular mechanism diagram of C. grandiflora that summarizes C. grandiflora response and tolerance mechanism under saline conditions.

Fig. 10
figure 10

Molecular mechanism diagram of salt stress resistance of C. grandiflora: (a) roots, (b) leaves

Conclusions

The results of transcriptome sequencing showed that salt stress changed the transcription levels of many genes related to multiple regulatory networks, including osmotic regulation, ion transport, and reactive oxygen scavenging systems. The functional enrichment analysis of candidate genes showed that the tissue-specific pattern of the transcriptome under salt treatment: in C. grandiflora, more transcriptome changes and number of genes involved in the salt stress response was greater in the leaf tissues than the roots. Root response to salinity included upregulation of genes encoding involved ion transporters. However, the leaf response focused on phenylpropane biosynthesis and plant hormone signal transduction. This work has greatly enriched the existing sequence resources of C. grandiflora and provides a large number of salt-tolerant candidate genes for further functional analysis to improve plant salt tolerance.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article. Sequencing database for Chrysanthemum×grandiflora could download from NCBI under the accession number SRR17510868, SRR17510867, SRR17510866, SRR17510865, SRR17510874, SRR17510873, SRR17510876, SRR17510875, SRR17510872, SRR17510871, SRR17510870 and SRR17510869. The data will be shared on reasonable request of the corresponding author.

References

  1. Tattini M, Heimler D, Traversi ML, Pieroni A. Polyamine analysis in salt stressed plants of olive (Olea europaea L.). J Horticult Sci. 2015;68(4):613–7. https://doi.org/10.1080/00221589.1993.11516392.

    Article  Google Scholar 

  2. Awana M, Jain N, Samota MK, Rani K, Kumar A, Ray M, et al. Protein and gene integration analysis through proteome and transcriptome brings new insight into salt stress tolerance in pigeonpea (Cajanus cajan L.). Int J Biol Macromol. 2020;164:3589–602. https://doi.org/10.1016/j.ijbiomac.

    Article  CAS  PubMed  Google Scholar 

  3. Ignacio LC, Carolina M, Alejandro GC, Marcelo D. Allantoin accumulation mediated by allantoinase downregulation and transport by Ureide permease 5 confers salt stress tolerance to Arabidopsis plants. Plant Mol Biol. 2016;91:581–95. https://doi.org/10.1007/s11103-016-0490-7.

    Article  CAS  Google Scholar 

  4. Solmaz I, Todd Christopher D. Ureide metabolism under abiotic stress in Arabidopsis thaliana. Plant Physiol. 2016;199:87–95. https://doi.org/10.1016/j.jplph.2016.05.011.

    Article  CAS  Google Scholar 

  5. De Yun M, Sha Y, Yi XJ, Na MN, Zhi WB, Tong QF, et al. Peanut (Arachis hypogaea L.) S-Adenosylmethionine decarboxylase confers the transgenic tobacco elevated tolerance to salt stress. Plant Biol Stuttg. 2020;23:341–50. https://doi.org/10.1111/plb.13173.

    Article  CAS  Google Scholar 

  6. Oliveira DM, Mota TR, Salatta FV, Sinzker RC, Končitíková R, Kopečný D, et al. Cell wall remodeling under salt stress: insights into changes in polysaccharides, feruloylation, lignification, and phenolic metabolism in maize. Plant Cell Environ. 2020;43(9):2172–91. https://doi.org/10.1111/pce.13805.

    Article  CAS  PubMed  Google Scholar 

  7. Lovelli S, Perniola M. Low CO2 does not remove diffusional limitation to photosynthesis in salt stressed tomato during osmotic phase. Acta Physiol Plant. 2014;36(7):1953–6. https://doi.org/10.1007/s11738-014-1561-5.

    Article  CAS  Google Scholar 

  8. Serrão d SBR, Lemos BB, Klynger d SLA. Anatomical changes in stem and root of soybean plants submitted to salt stress. Plant Biol (Stuttg). 2020;23:57–65. https://doi.org/10.1111/plb.13176.

    Article  CAS  Google Scholar 

  9. Hussain S, Zhu C, Huang J, Huang J, Zhu L, Cao X, et al. Ethylene response of salt stressed rice seedlings following Ethephon and 1-methylcyclopropene seed priming [J]. Plant Growth Regul. 2020;92:219–31. https://doi.org/10.1007/s10725-020-00632-1.

    Article  CAS  Google Scholar 

  10. Rana M, Mark T. Mechanisms of salinity tolerance. Annu Rev Plant Biol. 2008;59:651–81. https://doi.org/10.1146/annurev.arplant.59.032607.092911.

    Article  CAS  Google Scholar 

  11. Sadam H, Saddam H, Basharat A, Xiaolong R, Xiaoli C, Qianqian L, et al. Recent progress in understanding salinity tolerance in plants: story of Na+/K+ balance and beyond. Plant Physiol Biochem. 2021;160:239–56. https://doi.org/10.1016/j.plaphy.2021.01.029.

    Article  CAS  Google Scholar 

  12. Cheng P, Gao J, Feng Y, Zhang Z, Liu Y, Fang W, et al. The chrysanthemum leaf and root transcript profiling in response to salinity stress. Gene. 2018;674:161–9. https://doi.org/10.1016/j.gene.2018.06.075.

    Article  CAS  PubMed  Google Scholar 

  13. George S, Manoharan D, Li J, Britton M, Parida A. Drought and salt stress in Chrysopogon zizanioides leads to common and specific transcriptomic responses and may affect essential oil composition and benzylisoquinoline alkaloids metabolism. Curr Plant Biol. 2017;11-12:12–22. https://doi.org/10.1016/j.cpb.2017.12.001.

    Article  Google Scholar 

  14. Li ZQ, Xing W, Luo P, Zhang FJ, Jin XL, Zhang MH. Comparative transcriptome analysis of Rosa chinensis ‘Slater’s crimson China’ provides insights into the crucial factors and signaling pathways in heat stress response. Plant Physiol Biochem. 2019;142(C):312–31. https://doi.org/10.1016/j.plaphy.2019.07.002.

    Article  CAS  PubMed  Google Scholar 

  15. Daisuke S, Shigeo T, Yoshihiro M. Salt tolerance during germination and seedling growth of wild wheat Aegilops tauschii and its impact on the species range expansion. Sci Rep. 2016;6(1):38554–66. https://doi.org/10.1038/srep38554.

    Article  CAS  Google Scholar 

  16. Sharif SMU, Souvik S, Habib NF, Ghosh DS, Seraj Zeba I. HKT1;5 transporter gene expression and association of amino acid substitutions with salt tolerance across rice genotypes. Front Plant Sci. 2019;10:1420–38. https://doi.org/10.3389/fpls.2019.01420.

    Article  Google Scholar 

  17. Juan X, Xiaoli Tian A, Eneji E, Li Z. Functional characterization of GhAKT1 , a novel Shaker-like K+ channel gene involved in K+ uptake from cotton (Gossypium hirsutum). Gene. 2014;545(1):61–71. https://doi.org/10.1016/j.gene.2014.05.006.

    Article  CAS  Google Scholar 

  18. Dong J, Cuiyu L, Wang Y, Yujie Z, Dapeng G, Zhaohe Y. Genome-wide identification of the NHX gene family in Punica granatum L. and their expressional patterns under salt stress. Agronomy. 2021;11(2):264–78. https://doi.org/10.3390/agronomy11020264.

    Article  CAS  Google Scholar 

  19. Liu Z, Saiyinduleng QC, Cheng C, Zheng Z, Song Y. Identification of yellowhorn (Xanthoceras sorbifolium) WRKY transcription factor family and analysis of abiotic stress response model. J For Res. 2021;32(03):987–1004. https://doi.org/10.1007/s11676-020-01134-6.

    Article  CAS  Google Scholar 

  20. Qi W, Cun G, Zhiyuan L, Jinhao S, Zhichao D, Lichao W, et al. Potato NAC transcription factor StNAC053 enhances salt and drought tolerance in transgenic Arabidopsis. Int J Mol Sci. 2021;22(5):2568–86. https://doi.org/10.3390/ijms22052568.

    Article  CAS  Google Scholar 

  21. Khanale V, Bhattacharya A, Satpute R, Char B. Brief bioinformatics identification of cotton bZIP transcription factors family from Gossypium hirsutum, Gossypium arboreum and Gossypium raimondii. Plant Biotechnol Rep. 2021;15(4):493–511. https://doi.org/10.1007/s11816-021-00688-z.

    Article  Google Scholar 

  22. Zhang K, Luyuan Jiang X, Wang HH, Chen D, Qiu D, Yang Y. Transcriptome-wide analysis of AP2/ERF transcription factors involved in regulating taxol biosynthesis in Taxus × media. Ind Crop Prod. 2021;171(1):113972. https://doi.org/10.1016/j.indcrop.2021.113972.

    Article  CAS  Google Scholar 

  23. Liu Y, He M, Dong F, Cai Y, Gao W, Zhou Y, et al. The Chrysanthemum lavandulifolium ClNAC9 gene positively regulates saline, alkaline, and drought stress in transgenic Chrysanthemum grandiflora. J Am Soc Hortic Sci. 2019;144(4):280–8. https://doi.org/10.21273/JASHS04697-19.

    Article  CAS  Google Scholar 

  24. Liu X, Xia B, Purente N, Chen B, Zhou Y, He M. Transgenic Chrysanthemum indicum overexpressing cin-miR396a exhibits altered plant development and reduced salt and drought tolerance. Plant Physiol Biochem. 2021;168:17–26. https://doi.org/10.1016/j.plaphy.2021.09.035.

    Article  CAS  PubMed  Google Scholar 

  25. Takahashi R, Nishio T, Ichizen N, Takano T. Salt-tolerant reed plants contain lower Na+ and higher K+ than salt-sensitive reed plants. Acta Physiol Plant. 2007;29(5):431–8. https://doi.org/10.1007/s11738-007-0052-3.

    Article  CAS  Google Scholar 

  26. Eden E, Navon R, Steinfeld I, Lipson D, Yakhini Z. Gorilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics. 2009;10:48. https://doi.org/10.1186/1471-2105-10-48.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Mao XZ, Cai T, Olyarchuk JG, Wei LP. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005;21(19):3787–93. https://doi.org/10.1093/bioinformatics/bti430.

    Article  CAS  PubMed  Google Scholar 

  28. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods. 2001;25(4):402–8. https://doi.org/10.1006/meth.2001.1262.

    Article  CAS  PubMed  Google Scholar 

  29. Yao Y, Zhang X, Wang N, Cui Y, Zhang L, Fan S. Transcriptome analysis of salt stress response in halophyte Atriplex centralasiatica leaves. Acta Physiol Plant. 2020;42:3. https://doi.org/10.1007/s11738-019-2989-4.

    Article  CAS  Google Scholar 

  30. Shanhu H, Yiran W, Yunxiu Y, Yuhang L, Jingyao W, Chen S. A review on plant responses to salt stress and their mechanisms of salt resistance. Horticulturae. 2021;7(6):132. https://doi.org/10.3390/horticulturae7060132.

    Article  Google Scholar 

  31. Gupta A, Shaw BP. Augmenting salt tolerance in rice by regulating uptake and tissue specific accumulation of Na+ through Ca2+ induced alteration of biochemical events. Plant Biol (Stuttgart, Germany). 2021;23:122–30. https://doi.org/10.1111/plb.13258.

    Article  CAS  Google Scholar 

  32. Tomoaki H, Ichirou K, Maki K. Salinity tolerance mechanisms in glycophytes: an overview with the central focus on rice plants. Rice. 2012;5:11. https://doi.org/10.1186/1939-8433-5-11.

    Article  Google Scholar 

  33. Roy SJ, Negrão S, Tester M. Salt resistant crop plants. Curr Opin Biotechnol. 2014;26:115–24. https://doi.org/10.1016/j.copbio.2013.12.004.

    Article  CAS  PubMed  Google Scholar 

  34. Guo R, Xuan SL, Cangrong Y, Xiuli Z, Fengxue G, Qi L, et al. Ionomic and metabolic responses to neutral salt or alkaline salt stresses in maize (Zea mays L.) seedlings. BMC Plant Biol. 2017;17:41. https://doi.org/10.1186/s12870-017-0994-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. TimothyJ F, TimothyD C. Salinity tolerance in halophytes. New Phytol. 2008;179(4):945–63. https://doi.org/10.1111/j.1469-8137.2008.02531.x.

    Article  CAS  Google Scholar 

  36. Shu P, Li Y, Li Z, Sheng J, Shen L. SlMAPK3 enhances tolerance to salt stress in tomato plants by scavenging ROS accumulation and up-regulating the expression of ethylene signaling related genes. Environ Exp Bot. 2021;193:104698. https://doi.org/10.1016/j.envexpbot.2021.104698.

    Article  CAS  Google Scholar 

  37. Yinan Y, Yufang S, Qian F, Xuan Z, Yongfeng G, Yongbin O, et al. Acclimation to nitrogen salt stress in Populus bolleana mediated by potassium/sodium balance. Indust Crops Prod. 2021;170:113789. https://doi.org/10.1016/j.indcrop.2021.113789.

    Article  CAS  Google Scholar 

  38. Ming Z, Xiaoyan L, Limin W, Yibo C, Weibin S, Junpeng S, et al. A HAK family Na+ transporter confers natural variation of salt tolerance in maize. Nat Plants. 2019;5(12):1297–308. https://doi.org/10.1038/s41477-019-0565-y.

    Article  CAS  Google Scholar 

  39. Tada Y. The HKT Transporter Gene from Arabidopsis, AtHKT1;1, is dominantly expressed in shoot vascular tissue and root tips and is mild salt stress-responsive. Plants. 2019;8(7):204. https://doi.org/10.3390/plants8070204.

    Article  CAS  PubMed Central  Google Scholar 

  40. Guo-Qiang W, Wang J-L, Li S-J. Genome-wide identification of Na+/H+ antiporter (NHX) genes in sugar beet ( Beta vulgaris L.) and their regulated expression under salt stress. Genes. 2019;10(5):401. https://doi.org/10.3390/genes10050401.

    Article  CAS  Google Scholar 

  41. B-li C, Li N, Xu K. Crosstalk of phenylpropanoid biosynthesis with hormone signaling in Chinese cabbage is key to counteracting salt stress. Environ Exp Bot. 2020;179:104209. https://doi.org/10.1016/j.envexpbot.2020.104209.

    Article  CAS  Google Scholar 

  42. Zhu L, Zhang L, Zhao C. Phytohormone involved in salt tolerance regulation of Elaeagnus angustifolia L. seedlings. J For Res. 2019;24(4):235–42. https://doi.org/10.1080/13416979.2019.1637995.

    Article  CAS  Google Scholar 

  43. Liang Y, Han C, Yun L, Yang Y, Cao Y. Transcriptomic and metabolomic analysis of the mechanism of temperature-regulated anthocyanin biosynthesis in purple asparagus spears. Sci Hortic. 2022;295:110858. https://doi.org/10.1016/j.scienta.2021.110858.

    Article  CAS  Google Scholar 

  44. Guan Y, Wenzhong H, Yongping X, Sarengaowa YJ, XiaozheYang KF. Proteomic analysis validates previous findings on wounding-responsive plant hormone signaling and primary metabolism contributing to the biosynthesis of secondary metabolites based on metabolomic analysis in harvested broccoli (Brassica oleracea L. var. italica). Food Res Int. 2021;145:110388. https://doi.org/10.1016/j.foodres.2021.110388.

    Article  CAS  PubMed  Google Scholar 

  45. He Y, Zhong X, Jiang X, Cong H, Sun H, Qiao F. Characterisation, expression and functional analysis of PAL gene family in Cephalotaxus hainanensis. Plant Physiol Biochem. 2020;156:461–70. https://doi.org/10.1016/j.plaphy.2020.09.030.

    Article  CAS  PubMed  Google Scholar 

  46. Guohui L, Han W, Xi C, Xueqiang S, Yu Z, Taoshan J, et al. Comparative genomic analysis of the PAL genes in five Rosaceae species and functional identification of Chinese white pear. Peer J. 2019;7:e8064. https://doi.org/10.7717/peerj.8064.

    Article  Google Scholar 

  47. Awasthi P, Mahajan V, Jamwal VL, Chouhan R, Kapoor N, Bedi YS, et al. Characterization of the gene encoding 4-coumarate: CoA ligase in Coleus forskohlii. J Plant Biochem Biotechnol. 2019;28(2):203–10. https://doi.org/10.1007/s13562-018-0468-4.

    Article  CAS  Google Scholar 

  48. Tang YH, Liu F, Mao KQ, Xing HC, Chen JR, Guo QQ. Cloning and characterization of the key 4-coumarate CoA ligase genes in Boehmeria nivea. S Afr J Bot. 2018;116:123–30. https://doi.org/10.1016/j.sajb.2018.02.398.

    Article  CAS  Google Scholar 

  49. Yu Z, Duan X, Luo L, Dai S, Ding Z, Xia G. How plant hormones mediate salt stress responses. Trends Plant Sci. 2020;25(11):1117–30. https://doi.org/10.1016/j.tplants.2020.06.008.

    Article  CAS  PubMed  Google Scholar 

  50. Peiguo Y, Kiwamu T, Poovaiah BW. Calmodulin-binding transcription activator AtSR1/CAMTA3 fine-tunes plant immune response by transcriptional regulation of the salicylate receptor NPR1. Plant Cell Environ. 2021;44(9):3140–54. https://doi.org/10.1111/pce.14123.

    Article  CAS  Google Scholar 

  51. Han J, H-tao L, S-chang W, C-run W, Miao G. A class I TGA transcription factor from Tripterygium wilfordii Hook.F. modulates the biosynthesis of secondary metabolites in both native and heterologous hosts. Plant Sci. 2019;290:110293. https://doi.org/10.1016/j.plantsci.2019.110293.

    Article  CAS  PubMed  Google Scholar 

  52. Bai Y, Meng Y, Huang D, Qi Y, Chen M. Origin and evolutionary analysis of the plant-specific TIFY transcription factor family. Genomics. 2011;98(2):128–36. https://doi.org/10.1016/j.ygeno.2011.05.002.

    Article  CAS  PubMed  Google Scholar 

  53. Yanfang Y, Kaikai Z, Liying Y, Xing L, Ying W, Hongwei L, et al. Identification and characterization of MYC transcription factors in Taxus sp. Gene. 2018;675:1–8. https://doi.org/10.1016/j.gene.2018.06.065.

    Article  CAS  PubMed  Google Scholar 

  54. Wanga Y, Pan F, Chen D, Chu W, Liu H, Xiang Y. Genome-wide identification and analysis of the Populus trichocarpa TIFY gene family. Plant Physiol Biochem. 2017;115:360–71. https://doi.org/10.1016/j.plaphy.2017.04.015.

    Article  CAS  Google Scholar 

  55. Zhiwei C, Li S, Tiancong Q, Bosen Z, Wen P, Yule L, et al. The bHLH transcription factor MYC3 interacts with the Jasmonate ZIM-domain proteins to mediate Jasmonate response in Arabidopsis. Mol Plant. 2011;4(2):279–88. https://doi.org/10.1093/mp/ssq073.

    Article  CAS  Google Scholar 

  56. Prasad KVSK, Abdel-Hameed AAE, Xing D, Reddy ASN. Global gene expression analysis using RNA-seq uncovered a new role for SR1/CAMTA3 transcription factor in salt stress. Sci Rep. 2016;6:27021. https://doi.org/10.1038/srep27021.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Zheng K, Wang Y, Wang S. The non-DNA binding bHLH transcription factor Paclobutrazol resistances are involved in the regulation of ABA and salt responses in Arabidopsis. Plant Physiol Biochem. 2019;139:239–45. https://doi.org/10.1016/j.plaphy.2019.03.026.

    Article  CAS  PubMed  Google Scholar 

  58. Bo W, Zhaohui Z, Huanhuan Z, Xia W, Binglin L, Lijia Y, et al. Targeted Mutagenesis of NAC Transcription Factor Gene, OsNAC041 , Leading to Salt Sensitivity in Rice. Rice Sci. 2019;26(2):98–108. https://doi.org/10.1016/j.rsci.2018.12.005.

    Article  Google Scholar 

  59. Shuaishuai W, Mengyun S, Yang Z, Xingbin X, Peipei S, Congbing F, et al. FvMYB24, a strawberry R2R3-MYB transcription factor, improved salt stress tolerance in transgenic Arabidopsis. Biochem Biophys Res Commun. 2021;569:93–9. https://doi.org/10.1016/j.bbrc.2021.06.085.

    Article  CAS  Google Scholar 

  60. Long L, Yang W-W, Liao P, Guo Y-W, Kumar A, Gao W. Transcriptome analysis reveals differentially expressed ERF transcription factors associated with salt response in cotton. Plant Sci. 2019;281:72–81. https://doi.org/10.1016/j.plantsci.2019.01.012.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We are grateful to College of landscape architecture, Northeast Forestry University for providing materials. We also thank LC-Bio. Co., Ltd. for their support in RNA sequencing.

Funding

This study was fnancially supported by National Natural Science Foundation of China (31870687), National Key Research and Development Program of China (2019YFD1001500) and National Key Research and Development Program of China (2018YFD1000406). We thank Prof. Yunwei Zhou and Miao He for their help and support, we would like to sincerely thank the editors and reviewers for their patient work.

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H.L. designed the research and wrote the manuscript. Y.Z. and M.H. provided guidance on the experiment. Y.L., N. X, Y.S., Q.L. and L.Y. reviewed and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yunwei Zhou or Miao He.

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The author sincerely thanks Professor Yunwei Zhou for her funding from the National Natural Science Foundation of China and Professor Miao He for her national key research and development projects. All methods were carried out in accordance with the institutional guidelines and regulations.

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Liu, H., Liu, Y., Xu, N. et al. Chrysanthemum × grandiflora leaf and root transcript profiling in response to salinity stress. BMC Plant Biol 22, 240 (2022). https://doi.org/10.1186/s12870-022-03612-x

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  • DOI: https://doi.org/10.1186/s12870-022-03612-x

Keywords

  • Salt stress
  • Osmotic adjustment
  • Transcriptome
  • Chrysanthemum
  • DEGs
  • Transcription factors