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Article

Physiological and Transcriptional Responses of Apocynum venetum to Salt Stress at the Seed Germination Stage

by
Xin Li
1,
Jinjuan Li
2,
Hongyan Su
1,
Ping Sun
3,
Zhen Zhang
3,
Mengfei Li
1,3,* and
Hua Xing
3,*
1
State Key Laboratory of Aridland Crop Science, College of Agronomy, Gansu Agricultural University, Lanzhou 730070, China
2
Institute of Livestock Grass and Green Agriculture, Gansu Academy of Agricultural Sciences, Lanzhou 730070, China
3
College of Life Science and Technology, Gansu Agricultural University, Lanzhou 730070, China
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2023, 24(4), 3623; https://doi.org/10.3390/ijms24043623
Submission received: 21 January 2023 / Revised: 9 February 2023 / Accepted: 9 February 2023 / Published: 11 February 2023
(This article belongs to the Special Issue Recent Advances in Molecular Breeding for Drought and Salt Stress Tolerance in Crops)
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Abstract

:
Apocynum venetum is a semi-shrubby perennial herb that not only prevents saline–alkaline land degradation but also produces leaves for medicinal uses. Although physiological changes during the seed germination of A. venetum in response to salt stress have been studied, the adaptive mechanism to salt conditions is still limited. Here, the physiological and transcriptional changes during seed germination under different NaCl treatments (0–300 mmol/L) were examined. The results showed that the seed germination rate was promoted at low NaCl concentrations (0–50 mmol/L) and inhibited with increased concentrations (100–300 mmol/L); the activity of antioxidant enzymes exhibited a significant increase from 0 (CK) to 150 mmol/L NaCl and a significant decrease from 150 to 300 mmol/L; and the content of osmolytes exhibited a significant increase with increased concentrations, while the protein content peaked at 100 mmol/L NaCl and then significantly decreased. A total of 1967 differentially expressed genes (DEGs) were generated during seed germination at 300 mmol/L NaCl versus (vs.) CK, with 1487 characterized genes (1293 up-regulated, UR; 194 down-regulated, DR) classified into 11 categories, including salt stress (29), stress response (146), primary metabolism (287), cell morphogenesis (156), transcription factor (TFs, 62), bio-signaling (173), transport (144), photosynthesis and energy (125), secondary metabolism (58), polynucleotide metabolism (21), and translation (286). The relative expression levels (RELs) of selected genes directly involved in salt stress and seed germination were observed to be consistent with the changes in antioxidant enzyme activities and osmolyte contents. These findings will provide useful references to improve seed germination and reveal the adaptive mechanism of A. venetum to saline–alkaline soils.

1. Introduction

Apocynum venetum L. (Apocynaceae) is a semi-shrubby perennial herb that is widely distributed in saline–alkaline soils and plays a critical role in preventing the land from degradation [1,2]. The leaves are used as a traditional Chinese medicine (TCM) for the treatment of cardiac disease, hypertension, and nephritis, which largely rely on the bioactive compounds such as flavonoids, organic acids, and polysaccharides [3,4,5].
In natural habitats, the plants have to face abiotic stresses, such as drought, extreme temperatures, and high salinity [6]. In saline–alkaline soils, the plants grow flourishingly due to their adaptive ability in a high salinity environment [7,8]. Seed germination is the initial stage throughout the life cycle and plays a determining role in the distribution of plant populations, especially under adverse abiotic conditions [9,10]. Currently, germination characteristics and physiological changes have been conducted during the seed germination of A. venetum in response to abiotic stresses. Specifically, salt and drought stress significantly inhibited seed germination [11,12,13,14]; fluctuated temperatures (10/25 and 15/30 °C, 12 h/12 h) were more in favor of seed germination than other temperatures [8]; a prolonged storage period significantly decreased seed germination [8,15]; and there was no significant effect of light on seed germination [8]. For the physiological changes in response to salt stress, the rate of electrolyte leakage, the content of osmolytes (e.g., soluble sugar, malondialdehyde (MDA), and proline (Pro)), and the activity of antioxidant enzymes (e.g., superoxide dismutase (SOD), ascorbateperoxidase (APX), catalase (CAT), and peroxidase (POD)) gradually increased with increased NaCl concentrations [13,16,17,18]. Meanwhile, salt stress induced the UR of genes involved in cation transport and antioxidants while inducing the DR of genes involved in cell wall structure [19].
Previous studies have found that there are distinct resistances for seed germination among different psammophytes under salt stress. For example, the seed germination of Halimodendron halodendron and Alhagi sparsifolia was significantly affected by the NaCl treatments [20]; the seed germination of Halogeton glomeratus and Cannabis sativa was inhibited by increased salt concentrations [21,22]. Extensive studies have demonstrated that plants respond and adapt to salt stress through various physiological, biochemical, and transcriptional processes, thereby acquiring stress tolerance [23,24]. For example, the content of soluble protein and Pro increased at an early stage and then decreased with the prolonging of salt stress, and the activity of SOD, POD, and CAT as well as the content of MDA in Broyssonetia papyrifera and Pogostemon cablin gradually increased with increased salt concentrations [25,26]. Hundreds of genes involved in abiotic tolerance as well as growth and development have also been identified in response to salt stress [27]. For example, the stress-responsive genes (e.g., DREB/CBFs), abiotic stress-related TFs (e.g., ZAT, WRKY, and NAC), and transporters (e.g., MATE and LeOPT1-like) were up-regulated in Arabidopsis under salt stress [28,29,30]. The above results indicate that salt stress triggers a wide range of responses, including physiological characteristics (e.g., seed germination and growth), cellular metabolism (e.g., osmolytes accumulation and enzyme activity), and molecular regulation (e.g., gene and protein expression).
To date, a low-salt environment improving the seed germination of A. venetum has been found, and the physiological changes have also been primarily conducted [16,17,18], while the adaptive mechanism to salt stress is still limited. In order to reveal the adaptive mechanism of A. venetum to salt stress in this study, we examined the changes in the rate of seed germination, the activity of antioxidant enzymes, the content of osmolytes, and the expression levels of genes in A. venetum at the seed germination stage under different NaCl treatments.

2. Results

2.1. Seed Germination Rate at Different NaCl Treatments

As shown in Figure 1, the seed germination rate was distinctly affected by different NaCl treatments (0–300 mmol/L, p < 0.05), with an increase at the low NaCl concentration (50 mmol/L), while there was a gradual decrease with increased NaCl concentrations (from 100 to 300 mmol/L) compared with CK.

2.2. Antioxidant Enzyme Activities at Different NaCl Treatments

As shown in Figure 2, significant changes in the activities of the four antioxidant enzymes (i.e., SOD, POD, CAT, and APX) in seeds were observed under different NaCl treatments, with a significant increase with NaCl concentrations from 0 (CK) to 150 mmol/L and a significant decrease with NaCl concentrations from 150 to 300 mmol/L.

2.3. Osmolyte Contents under Different NaCl Treatments

As shown in Figure 3, significant changes in osmolyte contents (i.e., soluble sugar, protein, MDA, and Pro) in seeds were observed under different NaCl treatments, with a significant increase for the contents of soluble sugar, MDA, and Pro with increased NaCl concentrations, while a significant decrease in the protein content was observed at NaCl concentrations from 100 to 300 mmol/L.

2.4. Transcriptomic Analysis

2.4.1. Global Gene Analysis

In order to find far more genes involved in salt tolerance, transcriptomic analysis was conducted on a higher salt concentration (300 mmol/L) instead of a lower salt concentration (50 mmol/L) vs. CK. After data filtering, 51.43 and 65.36 million high-quality reads were generated, and 42.12 and 53.26 million unique reads with 0.81 and 0.80 million multiple reads were mapped for CK and NaCl (300 mmol/L), respectively (Table 1; Figure S1).
A total of 52,305 unigenes were annotated on the Kyoto Encyclopedia of Genes and Genomes (KEGG, 34,198), Eukaryotic Orthologous Groups of proteins (KOG, 22,630), NCBI non-redundant protein (Nr, 36,077), and SwissProt (27,467) databases (Figure S2). Using the KEGG database, 1967 DEGs were enriched into 139 metabolism pathways such as global and overview maps, carbohydrate metabolism, and amino acid metabolism (Figure S3). Using the KOG database, 43.27% unigenes encoded the identified proteins that could be classified into 25 functional categories (Figure S4). Using the NR database, the top 10 species included: Coffea arabica, Carica papaya, Coffea eugenioides, Pistacia vera, Actinidia chinensis, Vitis vinifera, Citrus clementine, Theobroma cacao, Olea europaea, and Citrus sinensis (Figure S5). Using the SwissProt database, 52.51% unigenes were annotated to have biological functions. Using the Gene Ontology (GO) database, the DEGs were classified into three ontologies, including biological process (BP), cellular component (CC), and molecular function (MF) (Figure S6).

2.4.2. Identification of DEGs

Among the 1967 DEGs, 1626 genes were UR and 341 genes were DR at 300 mmol/L NaCl vs. CK (Figure 4A,B), based on the principal component analysis (Figure S7) and Pearson correlation analysis (Figure S8). The cluster heat map of the 1967 DEGs is shown in Figure 4C. The distinct difference in the expression levels of genes between NaCl and CK treatments indicates that the data can be used for further analysis of gene biological functions.

2.4.3. Distribution and Classification of DEGs

Of these 1967 DEGs, 1729 genes were identified from the KEGG, KOG, SwissProt, or GO databases (Figure 5A). Among the 1729 genes, 1487 genes with characterized biological functions were distributed into 1293 UR and 194 DR (Figure 5B). Based on their biological functions, the 1487 genes were classified into 11 categories, including salt stress (29), stress response (146), primary metabolism (287), cell morphogenesis (156), transcription factor (TFs, 62), bio-signaling (173), transport (144), photosynthesis and energy (125), secondary metabolism (58), polynucleotide metabolism (21), and translation (286) (Figure 5C).

2.5. Specific Classification of DEGs and Validation of Expression Levels

2.5.1. DEGs Directly Associated with Salt Stress

Based on the biological functions of proteins encoded by the DEGs, 29 genes (25 UR, 4 DR) were found to be directly associated with salt stress (e.g., ALDH7B4, ALDH10A8, and ANN2) (Table 2). The expression levels of 10 selected genes were validated by qRT-PCR, with 3.07- (At2g40140) to 18.54-fold (IQM4) UR for eight genes and 0.47- (PCC13) and 0.50-fold (WSD1) DR for two genes at the 300 mmol/L NaCl vs. CK (Figure 6). Meanwhile, the RELs were consistent with their Reads Per kb per Million (RPKM) values (Table 2).

2.5.2. DEGs Directly Associated with Antioxidant Enzymes

In this study, 23 genes (21 UR, 2 DR) directly associated with antioxidant enzymes, including SOD (SODCP, FSD2, and SODA), POD (e.g., At5g06290, PNC1, and APX3), and CAT (CATA, CAT1, and PNC1) (Table 3), were screened from the 146 DEGs involved in stress response, and another 123 DEGs were directly associated with stress responses such as temperature, pathogens, and oxidative stresses (Table S1). The expression levels of 12 selected genes were validated by qRT-PCR, with 4.81- (CAT1) to 18.34-fold (SODA) UR for 11 genes and 0.71-fold (poxN1) DR at 300 mmol/L NaCl vs. CK (Figure 7). Meanwhile, the RELs were consistent with their RPKM values (Table 3).

2.5.3. DEGs Directly Associated with Soluble Sugar and Protein Metabolism

In this study, 79 genes (72 UR, 7 DR) directly associated with osmolytes, including soluble sugar (41 genes) and protein (38 genes), were screened from the 287 DEGs involved in primary metabolism; specifically, the 41 genes associated with soluble sugar metabolism included glucose (e.g., G6pc2, G6PDC, and GAPB), sucrose (INVE, SUS2, and SUS3), fructose (e.g., FKFBP, RHVI2, and FRK2), galactose (GOLS1 and GOLS2), trehalose (TPS6 and TPS7), fucose (OFUT19 and OFUT39), and starch (SBEI, DPE2, and AMY3), and the 38 genes associated with protein metabolism included PSMD2, RPN1A, RPN10, etc. (Table 4). The other 208 genes were associated with fatty acids, lipid metabolism, amino acids, etc. (Table S2). The expression levels of the 23 selected genes were validated by qRT-PCR, with 1.97- (ALEU) to 12.13-fold (GOLS1) UR for 22 genes and 0.57-fold (Cys) DR at 300 mmol/L NaCl vs. CK (Figure 8). Meanwhile, the RELs were consistent with their RPKM values (Table 4).

2.5.4. DEGs Directly Associated with Cell Morphogenesis for Seed Germination

In this study, six genes (5 UR, 1 DR) directly associated with seed germination (i.e., F16, FIP1, At5g13200, At5g23350, KAI2, and ROH1) (Table 5) were screened from the 156 DEGs involved in cell morphogenesis. The other 150 genes were associated with flower development, cell wall organization, programmed cell death, etc. (Table S3). The expression levels of the six genes were validated by qRT-PCR, with 1.42- (At5g23350) to 14.48-fold (F16) UR at 300 mmol/L NaCl vs. CK (Figure 9). Meanwhile, the RELs were almost consistent with their RPKM values, except for the At5g23350 gene (Table 5).

2.5.5. TFs Directly Associated with Stress Response and Seed Germination

In this study, 16 TFs (15 UR, 1 DR) directly associated with stress response and seed germination, including MYB (MYB73 and MYB1R1), WRKY (e.g., WRKY4, WRKY23, and WRKY24), NAC (e.g., NAC083, NAC091, and NAC100), BZIP44, TCP14, and UNE10 (Table 6), were screened from the 62 TFs; the other 46 TFs were associated with biotic stress, the regulation of transcription by RNA polymerase II, flower development, etc. (Table S4). The expression levels of eight selected genes were validated by qRT-PCR, with 4.33- (JA2L) to 12.13-fold (MYB73) UR at 300 mmol/L NaCl vs. CK (Figure 10). Meanwhile, the RELs were consistent with their RPKM values (Table 6).

2.5.6. DEGs Directly Associated with Hormone Response

In this study, 36 genes (30 UR, 6 DR) directly associated with hormone response, including GA (GASA2), IAA (e.g., ABP19A, AUX22D, and AUX12KD), CTK (CISZOG2, AHK3, and ARR4), JA (JOX2 and TIFY6B), ABA (e.g., PYL3, PYL4, and GRDP1), and ETH (e.g., RAV1, ETR2, and ERF4) response (Table 7), were screened from the 173 DEGs involved in bio-signaling. The other 137 genes were associated with other bio-signals such as protein kinases, protein phosphatase, calcium sensors, etc. (Table S5). The expression levels of the 12 selected genes were validated by qRT-PCR, with 3.92- (JOX2) to 13.36-fold (PP2CA) UR for eight genes and 0.39- (ETR2) to 0.98-fold (ERF013) DR for four genes at 300 mmol/L NaCl vs. CK (Figure 11). Meanwhile, the RELs were almost consistent with their RPKM values (Table 7).

2.5.7. DEGs Directly Associated with Ion Transport

In this study, 34 genes (27 UR, 7 DR) directly associated with ion transport (e.g., AHA10, CSC1, and CLC-B) (Table 8) were screened from the 144 DEGs involved in transport, and the other 110 genes were associated with other kinds of transport such as sugar transport, protein transport, amino acid transport, etc. (Table S6). The expression levels of the 10 selected genes were validated by qRT-PCR, with 4.07- (CAX1) to 12.41-fold (KEA2) UR for nine genes and 0.78-fold (ZIP1) DR at 300 mmol/L NaCl vs. CK (Figure 12). Meanwhile, the RELs were consistent with their RPKM values (Table 8).

2.5.8. DEGs Associated with Other Biological Functions

There are 490 DEGs involved in other biological functions, including photosynthesis and energy (125 genes, Table S7), secondary metabolism (58 genes, Table S8), polynucleotide metabolism (21 genes, Table S9), and translation (286 genes, Table S10). These genes may also participate in the seed germination of A. venetum in response to salt stress.

3. Discussion

Under both natural and agricultural conditions, plants are frequently exposed to unfavorable environments such as salt stress, extreme temperatures, and drought stress, which restrict plant distribution and reproduction, while plant adaptations that are genetically determined confer stress resistance [31]. Salt stress is a major abiotic stress that hinders seed germination, growth and development, and flowering and fruiting by driving various physiological and biochemical changes such as nutrition uptake, photosynthesis, and cellular metabolism [32,33,34,35,36,37]. In this study, we found that salt stress significantly affected the seed germination of A. venetum by changing the activity of antioxidant enzymes (i.e., SOD, POD, CAT, and APX), the content of osmolytes (i.e., soluble sugar, protein, MDA, and Pro), and the expression levels of genes associated with salt-stress response and seed germination.
Extensive experiments have demonstrated that stress resistance in response to salt stress is involved in the changes in physiological parameters (e.g., seed germination rate, plant growth, and flower development), antioxidant enzyme activities (e.g., SOD, POD, and CAT), and osmolyte contents (e.g., soluble protein, MDA, and Pro) [23,38]. For example, the seed germination of A. venetum decreases sharply under salt stress [11,12,13,14]. Salt stress causes oxidative stress that is responsible for the generation of reactive oxygen species (ROS), which are highly reactive and cause damage to biomolecules (e.g., lipids, proteins, and nucleic acids). To minimize the effect of oxidative stress, the ROS generation and increased activity of many antioxidant enzymes (e.g., SOD, CAT, and APX) during salt stress can protect plants from damage [23,39,40,41,42,43,44]. Under salt stress, ion imbalance and water deficiency induce osmotic stress, which triggers osmotic signaling pathways that regulate related genes’ expression, the enzyme activity of osmolyte biosynthesis, and the contents of osmolytes (e.g., soluble sugar, MDA, and Pro) [17,24,45].
In this study, we found that a low NaCl concentration (50 mmol/L) could promote the seed germination of A. venetum by adjusting the antioxidant enzyme activities and osmolyte contents. Actually, salt response is not only involved in the changes in phenotypes, antioxidant enzymes, and osmolytes but also in transcriptional alternations [46,47]. Here, 1487 DEGs (1293 UR and 194 DR) were observed during the seed germination of A. venetum at 300 mmol/L NaCl vs. CK, with 11 categories classified, including response to salt, stress response, primary metabolism, cell morphogenesis, TFs, bio-signaling, transport, photosynthesis and energy, secondary metabolism, polynucleotide metabolism, and translation.
Specifically, a total of 29 genes were directly associated with salt stress. For example, ALDH7B4 is activated by high salinity, dehydration, and ABA in a tissue-specific manner [48]; annexin (ANNs) in Arabidopsis is regulated by exposure to salt, drought, and extreme temperature conditions [49]; and RD22 is induced by salt stress and water deficit during the early and middle stages of seed development [50]. CAMBP25 is induced in Arabidopsis seedlings exposed to high salinity, dehydration, and low temperature [51]. PCC13 is abundantly expressed in dried leaves and abscisic acid-treated dried callus and is involved in the response to salt stress [52]; RBG7 plays a role in altering the germination and seedling growth of Arabidopsis under various stresses [53]; IQM4 plays a key role in modulating the responses to salt, ABA, and osmotic stress during seed germination and post-germination growth [54]; NFD4 mediates the transport of Na+ and K+ into the vacuole, influences plant development, and contributes to salt tolerance [55]; WSD1 is involved in the accumulation of wax esters in response to salt, drought, and ABA [56]; and At2g40140 plays important roles in modulating the tolerance of Arabidopsis to salt stress [57]. In this study, most of the genes involved in salt stress were UR, which may play a determining role in obtaining the ability of seed germination of A. venetum in saline–alkaline soils.
The primary effect of salt stress is hyperionic and hyperosmotic stresses, as well as, in severe cases, oxidative stress in plants. Oxidative stress is responsible for the generation of ROS, which are deleterious to plants. To minimize the effect of oxidative stress, plants have developed an efficient system of antioxidant enzymes (e.g., SOD, CAT, and APX) that can protect plants from damage [39,42,43,58,59,60,61]. Here, 23 genes were directly associated with antioxidant enzyme activities. For example, the SOD (SODCP, FSD2, and SODA) is a critical enzyme responsible for the elimination of superoxide radicals and is considered to be a key antioxidant in aerobic cells [23]; the POD (At5g06290, APX3, poxN1, PRDX1, PEX11C, and GPX1) catalyzes the reduction of hydrogen peroxide and plays a role in cell protection against oxidative stress by detoxifying peroxides [62]; and the CAT (CATA, CAT1, and PNC1) protects cells from the toxic effects of hydrogen peroxide [63]. In this study, most of the genes encoding SOD, POD, and CAT were UR, which is in accordance with the increased activities of SOD, POD, and CAT, which can reduce oxidative stress under salt stress.
Saline and alkaline ions can reduce the soil water potential, which makes it difficult for plants to absorb water, and then causes osmotic stress [35]. Previous studies have demonstrated that genes related to soluble sugar and protein metabolism play critical roles in response to salt stress in other plants. For example, the trehalose-6-phosphate synthase (TPS) gene plays a critical role in Citrullus lanatus’ response to salt stress [64]; the OsGolS1 gene is significantly up-regulated in Oryza sativa ssp. japonica under salt stress [65]; and the overexpression of MsTRX in tobacco induced the upregulation of beta-amylase 1 (BAM1) under salt stress [66]. In this study, 79 genes were directly associated with soluble sugar and protein metabolism, and 41 genes participate in soluble sugar metabolism. For example, G6PDC is involved in the synthesis of D-ribulose 5-phosphate from D-glucose 6-phosphate [67]; GAPA1 is involved in the synthesis of pyruvate from D-glyceraldehyde 3-phosphate [68]; PGMP is involved in both the breakdown and synthesis of glucose [69]; UGPA is involved in the UDP-glucose metabolic process [69]; INVE participates in cleaving sucrose into glucose and fructose and is associated with the assimilation of nitrogen to control the sucrose to hexose ratio [70]; SUS2 is involved in providing UDP-glucose and fructose for various metabolic pathways [71]; FKFBP is involved in the synthesis and degradation of fructose 2,6-bisphosphate [72]; F16P2 and FBA3 are involved in the fructose 1,6-bisphosphate metabolic process [69]; GOLS1 is involved in the synthesis of raffinose family oligosaccharides and promotes plant stress tolerance [73]; TPS6 is involved in the trehalose biosynthetic process [74]; OFUT39 is involved in the fucose metabolic process [75]; DPE2 is involved in the starch catabolic process and an intermediate on the pathway by which starch is converted to sucrose [76]; AMY3 is involved in stress-induced starch degradation [77]; BAM1 plays a role in the starch degradation and maltose metabolism [78]; and GWD3 is involved in starch degradation and mediates the incorporation of phosphate into starch-like phospho-alpha-glucan [79]. The other 38 genes participate in protein metabolism. For example, RPN1A is involved in the ATP-dependent degradation of ubiquitinated proteins [80]; PCS1 is involved in proteolysis and possesses peptidase activity toward casein [69,81]; Cys is involved in the protein catabolic process and shows the highest affinity for Pro [82]; DEGP1 is involved in the degradation of damaged proteins [83,84]; PBE2 is involved in the proteasomal protein catabolic process and shows an ATP-dependent proteolytic activity [69]; and SBT2.5 and ALEU are involved in proteolysis and show serine-type peptidase activity [69,85]. In this study, most of the genes involved in soluble sugar and protein metabolism were UR, which is in accordance with the increased content of soluble sugar and protein during seed germination.
For the biological functions of the six genes directly associated with seed germination, F16 is involved in seed trichome differentiation and expressed in the early phase of cotton fiber development [86]; GEM-like proteins (i.e., FIP1, At5g13200, and At5g23350) are involved in seed germination and play a novel role in regulating the reproductive development of plants [87]; KAI2 is involved in seed germination and seedling development [88]; and ROH1 is involved in seed coat development [89]. Thus, the differential expression of these genes could play important roles in seed germination under salt stress.
TFs are emerged as key regulators in various signaling networks and play significant roles by improving the growth and development of plants under stress conditions [90]. Previous studies have demonstrated that genes related to TFs play critical roles in response to salt stress in other plants. For example, the WRKY TFs of cotton play a significant role in the regulation of abiotic stresses (i.e., salt, drought, and extreme temperatures) [91]; MYB TFs are involved in the responses to different abiotic stresses, such as salt, cold, and drought, and the FvMYB82 gene probably plays an important role in the response to salt and cold stresses in Arabidopsis thaliana by regulating downstream related genes [92]; and NAC TFs play vital roles in plant development and responses to various abiotic stresses, and the ThNAC4 gene of Tamarix hispida is involved in salt and osmotic stress tolerance [93]. In this study, 16 TFs were directly associated with stress response and seed germination. Specifically for the stress response, MYB73 is involved in the salt-stress response [94]; WRKY TFs (WRKY24 and WRKY71) play critical regulatory roles in the plant alkaline metal (sodium) salt-stress response [95]; NAC083 is involved in xylem vessel formation and mediates signaling crosstalk between the salt-stress response and leaf-aging process [96]; and JA2L with MYC2 forms a transcription module that regulates wounding-responsive genes [97]. For seed germination, BZIP44 is involved in the positive regulation of seed germination through MAN7 gene activation [98]; TCP14 is involved in the regulation of seed germination and regulates the activation of embryonic growth potential during seed germination [99]; and UNE10 negatively regulates seed germination [100]. Here, their up-regulation may play a critical role in conferring the seed germination of A. venetum under salt stress.
As is known, endogenous hormones play critical roles in plant growth and development. Previous studies have demonstrated that genes related to hormone signaling play critical roles in response to salt stress in other plants. For example, SmGASA4 was found to be positively regulated by Gibberellin (GA) and significantly enhanced plant resistance to salt, drought, and paclobutrazol (PBZ) stress in Salvia miltiorrhiza [101]; Aux/IAA proteins in auxin and ARF transcription factors directly regulate auxin-responsive gene expression and OsIAA24 and OsIAA20 are up-regulated in rice under high salt stress [102]; genes related to Cytokinin (CK) and ethylene (ET) were involved in alleviating the root damage of Tamarix ramosissima under NaCl stress [103]. In this study, 36 genes were directly associated with hormone response. Specifically, GASA2 plays a role in the promotion of GA responses during seed germination, flowering, and seed maturation [104]; ARF2A, IAA9, and TET4 act as auxin-responsive genes and regulate vegetative growth, lateral root formation, and flower organ senescence [105,106]; CISZOG2 may regulate active versus storage forms of cytokinin (CTK) and can have an impact on seed growth [107]; AHK3 acts as a redundant positive regulator of CTK signaling that regulates many developmental processes such as seed germination, cell division, and shoot promotion [108]; JOX2 prevents the over-accumulation of jasmonate (JA) under stress responses [109]; TIFY6B acts as a repressor of JA responses and is involved in the regulation of defense responses [110]; PYL3 is involved in ABA signaling during seed germination and abiotic stress responses [111]; PP2CA acts as a major negative regulator of ABA responses during seed germination and cold acclimation [112]; ETR2 acts as a redundant negative regulator of ethylene (ETH) signaling [113]; and ERF013 may be involved in the regulation of gene expression by stress factors and by the components of stress signal transduction pathways [114]. Their differential expression may also play critical roles in promoting the seed germination of A. venetum.
Saline and alkaline stress can induce ion toxicity in plants when too many toxic ions enter plant cells, which can harm the plant cytoplasm and organelles; among them, Na+ is the main toxicity ion due to the similarity in size of the hydrated ionic radii of Na+ and K+, which makes them difficult to discriminate [115]. The salt overly sensitive (SOS) regulatory pathway regulates ion homeostasis by modulating Na+/H+ antiporter activity during salt stress [116]. Previous studies have demonstrated that genes related to ion transport play critical roles in the response to salt stress in other plants. For example, CLC-c is involved in the response to salt stress tolerance and seed germination in Gossypium hirsutum [117]; K+ efflux transporters (KEAs) were expressed under abiotic stress (salt, heat, and drought) in Cajanus cajan [118]; the Zipper (Zip) gene family participates in plant growth and development and the ability to cope with outside environment stresses, which may potentially regulate seed germination and stress resistance in Miscanthus sinensis [119]. In this study, 34 genes were directly associated with ion transport. For example, CSC1 acts as an osmosensitive calcium-permeable cation channel and is activated by hyperosmotic shock after NaCl treatment [120,121]; CLC-C is involved in ion transmembrane transport [122]; RAN1 is involved in copper import into the cell and acts by delivering copper to create functional hormone receptors [123]; KEA2 transports K+ and Cs+ preferentially relative to Na+ or Li+ [124]; OEP16 is involved in ion transport and acts as a voltage-dependent high-conductance channel [125]; PPI1 is involved in proton transport and promotes AHA1 plasma membrane ATPase activity by binding to a site different from the 14-3-3 binding site [126]; NHX2 is involved in the vacuolar ion compartmentalization necessary for cell volume regulation and cytoplasmic Na+ detoxification [127]; CAX1 translocates Ca2+ and other metal ions into vacuoles using the proton gradient formed by H+-ATPase and H+-pyrophosphatase [128]; VHA-a2 is involved in vacuolar nutrient storage and in the tolerance to some toxic ions, as well as catalyzing the translocation of protons across membranes [129]; and ZIP1 mediates zinc uptake from the rhizosphere and may also transport copper and cadmium ions [130]. Their differential expression may also play critical roles in promoting the seed germination of A. venetum under salt stress.
Based on the above studies on the physiological and transcriptional changes, a model of the low-salt-stress-enhanced seed germination of A. venetum is proposed (Figure 13). Briefly, when seeds are stimulated by salt stress, gene regulation is performed and related genes are differentially expressed; then, bio-signaling such as the hormone response (e.g., GASA2, IAAs, and PYLs) is generated; subsequently, the genes related to salt-stress responses (e.g., ALDHs, ANNs, and PCCs), soluble sugar metabolism (e.g., G6pc2, SUSs, and FBAs), protein metabolism (e.g., PSMD2, PRTs, and SBTs), TFs (e.g., MYBs, WRKYs, and NACs), and ion transport (e.g., AHA10, OEPs, and CAXs) are up-regulated, which promotes the antioxidant enzyme activities (e.g., SOD, POD, and CAT) and osmolyte contents (e.g., soluble sugar, MDA, and Pro) that protect the cells from salt-stress-induced membrane injury; finally, these changes are in favor of building the cell morphogenesis, enhancing seed germination, and conferring the ability to adapt to the saline–alkaline environment.

4. Materials and Methods

4.1. Plant Materials

Mature seeds of Apocynum venetum L. were collected from a resource nursery located at Alxa Left Banner, China (1050 m a.s.l.; E 103°42′14.77″, N 38°18′5.62″) in September 2020. Seeds were air dried at room temperature, stored at 4 °C in air-tight bags in the dark for two months, then cleaned with tap water and successively immersed in 50 °C water for 15 min and sanitized in 70% ethanol for 20 s. After being rinsed with sterile water 5 times, 30 seeds were sown in a Petri dish (15 cm diameter, two layers of gauze on the bottom) containing 10 mL of NaCl solution with 0 (CK), 50, 100, 150, 200, and 300 mmol/L. These doses were selected based on the published literature [11,16,17]. Each treatment had 40 independent biological replicates, which were made in 40 Petri dishes (30 seeds per dish).

4.2. Measurement of Germination Rate

After germination in a dark growth chamber at 22 °C for 3 days, the seed germination rate was measured. Three seeds were randomly collected from the 40 independent biological replicates for each NaCl treatment.

4.3. Determination of Antioxidant Enzyme Activities

The activities of 4 antioxidant enzymes including SOD, POD, CAT, and APX in seed embryos were determined using a spectrometer (Evolution 201, Thermo Scientific, Waltham, MA, USA). Briefly, SOD activity was determined based on the ability to inhibit the photochemical reduction of nitro blue tetrazolium chloride: extracts (100 μL) were added to the reaction, and the absorbance reading was taken at 560 nm [131]. POD activity was determined by the guaiacol colorimetric method: extracts (1000 μL) were added to the reaction and the absorbance reading was taken at 470 nm [132]. CAT activity was determined by the UV absorption method: extracts (100 μL) were added to the reaction and the absorbance reading was taken at 240 nm [133]. APX activity was determined based on the decrease in the absorbance of the oxidized ascorbate: extracts (100 μL) were added to the reaction and the absorbance reading was taken at 290 nm [134]. Each determination contained three biological replicates (a total of 120 samples = 3 seeds × 40 independent biological replicates) and each biological replicate had three technical replicates.

4.4. Determination of Osmolytes Content

The contents of 4 osmolytes including soluble sugar, protein, MDA, and Pro in seed embryos were determined using a spectrometer (Evolution 201, Thermo Scientific, Waltham, MA, USA). Briefly, the soluble sugar content was determined by the phenolsulfuric acid method: extracts (1000 μL) were added to the reaction and the absorbance reading was taken at 485 nm [135]. Protein content was determined by the comassie brilliant blue colorimetric method: extracts (800 μL) were added to the reaction and the absorbance reading was taken at 595 nm [136]. MDA content was determined by the thiobarbituric acid reaction: extracts (7000 μL) were added to the reaction and absorbance readings were taken at 532, 600, and 450 nm [137]. Pro content was determined by the sulfosalicylic acid-acid ninhydrin method: extracts (3000 μL) were added to the reaction and the absorbance reading was taken at 520 nm [138]. Each determination contained three biological replicates (a total of 120 samples = 3 seeds × 40 independent biological replicates) and each biological replicate had three technical replicates.

4.5. Transcriptomic Analysis

4.5.1. RNA Extraction, cDNA Library Construction, and Illumina Sequencing

Total RNA samples of CK and 300 mmol/L NaCl treatments with 3×40 biological replicates were extracted using an RNA kit (R6827, Omega Bio-Tek, Norcross, GA, USA). The RNA amount was quantified using a NanoDrop ND1000 spectrophotometer (Nanodrop Technologies, Wilmington, NC, USA), and the quality was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA). One cDNA library was constructed from the total RNA samples of CK and 300 mmol/L NaCl treatments, and the processes of enrichment, fragmentation, reverse transcription, the synthesis of the second-strand cDNA, and the purification of cDNA fragments were conducted as previously described [139]. Reads were generated using an Illumina HiSeqTM 4000 platform (Gene Denovo Biotechnology Co., Ltd., Guangzhou, China).

4.5.2. Reads Filtration, Assembly, Unigene Expression Analysis, and Basic Annotation

Raw reads were filtered using a FASTQ system to obtain high-quality clean reads by removing reads containing adapters, more than 10% of unknown nucleotides (N), and more than 50% of low-quality (Q-value ≤ 20) bases [140]. Clean reads were assembled using Trinity [141]. The expression level of each transcript was normalized to the RPKM values. The differential expression analysis of transcripts was performed using DESeq2 software [142] between the CK and 300 mmol/L NaCl treatments with the criteria of the false discovery rate (FDR) < 0.05 and |log2(fold-change)| > 1. The function of DEGs was annotated using BLAST against the databases, including Nr, KEGG, KOG, SwissProt, and GO, with an e-value ≤ 10−5 as a threshold [143].

4.5.3. qRT-PCR Validation

The primer sequences (Table S11) were designed via a primer blast in NCBI and synthesized by reverse transcription (Sangon Biotech Co., Ltd., Shanghai, China). First, cDNA was synthesized using an RT Kit (KR116, Tiangen, Beijing, China). PCR amplification was performed using a SuperReal PreMix (FP205, Tiangen, Beijing, China). The melting curve was analyzed at 72 °C for 34 s. The Actin gene was used as a reference control [14]. The RELs of genes were calculated using a 2−ΔΔCt method (Ct, cycle threshold value of target gene) according to the following formula [144]. The validation of qRT-PCR contained three biological replicates (a total of 120 samples = 3 seeds × 40 independent biological replicates) and each biological replicate had three technical replicates.
ΔCt Test gene = Ct Test gene − Ct Reference gene
ΔCt Control gene = Ct Control gene − Ct Reference gene
−ΔΔCt = −(ΔCt Test gene − ΔCt Control gene)
Relative gene expression fold (Test gene/Control gene) = 2−ΔΔCt

4.6. Statistical Analysis

SPSS 22.0 software was used for statistical analysis, and one-way analysis of variance (ANOVA) by Duncan’s test was performed for statistical comparisons with p < 0.05 considered statistically significant.

5. Conclusions

This research reveals that salt stress affects the seed germination of A. venetum. The seed germination of A. venetum is promoted at low NaCl concentrations such as 50 mmol/L, and significant changes in antioxidant enzyme activities, osmolyte contents, and genes expression levels in A. venetum play critical roles in regulating seed germination under different salt stresses. These findings indicate that A. venetum plants can adapt to salt stress in saline–alkaline soils by integrating physiological and transcriptional responses. The specific roles of key genes in conferring the ability to salt resistance will require further investigation.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24043623/s1.

Author Contributions

X.L.: data curation, formal analysis, and writing—original draft preparation; J.L.: data curation, formal analysis, and validation; H.S.: formal analysis, methodology, and validation; P.S.: formal analysis and methodology; Z.Z.: formal analysis; M.L.: conceptualization, funding acquisition, and writing—review and editing; H.X.: resources, supervision, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the State Key Laboratory of Aridland Crop Science Gansu Agricultural University (GSCS-2021-Z03).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets are publicly available at NCBI (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA847749, accessed on 2 August 2022), and Sequence Read Archive (SRA) accession: CK (SRR20341324, SRR20341330, and SRR20341336), and 300 mmol/L NaCl (SRR20341332, SRR20341333, and SRR20341334).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Change in the seed germination rate of Apocynum venetum under different NaCl treatments. Different letters represent a significant difference (p < 0.05) among different NaCl treatments.
Figure 1. Change in the seed germination rate of Apocynum venetum under different NaCl treatments. Different letters represent a significant difference (p < 0.05) among different NaCl treatments.
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Figure 2. Changes in the activities of the four antioxidant enzymes SOD (A), POD (B), CAT (C), and APX (D) in A. venetum seeds at different NaCl treatments. Different letters represent a significant difference (p < 0.05) among different NaCl treatments.
Figure 2. Changes in the activities of the four antioxidant enzymes SOD (A), POD (B), CAT (C), and APX (D) in A. venetum seeds at different NaCl treatments. Different letters represent a significant difference (p < 0.05) among different NaCl treatments.
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Figure 3. Changes in the contents of soluble sugar (A), protein (B), MDA (C), and proline (D) in A. venetum seeds under different NaCl treatments. Different letters represent a significant difference (p < 0.05) among different NaCl treatments.
Figure 3. Changes in the contents of soluble sugar (A), protein (B), MDA (C), and proline (D) in A. venetum seeds under different NaCl treatments. Different letters represent a significant difference (p < 0.05) among different NaCl treatments.
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Figure 4. Volcano plot of unigenes (A), number of DEGs (B), and cluster heat map of the DEGs (C) for NaCl (300 mmol/L) vs. CK. The black represent the genes without difference changes in the criteria of the false discovery rate (FDR) < 0.05 and |log2(fold-change)| > 1.
Figure 4. Volcano plot of unigenes (A), number of DEGs (B), and cluster heat map of the DEGs (C) for NaCl (300 mmol/L) vs. CK. The black represent the genes without difference changes in the criteria of the false discovery rate (FDR) < 0.05 and |log2(fold-change)| > 1.
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Figure 5. Distribution and classification of DEGs at 300 mmol/L NaCl vs. CK. Abbreviations: UR, up-regulated, DR, down-regulated. Image (A) represents the distribution of unidentified and identified genes; image (B) represents the distribution of uncharacterized and characterized genes, and image (C) represents the classification of the characterized biological functional genes.
Figure 5. Distribution and classification of DEGs at 300 mmol/L NaCl vs. CK. Abbreviations: UR, up-regulated, DR, down-regulated. Image (A) represents the distribution of unidentified and identified genes; image (B) represents the distribution of uncharacterized and characterized genes, and image (C) represents the classification of the characterized biological functional genes.
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Figure 6. The RELs of genes directly associated with salt stress in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 6. The RELs of genes directly associated with salt stress in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
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Figure 7. The RELs of genes directly associated with antioxidant enzymes in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 7. The RELs of genes directly associated with antioxidant enzymes in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
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Figure 8. The RELs of genes directly associated with soluble sugar and protein metabolism in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 8. The RELs of genes directly associated with soluble sugar and protein metabolism in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
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Figure 9. The RELs of genes directly associated with cell morphogenesis for seed germination in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 9. The RELs of genes directly associated with cell morphogenesis for seed germination in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
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Figure 10. The RELs of TFs directly associated with stress response and seed germination in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 10. The RELs of TFs directly associated with stress response and seed germination in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
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Figure 11. The RELs of genes directly associated with hormone response in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 11. The RELs of genes directly associated with hormone response in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Ijms 24 03623 g011
Ijms 24 03623 g012 550
Figure 12. The RELs of genes directly associated with ion transport in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
Figure 12. The RELs of genes directly associated with ion transport in A. venetum seeds at 300 mmol/L NaCl vs. CK (mean ± SD, n = 3). Different letters represent a significant difference (p < 0.05) among different genes. The red dotted line differentiates UR (>1) and DR (<1).
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Figure 13. A proposed model of the low-salt-stress-enhanced seed germination of A. venetum.
Figure 13. A proposed model of the low-salt-stress-enhanced seed germination of A. venetum.
Ijms 24 03623 g013
Table
Table 1. Summary of sequencing data of seed germination under the CK and 300 mmol/L treatments (mean ± SD, n = 3).
Table 1. Summary of sequencing data of seed germination under the CK and 300 mmol/L treatments (mean ± SD, n = 3).
CK300 mmol/L NaCl
Filtered data
Data of reads number (million)51.43 ± 12.2365.36 ± 26.19
Data of reads number×read length (million)7714 ± 18359803 ± 3928
Q20 (%)97.18 ± 0.2896.99 ± 0.04
Q30 (%)92.33 ± 0.5691.93 ± 0.08
Mapped data
Data of unique mapped reads (million)42.12 ± 10.0253.26 ± 21.33
Data of multiple mapped reads (million)0.81± 0.110.80 ± 0.33
Mapping ratio (%)83.47 ± 3.0882.71 ± 4.12
Table
Table 2. Twenty-nine genes directly associated with salt stress at 300 mmol/L NaCl vs. CK.
Table 2. Twenty-nine genes directly associated with salt stress at 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
ALDH7B4Q9SYG7Aldehyde dehydrogenase family 7 member B44.13
ALDH10A8Q9S795Aminoaldehyde dehydrogenase ALDH10A83.91
ANN2Q9XEE2Annexin D24.33
ANN5Q9C9X3Annexin D54.51
B2P37707B2 protein4.38
RD22Q08298BURP domain protein RD224.60
CAMBP25O80683Calmodulin-binding protein 254.19
CTL1Q9MA41Chitinase-like protein 13.03
RD19AP43296Cysteine protease RD19A3.95
PCC13P22242Desiccation-related protein PCC13-62−2.53
PCC27P22241Desiccation-related protein PCC27-453.94
FLZ13Q8GRN0FCS-Like Zinc finger 13−2.97
GRP1Q03878Glycine-rich RNA-binding protein5.23
RBG7Q03250Glycine-rich RNA-binding protein 73.30
HMGB2O49596High mobility group B protein 23.61
IQM4O64851IQ domain-containing protein IQM48.89
NRP1Q9ZQ80Nodulin-related protein 13.65
ATP1Q9LU63Probable pterin-4-alpha-carbinolamine dehydratase4.80
ARP1Q9M1S3Probable RNA-binding protein ARP1−1.09
ERD7O48832Protein EARLY-RESPONSIVE TO DEHYDRATION 78.98
NFD4F4I9E1Protein NUCLEAR FUSION DEFECTIVE 44.68
AVP1P31414Pyrophosphate-energized vacuolar membrane proton pump 13.98
REM4.1Q93YN8Remorin 4.11.16
ALDH5F1Q9SAK4Succinate-semialdehyde dehydrogenase4.24
TILQ9FGT8Temperature-induced lipocalin-14.08
WSD1Q93ZR6Wax ester synthase/diacylglycerol acyltransferase 1−1.11
At2g40140Q9XEE6Zinc finger CCCH domain-containing protein 291.30
Os07g0682400Q0D3J9Zinc finger CCCH domain-containing protein 533.70
ZFNLQ9SWF9Zinc finger CCCH domain-containing protein ZFN-like5.48
Table
Table 3. Twenty-three genes directly associated with antioxidant enzymes at the 300 mmol/L NaCl vs. CK.
Table 3. Twenty-three genes directly associated with antioxidant enzymes at the 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
SOD (3)
SODCPP07505Superoxide dismutase (Cu-Zn), chloroplastic3.98
FSD2Q9LU64Superoxide dismutase (Fe) 2, chloroplastic3.62
SODAP11796Superoxide dismutase (Mn), mitochondrial8.98
POD (17)
At5g06290Q9C5R82-Cys peroxiredoxin BAS1-like, chloroplastic3.39
APX3Q42564L-ascorbate peroxidase 33.31
APX1P48534L-ascorbate peroxidase, cytosolic1.08
PER12Q96520Peroxidase 125.22
PER23O80912Peroxidase 23−3.11
PER31Q9LHA7Peroxidase 315.22
PER42Q9SB81Peroxidase 423.83
PER52Q9FLC0Peroxidase 521.52
poxN1Q9XIV8Peroxidase N1−3.93
PRDX1Q06830Peroxiredoxin-19.68
PRDX2A9PCL4Peroxiredoxin-23.52
PRXIIEQ949U7Peroxiredoxin-2E, chloroplastic6.02
PEX5Q9FMA3Peroxisome biogenesis protein 53.81
PEX11CQ9LQ73Peroxisomal membrane protein 11C4.38
PEX13Q9SRR0Peroxisomal membrane protein 138.99
PEX14Q9FXT6Peroxisomal membrane protein PEX144.29
GPX1P52032Phospholipid hydroperoxide glutathione peroxidase 13.70
CAT (3)
CATAQ9AXH0Catalase3.80
CAT1P17598Catalase isozyme 13.78
PNC1P22195Cationic peroxidase 13.52
Table
Table 4. Seventy-nine DEGs directly associated with soluble sugar and protein metabolism at 300 mmol/L NaCl vs. CK.
Table 4. Seventy-nine DEGs directly associated with soluble sugar and protein metabolism at 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
Glucose (11)
G6pc2Q9Z186Glucose-6-phosphatase 29.28
G6PDCQ43839Glucose-6-phosphate 1-dehydrogenase, chloroplastic3.29
GAPBP12859Glyceraldehyde-3-phosphate dehydrogenase B3.73
GAPA1P25856Glyceraldehyde-3-phosphate dehydrogenase GAPA13.85
GAPC2Q9FX54Glyceraldehyde-3-phosphate dehydrogenase GAPC23.65
PGMPQ9M4G5Phosphoglucomutase, chloroplastic3.47
PGM1Q9ZSQ4Phosphoglucomutase, cytoplasmic3.20
GcgP55095Pro-glucagon12.87
PSL5Q9FN05Probable glucan 1,3-alpha-glucosidase3.31
UGD3Q9AUV6UDP-glucose 6-dehydrogenase 33.50
UGPAP19595UTP--glucose-1-phosphate uridylyltransferase4.88
Sucrose (3)
INVEQ9FK88Alkaline/neutral invertase E, chloroplastic8.90
SUS2O24301Sucrose synthase 23.82
SUS3Q9M111Sucrose synthase 3−3.29
Fructose (9)
FKFBPQ9MB586-phosphofructo-2-kinase/fructose-2,6-bisphosphatase3.50
RHVI2H2DF88Acid beta-fructofuranosidase 2, vacuolar−1.32
FRK2Q42896Fructokinase-25.37
FBPP46275Fructose-1,6-bisphosphatase, chloroplastic3.26
F16P2P46276Fructose-1,6-bisphosphatase, cytosolic4.07
FBA2Q944G9Fructose-bisphosphate aldolase 2, chloroplastic3.49
FBA3Q9ZU52Fructose-bisphosphate aldolase 3, chloroplastic1.93
FBA6Q9SJQ9Fructose-bisphosphate aldolase 6, cytosolic1.31
FBA1P46256Fructose-bisphosphate aldolase, cytoplasmic isozyme 14.00
Galactose (2)
GOLS1O22893Galactinol synthase 18.16
GOLS2C7G304Galactinol synthase 28.35
Trehalose (2)
TPS6Q94AH8Alpha,alpha-trehalose-phosphate synthase 4.20
TPS7Q9LMI0Probable alpha,alpha-trehalose-phosphate synthase 3.11
Fucose (2)
OFUT19Q9SH89O-fucosyltransferase 191.08
OFUT39Q0WUZ5O-fucosyltransferase 393.78
Starch (12)
SBEIQ410581,4-alpha-glucan-branching enzyme 13.43
DPE2Q8RXD94-alpha-glucanotransferase DPE24.63
AMY3Q94A41Alpha-amylase 3, chloroplastic3.49
R1Q8LPT9Alpha-glucan water dikinase, chloroplastic3.37
BAM1Q9LIR6Beta-amylase 1, chloroplastic4.43
BAM3O23553Beta-amylase 3, chloroplastic4.61
ADG2P55229Glucose-1-phosphate adenylyltransferase large subunit 13.43
AGPS1Q9M462Glucose-1-phosphate adenylyltransferase small subunit2.91
ISA1D0TZF0Isoamylase 1, chloroplastic5.35
DSP4G4LTX4Phosphoglucan phosphatase DSP4, amyloplastic3.88
GWD3Q6ZY51Phosphoglucan, water dikinase, chloroplastic4.48
SS4Q0WVX5Probable starch synthase 4, chloroplastic/amyloplastic5.33
Protein (38)
PSMD2Q5R9I626S proteasome non-ATPase regulatory subunit 24.39
RPN1AQ9SIV226S proteasome non-ATPase regulatory subunit 2 homolog A3.51
RPN9BQ8GYA626S proteasome non-ATPase regulatory subunit 13 homolog B8.52
RPN10P5503426S proteasome non-ATPase regulatory subunit 4 homolog4.94
RPT5AQ9SEI226S proteasome regulatory subunit 6A homolog A3.39
RPT1AP0DKJ926S proteasome regulatory subunit 7A5.17
RPT6AQ9C5U326S proteasome regulatory subunit 8 homolog A4.29
RPT4AQ9SEI326S proteasome regulatory subunit 10B homolog A8.74
PCS1Q9LZL3Aspartic proteinase PCS13.89
APF2Q9LNJ3Aspartyl protease family protein 28.63
At5g10770Q8S9J6Aspartyl protease family protein At5g107704.31
CysQ86GF7Crustapain−10.16
SMAC_06893D1ZSU8Extracellular metalloprotease SMAC_06893−6.78
GGP5O82225Gamma-glutamyl peptidase 54.19
LAP2Q944P7Leucine aminopeptidase 2, chloroplastic3.76
Pcsk2P21661Neuroendocrine convertase 25.62
maoIQ07121Primary amine oxidase3.53
RD19CQ9SUL1Probable cysteine protease RD19C5.48
RD21BQ9FMH8Probable cysteine protease RD21B2.33
MPPbetaQ42290Probable mitochondrial-processing peptidase subunit beta6.03
PrepQ9QUR6Prolyl endopeptidase−2.29
DEGP1O22609Protease Do-like 1, chloroplastic5.36
DEGP2O82261Protease Do-like 2, chloroplastic3.67
PBG1Q7DLR9Proteasome subunit beta type-48.91
PBE2Q9LIP2Proteasome subunit beta type-5-B4.84
PBA1Q8LD27Proteasome subunit beta type-64.68
MPA1Q8H0S9Puromycin-sensitive aminopeptidase3.52
Rbp3P49194Retinol-binding protein 3−7.96
RBL6Q8VZ48RHOMBOID-like protein 6, mitochondrial5.28
SCPL49P32826Serine carboxypeptidase-like 494.84
SBT1.2O64495Subtilisin-like protease SBT1.2−1.73
SBT1.4Q9LVJ1Subtilisin-like protease SBT1.48.46
SBT1.6O49607Subtilisin-like protease SBT1.63.21
SBT1.7O65351Subtilisin-like protease SBT1.70.77
SBT2.5O64481Subtilisin-like protease SBT2.54.43
SPDS1Q96556Spermidine synthase 15.04
ALEUQ8H166Thiol protease aleurain3.66
TPP2F4JVN6Tripeptidyl-peptidase 24.06
Table
Table 5. Six DEGs directly associated with cell morphogenesis for seed germination at 300 mmol/L NaCl vs. CK.
Table 5. Six DEGs directly associated with cell morphogenesis for seed germination at 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
F16Q8W4Z5CASP-like protein F169.63
FIP1Q9SE96GEM-like protein 15.00
At5g13200Q9LYV6GEM-like protein 57.09
At5g23350Q9FMW6GEM-like protein 6−1.28
KAI2Q9SZU7Probable esterase KAI29.61
ROH1Q9CAK4Protein ROH13.61
Table
Table 6. Sixteen TFs directly associated with stress response and seed germination at 300 mmol/L NaCl vs. CK.
Table 6. Sixteen TFs directly associated with stress response and seed germination at 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
MYB (2)
MYB73O23160Transcription factor MYB735.75
MYB1R1Q2V9B0Transcription factor MYB1R13.32
WRKY (7)
WRKY4Q9XI90Probable WRKY transcription factor 44.19
WRKY23O22900WRKY transcription factor 231.15
WRKY24Q6IEQ7WRKY transcription factor WRKY245.42
WRKY33Q8S8P5Probable WRKY transcription factor 334.71
WRKY40Q9SAH7Probable WRKY transcription factor 40−1.20
WRKY49Q9FHR7Probable WRKY transcription factor 491.48
WRKY71Q93WV4WRKY transcription factor 712.01
NAC (4)
NAC083Q9FY93NAC domain-containing protein 833.76
NAC091Q9LKG8NAC domain-containing protein 915.15
NAC100Q9FLJ2NAC domain-containing protein 1001.34
JA2LA0A3Q7HH64NAC domain-containing protein JA2L1.64
bZIP (1)
BZIP44C0Z2L5bZIP transcription factor 445.39
TCP (1)
TCP14Q93Z00Transcription factor TCP143.78
UNE (1)
UNE10Q8GZ38Transcription factor UNE104.16
Table
Table 7. Thirty-six DEGs directly associated with hormone response at 300 mmol/L NaCl vs. CK.
Table 7. Thirty-six DEGs directly associated with hormone response at 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
GA (1)
GASA2P46688Gibberellin-regulated protein 24.35
IAA (14)
ABP19AQ9ZRA4Auxin-binding protein ABP19a3.50
AUX22DO24542Auxin-induced protein 22D3.32
AUX12KDQ05349Auxin-repressed 12.5 kDa protein3.57
ARF2AQ2LAJ3Auxin response factor 2A−2.28
ARF2BK4DF01Auxin response factor 2B3.98
ARF6Q9ZTX8Auxin response factor 64.48
IAA4P33077Auxin-responsive protein IAA43.62
IAA8Q38826Auxin-responsive protein IAA84.07
IAA9Q38827Auxin-responsive protein IAA94.24
IAA14Q38832Auxin-responsive protein IAA143.85
SAUR71Q9SGU2Auxin-responsive protein SAUR71−1.28
LAX2Q9FEL7Auxin transporter-like protein 22.89
TET4Q9LSS4Tetraspanin-44.97
TET8Q8S8Q6Tetraspanin-83.93
CTK (3)
CISZOG2Q8RXA5Cis-zeatin O-glucosyltransferase 2−1.09
AHK3Q9C5U1Histidine kinase 34.69
ARR4O82798Two-component response regulator ARR41.09
JA (2)
JOX2Q9FFF6Jasmonate-induced oxygenase 22.21
TIFY6BQ9LVI4Protein TIFY 6B3.61
ABA (6)
PYL3Q6EN42Abscisic acid receptor PYL33.73
PYL4O80920Abscisic acid receptor PYL4−1.14
GRDP1Q9ZQ47Glycine-rich domain-containing protein 13.49
PP2CAP49598Protein phosphatase 2C 375.90
PP2C51Q65XK7Protein phosphatase 2C 511.43
SAL1Q42546SAL1 phosphatase3.31
ETH (10)
RAV1Q9ZWM9AP2/ERF and B3 domain-containing transcription factor 3.47
ETR2Q0WPQ2Ethylene receptor 2−2.03
ERF4Q9LW49Ethylene-responsive transcription factor 49.00
ERF5Q40478Ethylene-responsive transcription factor 50.83
ERF013Q9CAP4Ethylene-responsive transcription factor ERF013−2.74
ERF016Q9C591Ethylene-responsive transcription factor ERF0162.11
ERF113Q9LYU3Ethylene-responsive transcription factor ERF1131.95
RAP2-2Q9LUM4Ethylene-responsive transcription factor RAP2-24.50
RAP2-4Q8H1E4Ethylene-responsive transcription factor RAP2-43.65
EIN3O24606Protein ETHYLENE INSENSITIVE 34.05
Table
Table 8. Thirty-four DEGs directly associated with ion transport at 300 mmol/L NaCl vs. CK.
Table 8. Thirty-four DEGs directly associated with ion transport at 300 mmol/L NaCl vs. CK.
Gene NameSwissProt IDProtein Namelog2FC (NaCl vs. CK)
AHA10Q43128ATPase 10, plasma membrane-type3.98
CSC1Q5XEZ5Calcium permeable stress-gated cation channel 14.65
CLC-BP92942Chloride channel protein CLC-b4.68
CLC-CQ96282Chloride channel protein CLC-c3.91
ATX1Q94BT9Copper transport protein ATX16.95
PAA2B9DFX7Copper-transporting ATPase PAA2, chloroplastic8.69
RAN1Q9S7J8Copper-transporting ATPase RAN14.28
ERD4A9LIW2CSC1-like protein ERD43.81
KEA2O65272K(+) efflux antiporter 2, chloroplastic5.20
MOT1Q9SL95Molybdate transporter 1−2.18
NEW1Q08972[NU+] prion formation protein 1−9.03
OEP16Q41050Outer envelope pore protein 16, chloroplastic3.58
OEP162Q0WMZ5Outer envelope pore protein 16-2, chloroplastic1.59
PHO1-H1Q93ZF5Phosphate transporter PHO1 homolog 1−1.21
PPI1O23144Proton pump-interactor 13.54
Atp2a3Q64518Sarcoplasmic/endoplasmic reticulum calcium ATPase 39.37
NHX2Q56XP4Sodium/hydrogen exchanger 23.07
ATP1A3P13637Sodium/potassium-transporting ATPase subunit alpha-3−9.32
CAX1Q39253Vacuolar cation/proton exchanger 12.30
CAX3Q93Z81Vacuolar cation/proton exchanger 33.94
VPS2.1Q9SKI2Vacuolar protein sorting-associated protein 2 homolog 14.27
VPEP49043Vacuolar-processing enzyme1.64
VSR1P93026Vacuolar-sorting receptor 14.04
VATLQ96473V-type proton ATPase 16 kDa proteolipid subunit4.97
VHA-a2Q9SJT7V-type proton ATPase subunit a24.06
VATB1Q43432V-type proton ATPase subunit B 13.65
VHA-CQ9SDS7V-type proton ATPase subunit C5.36
VHA-DQ9XGM1V-type proton ATPase subunit D4.70
VHA-d2Q9LHA4V-type proton ATPase subunit d24.43
VATEQ9SWE7V-type proton ATPase subunit E4.41
VHA-HQ9LX65V-type proton ATPase subunit H4.04
ZIP1O81123Zinc transporter 1−1.58
ZIP4O04089Zinc transporter 4, chloroplastic−1.06
ZIP5Q6L8G0Zinc transporter 5−2.14
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MDPI and ACS Style

Li, X.; Li, J.; Su, H.; Sun, P.; Zhang, Z.; Li, M.; Xing, H. Physiological and Transcriptional Responses of Apocynum venetum to Salt Stress at the Seed Germination Stage. Int. J. Mol. Sci. 2023, 24, 3623. https://doi.org/10.3390/ijms24043623

AMA Style

Li X, Li J, Su H, Sun P, Zhang Z, Li M, Xing H. Physiological and Transcriptional Responses of Apocynum venetum to Salt Stress at the Seed Germination Stage. International Journal of Molecular Sciences. 2023; 24(4):3623. https://doi.org/10.3390/ijms24043623

Chicago/Turabian Style

Li, Xin, Jinjuan Li, Hongyan Su, Ping Sun, Zhen Zhang, Mengfei Li, and Hua Xing. 2023. "Physiological and Transcriptional Responses of Apocynum venetum to Salt Stress at the Seed Germination Stage" International Journal of Molecular Sciences 24, no. 4: 3623. https://doi.org/10.3390/ijms24043623

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