Response of different cotton genotypes to salt stress and rewatering

doi:10.21203/rs.3.rs-4711357/v1

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Research Article

Response of different cotton genotypes to salt stress and rewatering

https://doi.org/10.21203/rs.3.rs-4711357/v1

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Background: Cotton is a vital economic crop and reserve material and a pioneer crop planted on saline-alkaline soil. Improving the tolerance of cotton to saline alkaline environments is particularly important.

Results: Salt-tolerant and salt-sensitive cotton plants at the three-leaf stage were subjected to 200 mM NaCl stress treatment, and microstructural observations and physiological and biochemical analyses were performed on cotton leaves at 0 h (CK), 48 h (NaCl) and re-watering (RW) for 48 h. Salt-tolerant materials showed better salt tolerance and faster recovery after re-watering than sensitive materials. Transcriptome analysis was performed on cotton leaves under salt stress and re-watering conditions. A total of 32,390 DEGs were identified between the two materials under the different treatments. KEGG analysis revealed that the response of cotton to salt stress and its adaptation to re-watering may be related to interactions such as photosynthesis (ko 00195), photosynthesis-antenna protein (ko 00196), plant hormone signal transduction (ko 04075), starch and sucrose metabolism (ko 00500), and porphyrin and chlorophyll metabolism (ko 00860). A gray coexpression module associated with cotton restoration under salt stress was enriched according to WGCNA.

Conclusions: Salt stress not only affected the physiological and biochemical levels of cotton but also induced structural changes in cells and tissues, and re-watering alleviated the physiological and biochemical changes in cotton plants under salt stress. WGCNA revealed enriched gray coexpression modules related to the recovery of cotton plants under salt stress, and screening of the pivotal genes in the gray module revealed five critical hubs, namely, GH_A01G1528, GH_A08G2688, GH_D08G2683, GH_D01G1620 and GH_A10G0617. Overall, our findings can provide new insights into enhancing cotton salt tolerance and exploring salt tolerance genes in cotton.

cotton

salt stress

RNA-seq

salt tolerance

Soil salinization seriously affects agricultural activities and food security and is an important ecological problem worldwide[1, 2]. Approximately 800,000 hectares of irrigated soil, or 40% of the total irrigated area, are affected by soil salinization worldwide[3]. With the increase in human activities and ecological deterioration, reclamation areas continue to expand, causing constant growth in soil salinization. It is estimated that by 2050, 50% of the world's agricultural land will experience varying degrees of soil salinization[4]. Moreover, secondary salinization in arid and semiarid regions of China tends to increase annually [5]. Xinjiang has sparse precipitation, high evaporation, and special geology, which cause the accumulation of inorganic salts in the soil and make it prone to soil salinization[6]. Salt-alkaline soil is a general term for salinized soils, including saline soil, alkaline soil, alkaline soil, and other soils that exhibit different levels of salinization[7, 8]. Saline soil has a high content of neutral salts, including NaCl and Na₂SO₄. Crop growth and development are influenced mainly by osmotic equilibrium, ion toxicity, nutrient absorption, synthesis, and respiration[9-13].

To adapt to salt stress, plants have developed various adaptive strategies[6]. Salt-tolerant plants may increase leaf thickness[14] and root development[15] to improve water and nutrient absorption under salt stress. Compared with the normal ecotype of Imperata cyclindrica (L. Raeuschel), which grows in salt-free environments, the solar pond ecotype under salt stress has thicker cuticles, more succulent leaves, more developed palisade tissues, and more sunken stomata[16]. In saline environments, plants may also regulate the composition and structure of cell walls to maintain cell stability and integrity[17]. High pH stress in salt-alkalinene soil directly damages the absorption and transport of root ions. The efflux of K⁺from roots causes K⁺-Na⁺imbalance and a decrease in stomatal conductivity. Furthermore, as the concentration of soil salt-alkalinene increased, the length, width, and pore size of the stomata decreased[18]. However, plants can redistribute ions and soluble compounds under salt stress to alleviate the adverse effects of salt on cellular function and metabolism[19]. For example, plants transport excessive Na⁺ from mesophyll cells to leaf veins, reducing Na⁺ toxicity in the cytoplasm and maintaining normal photosynthesis in leaves[20, 21]. Salt stress can induce excessive production of reactive oxygen species (ROS) in plants, leading to membrane damage[22]. Various enzymes with ROS scavenging abilities, such as catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD), have been found in plants, all of which can enhance plant salt tolerance[23]. Plants may also synthesize antioxidants to counter damage induced by oxidative stress[24]. Melatonin, as a free radical scavenger and antioxidant, plays a critical role in improving the antioxidant system under salt stress[25]. Plants may change their patterns of gene expression under salt stress[26, 27], such as genes that directly protect plants from environmental stress and that regulate the expression of target genes in response to stress.

Cotton (Gossypium hirsutum), a member of the Mallow family, is a pioneer crop in the development and utilization of salt-alkalinene land[28]. It is a major economic crop in China, holding a prominent position in national politics, economy, culture, and social life[29, 30]. High salt stress affects chlorophyll synthesis, resulting in slow and abnormal seedling growth and difficulty in spreading two cotyledons[31]. Cotton plants begin flower bud differentiation and are sensitive to salt stress during the two-leaf and trefoil stages[32]. Usually, cotton plants exhibit symptoms such as leaf margin carving, leaf color darkening, cotyledon shedding, and plant wilt under salt stress. This is because the increase in osmotic pressure in the soil solution leads to physiological drought and ion accumulation and hinders the absorption of nutrients and water[33]. Studies of salt tolerance in cotton have shown that important membrane receptors involved in the biosynthesis and signal transduction of calc-dependent protein kinases, mitogen-activated protein kinases and hormones (abscisic acid and ethylene), as well as transporters and pathcode-coding genes, are upregulated[34]. By performing different salt-alkaline treatments on upland cotton, the specific alkaline resistance candidate gene GhA12G2168 (cystathionine γ-synthase gene ChMGL11) was identified[35]. Melatonin can enhance cotton salt tolerance by regulating various mechanisms, such as antioxidant systems, plant hormones, transcription factors, phospholipid metabolism, and signaling molecules[36]. Under the interaction of cotton, bacteria, and salt, symbiotic metabolites, inositol and galactose are converted into raffinose to participate in plant osmoregulation and eliminate free radicals to alleviate salt stress[37]. These findings provide new ideas for breeding salt-tolerant cotton and are expected to be further applied in related fields.

For plants under salt stress, re-watering can effectively restore their phenotype, physiology, and gene expression, alleviating the influence of salinity on plants. However, there is limited research on how re-watering affects plant responses to salt stress[38]. A deep understanding of the physiological and molecular mechanisms of salt stress and re-watering is conducive to protecting and efficiently utilizing water resources[39]. In addition, because of its high efficiency in mining function-related genes in coexpression modules, weighted gene coexpression network analysis (WGCNA) has been extensively applied to mine corresponding candidate genes in crops[40]. This study investigated the response of cotton to salt stress and its adaptability after re-watering through morphology, physiology, and microstructure analyses. Moreover, cotton salt tolerance genes were identified through RNA-seq technology. This study provides a theoretical basis for further exploration of the molecular mechanism of cotton salt tolerance and genetic resources for breeding salt-tolerant cotton.

Experimental Design

This study used two cotton materials with significant differences in salt tolerance, namely, The Yangtze River Valley-52-128 (Salt-Sensitive type, SS) and The Yellow River Valley-Jing Si Mian (Salt-Tolerant type, ST) . Cotton seeds were collected from the experimental base of Xinjiang Agricultural University, Shawan County, Xinjiang Uygur Autonomous Region. Natural salt-tolerant soil experiments were conducted in Shawan, China, from 2018 to 2019 (Table S1). Du et al.[41] verified the differences in salt tolerance between these two materials during the seedling stage. The seeds were disinfected with 5% sodium hypochlorite (NaClO) for 20 minutes, rinsed three times with sterile water, and sowed in germination boxes (12.4 cm × 17.5 cm) under controlled conditions (day and night temperatures of 26°C/18°C, relative humidity of 65%, day and night duration of 8 h/16 h, and light intensity of 12,000 lux; stored in artificial climate boxes). After the cotyledons were fully unfolded, the plants were transferred to a 1/2 Hoagland nutrient solution until the trefoil stage. Cotton plants at the trefoil stage were cultivated in a 200 mM NaCl solution for 48 h and then cultured in 1/2 Hoagland nutrient solution for 48 h (re-watering, RW). Samples were taken at 0 h, 48 h, and 48 h. There were 100 plants with three biological replicates. A total of 18 samples (3 time points× 2 varieties × 3 biological replicates) were collected.

Physiological Measurement

The maximum functional leaves of cotton plants under different treatments were measured using a portable chlorophyll analyzer (SPAD-502Plus). The malondialdehyde content, superoxide dismutase activity, and peroxidase activity were measured using thiobarbituric acid colorimetry, the nitrogen blue tetrazole photoreduction method, and the guaiacol hydrogen peroxide method, respectively[42].

Morphological observation

Leaves from the different treatment groups were cut vertically from veins and placed in FAA fixation solutions separately. Pruning, dehydration, embedding, slicing, and staining should be carried out when the leaves are in good fixed condition. Finally, the sample was sealed through a microscope and stained with saffron rapid green staining solution. Images were collected and scanned using a panoramic slicing scanner (models: PANNORAMIC DESK/MIDI/250/1000 and CaseViewer2.2) produced by 3DHISTECH (Hungary). Image-Pro Plus 6.0 produced by Media Cybertics (USA) was used to analyze these images. The thicknesses of each slice at five locations, namely, the upper epidermis, palisade tissue, sponge tissue, and lower epidermis, were measured and averaged.

RNA Extraction and cDNA Library Construction

At 0 h and 48 h of NaCl treatment and at 48 h of RW treatment, the leaves of the ST and SS plants were collected and immediately frozen in liquid nitrogen. Then, all the samples were stored at -80°C for RNA-Seq analysis. Total RNA was extracted according to the product manual of Tiangen's polysaccharide and polyphenol total RNA extraction kit. RNA degradation and contamination were detected by 1% agarose gel electrophoresis. A Nanodrop 2000 (Thermo Fisher Nanodrop 2000, Shanghai, China) was used for concentration detection. An Agilent 2100 (Platinum Elmer LabChip GX, Beijing, China) was used to calibrate the RNA integrity. The RNA concentration was calibrated based on qubit quantitation (Life Technologies, Beijing, China). The samples with OD260/280 values ranging from 1.8 to 2.2 and OD260/230 g ranging from 1.8 to 2.2 were qualified. Qualified RNAs were sent to Beijing Biomarker Biological Company for cDNA library construction. The Illumina high-throughput sequencing platform was used to sequence the cDNA library and obtain the raw data.

Data and Differentially Expressed Gene (DEG) Analysis

Original readings were obtained using Illumina. First, fastp software[43] was used for data filtering and quality control. Clean reads were obtained while calculating the Q30 and GC content. Then, HISAT2 software was used to map the clean reads to the cotton reference genome Gossypium_Hirsutum.TM_1_V2.1.genome.fa[44]. StringTie software[45] was used for quantification based on fragments per kilobase of transcript per million fragments mapped (FPKM) to estimate the gene expression level of each transcript[46]. Using the edge R package[47], genes with a fold change ≥ 2 and an FDR<0.01 were considered DEGs (differentially expressed genes)[48]. The false discovery rate (FDR) was calculated by adjusting the p value multiple times[49].

WGCNA Construction

Through the BMKCloud cloud platform (www.biocloud.net), a cotton salt tolerance coexpression network was established for 32,390 DEGs produced by ST and SS under salt stress and re-watering. In the scale-free weighted gene network, nodes corresponded to DEGs, and edges were determined by similar expression profiles of paired genes calculated through Pearson correlation. Therefore, an optimal soft threshold β= 26 was chosen to construct a network based on an adjacency matrix (R²>0.8). The topological overlap matrix was calculated through the adjacency matrix, and the dynamic tree cutting algorithm was used to segment the modules according to default parameter settings. A grouping matrix of 18 samples was used as a trait for specificity module identification. Cytoscape 3.9.1 software was used to visualize the coexpression networks.

qRT‒PCR Validation of the Transcriptome

To verify the Illumina sequencing results, RNA was extracted from SS and ST plants under salt stress conditions at 0 h, 48 h, and 48 h. Ten DEGs were randomly selected, and conserved regions of the sequence were identified via BLASTX and ORF finders in the NCBI. An online website (https://www.primer3plus.com) was utilized to design the qRT‒PCR primers (Table S2). Based on previous research[50], with GhUBQ7 as the internal reference, a two-step program was used to detect changes in gene expression using the ABI7500 Fast System (USA ABI Company). Each reaction was repeated three times.

Data Analysis

IBM SPSS 27 was used for data statistics and analysis. The sequencing results were analyzed through the BMKCloud cloud platform (www.biocloud. net).

Phenotypic observation of cotton seedlings under salt stress and re-watering

Cotton plants at the trefoil stage were treated with 200 mM NaCl solution. The growth of cotton plants under salt stress was observed at different time points (Fig.1). Under NaCl stress, the leaves and stems of the ST and SS plants gradually softened, and the cotyledons wilted severely at 48 h. Compared with those of the ST plants, the leaves and stems of the SS plants changed significantly, their cotyledons withered and fell at 48 h, and their true leaf margins were slightly charred. After 48 h of re-watering, ST growth was relieved, and the true SS leaves wilted.

Fig. 1 Growth of cotton plants under salt stress conditions at different time points.

Physiological Responses of Cotton Seedlings to Salt Stress and re-watering

Salt stress can disrupt the ion balance within plant cells. The generated ion toxins, osmotic pressure, and reactive oxygen subsequently affect the growth and development of cotton. As shown in Fig. 2, the malondialdehyde concentrations of the ST and SS plants significantly increased, and the chlorophyll content, superoxide dismutase activity and peroxidase activity decreased under NaCl treatment for 48 h, indicating that salt stress affected the normal growth and development of the cotton plants. The malondialdehyde concentrations in the ST and SS treatments increased by 36.07% and 64.61%, respectively, compared with that in the CK treatment, and after 48 h of re-watering, the malondialdehyde concentration in the ST treatment did not change, while the malondialdehyde concentration in the SS treatment increased by 11.54% compared with that in the CK treatment. This indicated that salt stress significantly affected the lipid peroxidation level and that re-watering had a greater mitigating effect on ST than on SS. The relative chlorophyll contents of the ST and SS plants were reduced by 10.29% and 13.89%, respectively, compared with those of the CK plants under salt stress and by 5.23% and 10.36%, respectively, compared with those of the CK plants after re-watering. This indicates that salt stress significantly inhibited chlorophyll synthesis in cotton and that re-watering also significantly improved chlorophyll synthesis in both ST and SS. Compared with those in the CK treatment, the superoxide dismutase activity and peroxidase activity in the ST treatment decreased by 3.06% and 12.98%, respectively, and after re-watering, they decreased by 0.36% and 12.51%, respectively. The superoxide dismutase activity and peroxidase activity in SS were significantly reduced by 27.5% and 13.89%, respectively, compared with those in CK and were reduced by 5.23% and 10.36%, respectively, compared with those in CK after re-watering under salt stress. Compared with those in the CK treatment, the stress in the CK treatment significantly decreased by 27.31% and 22.46%, respectively, and after re-watering, the stress significantly decreased by 39.79% and 36.67%, respectively. This indicated that the ability of ST to clear reactive oxygen species under salt stress was greater than that of SS and did not improve re-watering.

Fig.2 Physiological response of cotton seedlings to salt stress and re-watering.

Note: The same letters indicate no significant differences between treatments (P<0.05, LSD method).

Microstructures of Cotton Leaves under Salt Stress and re-watering

Salt stress not only affects the physiological and metabolic processes of plants but also causes changes in plant morphology, anatomical structure, and other aspects. According to the microstructure of the cotton leaves under salt stress and re-watering (Fig. 3), the ST and SS seedling slices were deeply stained, the microstructure was tightly arranged, the bulliform cells were shaped like single-layer irregular quadrilaterals and closely arranged under normal conditions, the bulliform cells were ovoid, the arrangement of palisade and sponge tissue cells was relatively loose, and the leaves were softened. After re-watering, the bulliform cells had a long egg shape, and the leaves were relatively flat, gradually returning to normal growth.

Analysis of the leaf epidermal structure revealed that under normal conditions, there was no significant difference in the epidermal structure of the leaves between the ST and SS cotton plants (Table S3). Under NaCl stress, the leaf thickness, palisade tissue thickness, and sponge tissue thickness of the ST and SS plants all decreased, and they relatively recovered after re-watering. After NaCl treatment, compared with those of the control, the leaf thickness, palisade tissue thickness, and sponge tissue thickness of the ST seedlings decreased by 16.17%, 13.92%, and 18.46%, respectively, without any significant difference; those of the SS decreased by 32.43%, 30.13%, and 41.10%, respectively. After re-watering, the leaf thickness, palisade tissue thickness, spongy tissue thickness and upper epidermis thickness of the ST cotton seedlings increased by 0.93%, 0.09%, 3.41% and 2.28%, respectively, and the leaf thickness, palisade tissue thickness and spongy tissue thickness of the SS plants significantly decreased by 28.60%, 28.71% and 32.53%, respectively, compared to those of the control plants.

Fig.3 Microstructure of cotton leaves under salt stress and re-watering.

Note: Upper, upper epidermis; Pt, palisade issue; St, spongy issue; Le, lower epidermis.

Transcriptome Sequencing Analysis of Cotton Seedlings under Salt Stress and re-watering

To explore key genes related to salt tolerance in cotton, this study sampled two cotton materials whose salt tolerance significantly differed under 200 mM NaCl stress at 0 h, 48 h, and 48 h of re-watering. Each treatment had three biological replicates. The 18 collected samples (3 time points × 2 varieties × 3 biological replicates) were used to construct 18 RNA-seq libraries, and Illumina HiSeq 4000 sequencing and analysis were performed. A total of 127.58 Gb of clean data were obtained, with a Q30 percentage of no less than 91.70% for all the samples. Sequence alignment was performed between the total reads of each sample and the reference genome (TM-1) of upland cotton. According to the alignment results, the alignment efficiency between the reads of each sample and the reference genome was between 94.06% and 96.60%, and the GC content of each sample exceeded 43.47%. These results demonstrated that the RNA-seq data in this study were of high quality and could be further analyzed (Table S4).

Based on the comparison results, 11,125 genes were discovered, of which 6,974 were functionally annotated. The normalized FPKM value was used to measure the expression level of each gene, and the Pearson correlation coefficient (PCC) was used to detect the correlation between all samples. The overall correlation between the three biological replicates of the two varieties at the same growth stage was high. Moreover, sample clustering exhibited good correlation between biological replicates in the same environment (Fig. S1A). To further confirm the correlation between ST and SS at different stages under salt stress and re-watering, principal component analysis was performed on the genes expressed as described above (Fig. S1B). These results indicated that the two cotton varieties with significant differences in salt tolerance have apparently diverse expression patterns in different environments. SS and ST exhibited consistency in three biological replicates in the same environment, indirectly verifying the reliability of the transcriptome data.

To confirm the reliability of the RNA-Seq results in this study, ten genes were randomly selected for qRT‒PCR (Table S2). The results were consistent with the expression trend of the transcriptome expression profile, proving that the transcriptome data were reliable for subsequent analysis (Fig. 4). In SS, 43,233, 40,970, and 42,529 genes were expressed in sequence, of which 36,890 genes were coexpressed. There were 43,593, 41,028, and 43,943 genes expressed in STs, respectively, of which 37,256 genes were coexpressed (Fig. 5).

Fig.4 qRT‒PCR validation of the RNA-Seq results.

Note: (A) qRT‒PCR results for ten genes. The relevant significance level (p value) has been added above each histogram. Ns indicates no significant impact at the p<0.05 level, while * indicates a significant impact at p<0.05. The black strip represents ST; the gray bar represents SS. (B) RNA-seq heatmap of ten genes.

Fig.5 (A) Venn diagram of gene expression in ST leaves; (B) Venn diagram of gene expression in SS leaves.

Analysis of DEG Expression between the Two Cotton Materials

To further analyze the differential mechanism between the two cotton materials, a total of 10,589 genes were screened, of which 5,960 were upregulated, including 136 under normal conditions, 2,151 under salt stress, and 3,673 under re-watering; 4,629 genes were downregulated, including 228 under normal conditions, 2,271 under salt stress, and 2,130 under re-watering (Fig. 6). As the growth period increased, the number of DEGs in the two cotton materials increased, indicating that these two cotton materials have distinct response mechanisms to salt stress and re-watering.

The DEGs between the two materials were compared against the GO database (Fig. 7). In terms of biological processes, DEGs were mainly enriched in metabolic processes, cellular processes, and single-organism processes. In terms of cell components, DEGs were enriched mainly in cell and cellular components, while in terms of molecular functions, DEGs were enriched mainly in binding and catalytic activities. Under normal conditions, a large number of genes were downregulated, while many genes were upregulated after re-watering. This fully demonstrates the adaptability of cotton to re-watering. Subsequently, KEGG enrichment analysis was performed on the DEGs. As shown in Fig. 8, DEGs of STs were significantly enriched in photosynthesis-antenna protein (ko00196), carbon fixation (ko00710) in photosynthetic organisms, and vitamin B6 metabolism (ko00750).

Fig. 6 DEGs between materials subjected to the same treatment.

(A) Histogram of DEGs between materials with the same treatment; (B) Venn diagram of DEGs between materials with the same treatment.

Fig.7 GO analysis of DEGs between materials subjected to the same treatment.

Fig.8KEGG analysis of DEGs between materials subjected to the same treatment.

(A) KEGG analysis of DEGs under normal conditions (ST-CK vs. SS-CK); (B) KEGG analysis of DEGs under salt stress (ST-NaCl vs. SS-NaCl); (C) KEGG analysis of DEGs under re-watering (ST-RW vs. SS-RW).

Expression analysis of DEGs under salt stress and re-watering

A fold change ≥ 2 and FDR<0.01 were adopted as screening criteria to obtain DEGs under salt stress and re-watering for further analysis of the differential mechanisms (Fig. 9). A total of 32,390 genes were screened. Under salt stress, 15,780 genes were screened in the ST, of which 7,996 DEGs were upregulated, and 7,784 DEGs were downregulated. Under re-watering, 2,454 genes were screened, including 659 upregulated genes and 1,795 downregulated genes. For SS under salt stress, 14,156 genes were screened. Among them, 6,925 DEGs were upregulated, and 7,231 DEGs were downregulated. Under re-watering, 9,390 genes were screened in SS, of which 4,666 DEGs were upregulated and 4,724 DEGs were downregulated. Under salt stress, the number of DEGs screened in ST was greater than that in SS. However, fewer DEGs were produced after re-watering in the ST treatment than in the SS treatment, which may be related to the greater recovery of the STs after re-watering.

The DEGs of the two materials under salt stress and re-watering were compared via the GO database (Fig. 10). In terms of biological processes, DEGs were mainly enriched in metabolic processes, cellular processes, and single organism processes. For cellular components, DEGs were mainly involved in cells, cellular components, and membranes. Regarding molecular functions, DEGs were mainly enriched in binding and catalytic activities.

DEGs annotated by KEGG were classified into multiple categories (Fig. 11). The response of cotton to salt stress and its adaptation to re-watering may be related to interactions such as photosynthesis (ko 00195), photosynthesis-antenna protein (ko 00196), plant hormone signal transduction (ko 04075), starch and sucrose metabolism (ko 00500), and porphyrin and chlorophyll metabolism (ko 00860). Additionally, STs respond to salt stress through pathways such as circadian rhythm-plant (ko 04712), carbon fixation (ko 00710) and carbon metabolism (ko 01200) pathways in photosynthetic organisms. The adaptability of STs to re-watering was regulated through pathways such as glyceride metabolism (ko 00561), the reciprocal transformation of pentose and glucuronate (ko 00040), circadian rhythm-plant (ko 04712), and phenylpropane biosynthesis (ko 00940). SSs resist salt stress through pathways such as fatty acid degradation (ko 00071); degradation of valine, leucine, and isoleucine (ko 00280); biosynthesis of brassinosteroid (ko 00905); and sphingolipid metabolism (ko 00600). The damage caused by salt stress was alleviated through plant‒pathogen interactions (ko 04626), the MAPK signaling pathway (ko 04016), and α-linolenic acid metabolism (ko 00592).

Fig. 9 DEGs between treatments.

(A) Histogram of DEGs between treatments; (B) Wayne plot of DEGs between treatments.

Fig. 10 GO analysis of DEGs between treatments.

Fig. 11 KEGG analysis of DEGs between treatments.

(A) KEGG analysis of DEGs in STs under salt stress (ST-CK vs. ST NaCl); (B) KEGG analysis of DEGs in STs under re-watering (ST-CK vs. ST-RW); (C) KEGG analysis of DEGs in SS under salt stress (SS-CK vs. SS-NaCl); (D) KEGG analysis of DEGs in SS under re-watering (SS-CK vs. SS-RW)

Effects of salt stress on genes related to photosynthesis and carbon metabolism in cotton

KEGG pathway analysis revealed enrichment of "carbon fixation in photosynthetic organisms" and "photosynthesis" pathways in cotton. The expression levels of genes encoding key enzymes involved in carbon fixation in STs and SS were suppressed under salt stress (Fig 12). Similarly, salt stress inhibited photosynthesis and reduced carbon assimilation in the ST and SS, which ultimately led to structural and functional damage to the cotton leaves. Moreover, the expression of most genes involved in photosynthesis and carbon metabolism was more affected by salt stress than by genotype, and the genes related to photosynthesis and carbon metabolism in STs and SS were suppressed under salt stress. After re-watering, more similar gene expression patterns were detected under salt stress and re-watering treatments. In particular, the expression of genes related to PSII, PSⅠ, FNR, Fd, LHCⅠ and LHCⅡ in the ST decreased in response to salt stress, and after re-watering, their expression levels increased to normal levels. After re-watering, the expression levels of related genes were still downregulated after SS re-watering.

Fig. 12 Expression of genes related to photosynthesis and carbon metabolism in cotton under salt stress and re-watering.

ST improved growth hormone, gibberellin and cytokinin signaling under salt stress and re-watering to promote cotton plant growth

Growth hormones, gibberellins and cytokinins control plant growth by promoting cell elongation or division, thereby increasing salt tolerance in plants under salt stress[51]. Furthermore, the growth hormone endocytic vector (AUX1) and gibberellin receptor (GID1) are required to cope with cell damage under salt stress, and the expression of cytokinin receptors and several Arabidopsis A-type response regulators is affected by salt treatment[39, 52]. In this study, under salt stress and re-watering treatment, the expression levels of 8 genes related to AUX1 in ST47 were greater than those in SS. There were 6 genes related to GID1 whose expression levels were elevated by salt stress, and these genes showed better recovery in STs with lower expression levels after re-watering, but SS still showed higher expression levels (Fig. 13). Four genes related to A-type response regulators in ST and SS showed low expression levels under normal conditions, and 2 genes were elevated under salt stress. After re-watering, the expression levels of these 2 genes in the STs decreased and recovered. However, these 2 genes of SS were still highly expressed. Our results suggest that ST coordinately regulates growth hormone, gibberellin and cytokinin signaling and promotes improved growth and recovery under salt stress.

Fig. 13Effects of salt stress and re-watering on the expression of growth hormone-, cytokinin- and gibberellin-related genes in cotton.

Response of plant circadian genes to salt stress and re-watering in cotton

Plant circadian rhythms and their response mechanisms to various abiotic stresses have been a hot topic in plant physiology and ecology[53]. There are many different models of biological clocks. A simple model of a plant biological clock consists of three circuits: CCA1, LHY and TOC1 (PRR1), which form the core circuit; PRR5/7/9, which forms the daytime circuit; and ELF3, ELF4, GI and LUX, which form the nighttime circuit[54]. In this study, KEGG pathway analysis revealed that ST cotton was enriched in the "plant circadian rhythm" pathway under salt stress and re-watering, and two TOC1 genes in ST and SS exhibited low expression levels under normal conditions, while the expression of ST-related genes increased under salt stress and decreased after re-watering, while that of SS decreased under both salt stress and re-watering (Fig 14). SS had lower gene expression levels in both the salt stress and re-watering treatments. Similarly, the expression of one GI and three PRR7 genes in both materials increased under salt stress and decreased after re-watering. There were 2 PRR9 genes in the ST, whose expression increased under salt stress and decreased after re-watering, and in the SS, whose expression decreased under both salt stress and re-watering.

MAPK signaling in response to salt stress

The MAPK cascade pathway plays an important role in environmental stress signaling via the MAPKKK-MAPKK-MAPK-mediated triple phosphorylation cascade to induce tolerance responses[55]. In this study, the majority of MAPK-related genes in ST and SS were altered by salt stress, and most of the genes in ST were restored to normal levels after re-watering, while most of the genes in SS were still activated to relatively high or low levels (Fig 15). The expression of the MEKK1, MEKK2, and MEK4/6 genes in both STs and SSs was induced by salt stress, and their expression was elevated. Interestingly, after re-watering, the expression of all genes related to ST decreased, and the expression of some genes related to SS decreased, while others maintained high expression.

Fig. 14Effects of salt stress and re-watering on the expression of genes related to biological clocks in cotton.

Fig. 15 Effects of salt stress and re-watering on MAPK signal transduction-related genes in cotton.

WGCNA of DEGs under Salt Stress and re-watering

To understand gene expression and re-watering and identify candidate genes for salt tolerance, WGCNA was used to construct a coexpression network for DEGs under salt stress and re-watering (Fig. 16). The expression matrix was imported. The dist function and hclust clustering were used to calculate the sample algorithm. The graph shows no outliers among the 18 samples. There were significant differences between ST and SS under the different treatments. ST and SS can be clearly distinguished under re-watering, which implies that the expression matrix has good specificity and can be used to effectively distinguish between ST and SS under different treatments. This study selected the optimal soft threshold of 26 to construct an infinitely close scale-free network of gene coexpression. Genes were divided into six modules. The gray module had the greatest correlation with SS re-watering (R=0.86 and p<0.0001).

By using the Cytohubba plugin in Cytoscape, the top five genes with the highest correlation were selected as the hub genes for the modules (Fig. 17). Five key hubs, namely, GH_A01G1528, GH_A08G2688, GH_D08G2683, GH_D01G1620, and GH_A10G0617, were screened from among the hub genes in the MEgray module (Table 1).

Fig. 16WGCNA of DEGs under salt stress and re-watering conditions.

Fig. 17 (A) Connection results related to Cytoscape imported by the gray module. (B) Filtering results for the Cytohubba plug-in.

Table 1. IDs and gene annotations of five key genes obtained from WGCNA.

Hub gene ID	Homologous gene ID in A.thaliana	Functional Annotation	Gene Name
GH_A01G1528	AT5G59310	Nonspecific lipid-transfer protein 4	LTP4
GH_A08G2688	AT5G57800	Protein ECERIFERUM 3	CER3
GH_D01G1620	AT4G38660	Nonspecific lipid-transfer protein 1	LTP1
GH_A10G0617	AT1g17710	Inorganic pyrophosphatase 2	PEPC1
GH_D08G2683	AT5G57800	Protein ECERIFERUM 3	CER3

Response of Cotton Leaves to Salt Stress and re-watering

Salt causes osmotic damage by constraining the water absorption of plants. Moreover, it leads to excessive ion content in plant cells, resulting in ion stress[56]. Like other plants, cotton has evolved a series of responses to salinity and other environmental pressures, including morphological, physiological, biochemical, and molecular processes. These processes can help plants avoid and tolerate stress or restore stress, enabling them to survive under abiotic stresses[57]. The rapid adaptation, physiological adaptation, and tolerance to external high salt stress of salt-tolerant materials may contribute to the differences between them and salt-sensitive materials[17]. After 48 h of NaCl treatment, the cotton seedling leaves were severely damaged, and the concentration of malondialdehyde in the leaves of the ST and SS seedlings significantly increased, while the chlorophyll content and superoxide dismutase activity apparently decreased. After re-watering, the ST and SS plants recovered to a certain extent, the concentration of malondialdehyde decreased, and the chlorophyll content, superoxide dismutase activity, and peroxidase activity increased. Usually, compared with salt-sensitive materials, salt-tolerant materials have greater salt resistance and faster recovery after re-watering[58].

Plant growth, metabolic mechanisms, morphology and anatomy are all regulated by salt stress[59]. Leaves are the center of photosynthesis in higher plants. When subjected to stress, the phenotype, physiology, and anatomical structure of plant leaves can respond in a timely manner[60]. Research on cotton Na+ segregation indicates that salt secretion from glandular hairs of upland cotton leaves is a specific manifestation of cotton salt tolerance [61]. The microstructural characteristics of leaves are an important aspect of plant adaptation to salt-alkaline stress. Under NaCl stress, the component cells of cotton leaves contract due to water loss, the thickness of the cross-section of leaves decreases, and cell morphology, such as palisade tissues, is affected[62]. In this study, under normal conditions, the microstructure of the cotton leaves was closely arranged. Bulliform cells were shaped like single-layer irregular quadrilaterals with a compact permutation. Under salt stress, the bulliform cells were ovoid, the arrangement of palisade and sponge tissue cells was relatively loose, and the leaves were softened. After re-watering, the bulliform cells had a long egg shape, and the leaves became flat and gradually returned to normal growth. Under normal conditions, there was no significant difference in the leaf epidermis structure between the ST and SS cotton plants, while under NaCl stress, the leaf thickness, palisade tissue thickness, and sponge tissue thickness of the ST and SS plants decreased. The plants recovered to a certain degree after re-watering.

Transcriptomic Analysis of the Response of Cotton Leaves to Salt Stress

re-watering is an effective means to restore the growth and physiological conditions of plants under stress[63]. This study compared the transcriptome changes of ST and SS under salt stress and re-watering conditions. Under salt stress, both ST and SS produced a large number of DEGs (15,780 and 14,156, respectively). ST mainly responds to salt stress through circadian rhythm-plant (ko 04712), carbon fixation (ko 00710) and carbon metabolism (ko 01200) pathways in photosynthetic organisms. SSs resist salt stress through pathways such as fatty acid degradation (ko 00071), valine, leucine, and isoleucine degradation (ko 00280), brassinosteroid biosynthesis (ko 00905), and sphingolipid metabolism (ko 00600). After re-watering, SS still produced a large number of DEGs (9,390), while the number of DEGs produced in ST significantly decreased (2,454), indicating that ST has better adaptability to salt stress than SS. Under re-watering, ST regulates its adaptability through pathways such as glyceride metabolism (ko 00561), the reciprocal transformation of pentose and glucuronate (ko 00040), circadian rhythm-plant (ko 04712), and phenylpropane biosynthesis (ko 00940). SS alleviates the damage caused by salt stress through plant‒pathogen interactions (ko 04626), MAPK signaling pathway–plant interactions (ko 04016), and α-linolenic acid metabolism (ko 00592).

Molecular mechanisms of the salt stress response in cotton

Salt stress can cause multiple injuries to plants, such as osmotic stress, ionic toxicity and oxidative damage, which in turn reduces photosynthesis and inhibits plant growth and development processes[64].

Osmotic stress reduces cell expansion, affects plant water use efficiency, and induces stomatal closure and disruption of photosynthetic pigments[65]. Stomatal closure reduces the amount of carbon dioxide available for fixation and reduces the activity of carbon dioxide-fixing enzymes under salt stress[64]. In this study, the KEGG pathways of both ST and SS were significantly enriched for photosynthesis (ko00195) and photosynthesis-antenna proteins (ko00196), and related genes were repressed under salt stress, but the gene expression of ST under complex water conditions was greater than that of SS. Inhibition of photosynthesis by salt stress results in insufficient accumulation of carbon assimilation to maintain normal growth, thus affecting normal plant growth and development[66]. re-watering improves photosynthesis in salt-tolerant materials, which in turn increases carbohydrate levels.

Plant growth and development need to maintain low levels of Na⁺, and excessive accumulation may lead to physiological and metabolic disorders in the plant body and interfere with ionic balance, thus inhibiting plant growth and reducing yield[67]. Plants mainly achieve salt tolerance by limiting Na⁺ absorption, Na⁺ efflux and Na⁺ segregation in vacuoles[68]. The salt-oversensitive (SOS) pathway is crucial in this regulatory process, and four major components have been identified: SOS1 (PM Na⁺/H⁺ reverse transporter), SOS2 (protein kinase), SOS3 (calcium-binding protein), and SCaBP8 (SOS3-like calcium-binding protein 8)[69]. Under salt stress, the complex of GI and SOS2 kinase can be cleaved by the 26S proteasome, and GI is released from the SOS2 system, which facilitates the interaction with Na⁺ receptors on SOS3 to activate SOS1; Na⁺ is transported out of the cell, and plant salt tolerance develops[70].

Receptors (receptor protein kinases, RLKs) in roots recognize salt signals and trigger transient increases in calcium (Ca²⁺), ROS and phytohormones (including growth hormones, cytokinins, gibberellins and abscisic acid, among others) when cotton plants are subjected to high salt conditions under salt stress[71]. Downstream of these second messengers is intracellular phosphorylation, such as the calcium-dependent protein kinase (CDPK) and mitogen-activated protein kinase (MAPK) cascades. In this study, DEGs under ST and SS salt stress with re-watering were also enriched in phytohormone signaling and the MAPK signaling pathway-plant pathway. In addition, there was a better recovery of gene expression in the ST treatment under re-watering. This suggests that re-watering improved the ability of ST to recognize salt signals and acted on intracellular phosphorylation, which in turn improved plant growth.

Identification of Salt Tolerance-Related Coexpression Modules in Cotton Leaves via WGCNA

WGCNA is a bioinformatics analysis method based on large amounts of transcriptome sample data. It assumes that the gene network follows a scale-free distribution, clusters genes with similar expression patterns into different modules, analyzes correlations between the modules and specific traits or phenotypes, and constructs a coexpression regulatory network based on gene clustering and association analysis results. Genes located at the center of the regulatory network are referred to as hub genes, which are usually key regulatory genes and are worthy of in-depth exploration and analysis[72].

Our study used WGCNA to enrich a gray coexpression module associated with cotton restoration under salt stress. By screening the gray module, several key genes were identified. GH_A01G1528 (LTP4, lipid transfer protein) and GH_D01G1620 (LTP1, lipid transfer protein) are essential active proteins involved in plant life activities, accounting for 4% of cell soluble proteins[73]. LTPs can respond to low temperature, drought, salt stress, infections by bacterial and fungal pathogens, and environmental changes in signaling molecules, such as abscisic acid (ABA), salicylic acid (SA), and ethylene[74-76]. Combining transcription analysis of Arabidopsis wild-type and tdr1 mutant plants under NaCl treatment with yeast one-hybrid experiments, it can be seen that LTP4 may serve as a direct target gene for TDR1, mediating the regulation of TDR1 in plant salt tolerance[77]. As a positive regulatory factor, NtLTP4 participates in the response of plants to abiotic stresses. Under high salt and drought stress conditions, compared with those in the wild-type control group, the NtLTP4-overexpressing strains exhibited extremely strong tolerance, faster seed germination, longer seedling roots, and slower water loss from leaves[78]. In high-salt environments, the growth of NtLTP4 transgenic potato lines is greater than that of wild-type potato plants, and the greater the expression level of NtLTP4 is, the greater the salt tolerance of potato plants[79]. GH_A08G2688 (CER3) is an important gene involved in the biosynthesis of long-chain alkanes[80-82]. The expression of BnCER3 in Brassica napus is significantly downregulated under the induction of MeJA and ACC[82]. GH_A10G0617 (PEPC1) is an important enzyme in plants that regulates carbon flow through the TCA cycle and controls protein and oil biosynthesis[83]. The expression of PEPC1 (1A and 1D) in cotton is induced by cold and salt stresses[84]. Overall, these genes may play a critical role in the response of plants to salt stress. However, further research is needed to reveal their specific mechanisms of action.

In summary, the present study systematically analyzed the differences in the response of different salt-tolerant cotton plants to salt stress at the physiological, biochemical, microstructural and transcriptomic levels. Under salt stress, the cotton malondialdehyde content increased, and the chlorophyll content, superoxide dismutase activity and peroxidase activity decreased; after re-watering, both cotton materials recovered somewhat, and ST performed significantly better than did SS. Similarly, leaf microstructural observations revealed that salt stress induced structural changes in cells and tissues; after re-watering, the STs exhibited improved recovery. By comparing the transcriptome data of ST and SS, 15780/14156 and 2454/9390 DEGs related to salt tolerance were identified at 48 h NaCl treatment and 48 h RW treatment, respectively. GO and KEGG pathway enrichment analyses revealed a variety of organismal responses to salt stress, including photosynthesis (ko 00195), photosynthesis-antenna protein (ko 00196), plant hormone signal transduction (ko 04075), starch and sucrose metabolism (ko 00500), and porphyrin and chlorophyll metabolism (ko 00860), among other interactions. WGCNA revealed enriched gray coexpression modules related to the recovery of cotton plants under salt stress, and screening of the pivotal genes in the gray module revealed five critical hubs, namely, GH_A01G1528, GH_A08G2688, GH_D08G2683, GH_D01G1620 and GH_A10G0617.

Author contributions

Kang Zhao: Writing – original draft. Tao Yang: Methodology. Bo Pang: Methodology. Honggang Wang: Data curation. Zhining Yang: Methodology. Weiwei Liang: Writing – review & editing. Cun Rui: Writing – review & editing. Wengwei Gao: Writing – review & editing, supervision, funding acquisition.All authors read and approved the fnal manuscript.

Funding

This study was supported by grants from the Chinese National Natural Science Foundation (31771885) and the Application Technology Research and Demonstration Promotion of National Key Research and Development Program of China (2021YFD1900802, 2016FYC0501407).

Data availability

RNA-seq raw data were also deposited under these NCBI accessions of PRJNA1133963.

Ethics approval and consent to participate

All the cotton materials were collected from College of Agriculture, Xinjiang Agricultural University，which are publicly and avail-able for non-commercial purpose. All experimental studies on plants were

complied with relevant institutional, national, and international guidelines and legislation.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Response of different cotton genotypes to salt stress and rewatering

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