Time-course RNA-sequencing and Co-expression Modules Revealed a Critical Salt Response Regulatory Network in Apple

in Journal of the American Society for Horticultural Science
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Xin HuangCollege of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, Hebei, China

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Meiling ZhangInstitute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100093, China

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Liping WangCollege of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, Hebei, China

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Xuyao ZhangCollege of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, Hebei, China

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Ruigang WuCollege of Landscape and Ecological Engineering, Hebei University of Engineering, Handan 056038, Hebei, China

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Fei ShenBeijing Agro-biotechnology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China

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As one of the most important fruit tree crops, apple (Malus ×domestica), is faced with the serious impact of soil salinization. However, the underlying genetic and regulatory network remains elusive. Here, we adopted time-course RNA sequencing to decipher the genetic basis and regulatory module of apple in response to salt stress. Among a series of intense changes in genes at each time point, the critical genes in the mitogen-activated protein kinase signaling pathway were highly consistent with the duration of the stress treatment. Moreover, Salt Overly Sensitive 1 (SOS1) genes were identified and predicted to play important roles in the response process. We constructed coexpression modules and explored modules significantly associated with stress. SOS genes were identified in the hub genes, suggesting a critical role. Interestingly, transcription factors were also identified and predicted to cointeract with SOS genes in the hub genes of the coexpression module [e.g., HB7 (MD01G1226600), WRKY33 (MD12G1181000), and ERF106 (MD07G1248700)]. Collectively, our exploration and findings provide a reference and data resource for the study of genetic and salt regulatory networks in apple.

Abstract

As one of the most important fruit tree crops, apple (Malus ×domestica), is faced with the serious impact of soil salinization. However, the underlying genetic and regulatory network remains elusive. Here, we adopted time-course RNA sequencing to decipher the genetic basis and regulatory module of apple in response to salt stress. Among a series of intense changes in genes at each time point, the critical genes in the mitogen-activated protein kinase signaling pathway were highly consistent with the duration of the stress treatment. Moreover, Salt Overly Sensitive 1 (SOS1) genes were identified and predicted to play important roles in the response process. We constructed coexpression modules and explored modules significantly associated with stress. SOS genes were identified in the hub genes, suggesting a critical role. Interestingly, transcription factors were also identified and predicted to cointeract with SOS genes in the hub genes of the coexpression module [e.g., HB7 (MD01G1226600), WRKY33 (MD12G1181000), and ERF106 (MD07G1248700)]. Collectively, our exploration and findings provide a reference and data resource for the study of genetic and salt regulatory networks in apple.

Soil salinization is a serious global problem that affects agricultural development and could lead to osmotic stress, ion toxicity, ion imbalance, and nutrient deficiency for plants. For example, the root hairs of plants become shorter and their absorption capacity decreases significantly with increased salinity. Moreover, chlorophyll and carotenoids in plants decrease under long-term salt stress conditions, which results in a lower photosynthetic rate, and the plant leaves become wilted and turn yellow, ultimately leading to plant death (Kumari et al. 2015). High salt concentrations can also inhibit the germination of plant seeds. Hence, research on the salt tolerance of plants has gradually become a top priority, which, along with related mechanisms, has been explored in several plants, including Glycine max (Osman et al. 2021), Stevia rebaudiana (Forouzi et al. 2020), Zea mays (Noman et al. 2021), Vitis vinifera (Bari et al. 2021), and Punica granatum (Calzone et al. 2021). In recent years, several investigations have shown that various physiological activities, metabolic pathways, and gene networks contribute to salt tolerance in plants, including the activation of antioxidant enzymes, the induction and regulation of plant hormones, as well as the regulation of osmotic pressure, ion excretion, and other mechanisms (Al Hassan et al. 2017; Gharbi et al. 2017; Rahman et al. 2017). Moreover, genes verified to be related to salt resistance, including genes encoding transcription factors (Tang et al. 2018), Na+/H+ antiporter genes (Rauf et al. 2014), and genes encoding antioxidant enzymes (Mohamed et al. 2015), have been used by modern biotechnology to enhance the salt tolerance of plants. Nevertheless, the current knowledge on the effects of salt stress in plants is still relatively limited, and many underlying cellular and molecular mechanisms remain unknown.

Apple (Malus ×domestica) is an edible member of the Rosaceae family and is considered one of the top four fruits in the world (Xu et al. 2016). ‘Golden Delicious’ is a well-known apple cultivar that is widely planted in Europe, the United States, and China. In 2010, the whole genome of ‘Golden Delicious’ was sequenced (Velasco et al. 2010), and since that time, it has been considered as a standard for apple gene family prediction and bioinformatics analysis. The full understanding of the gene regulatory network of apple in response to abiotic stress remains poorly known, and more in-depth physiological and molecular studies are needed to reveal the mechanisms of apple adaptation to salinity.

Time-course gene expression profiling is a valuable method to investigate the complete gene regulatory network with respect to salt resistance. Here, to decipher the genetic basis and regulatory module of apple in response to the salt stress, we adopted time-course RNA sequencing. The findings of this study are expected to help explain the metabolic regulation mechanisms of fruit trees in response to salt stress and consequently provide a theoretical basis for selecting genes related to salt tolerance and for molecular resistance breeding of salt-tolerant apple in the future.

Materials and Methods

Plant materials and growth conditions.

In vitro tissue cultures of ‘Golden Delicious’ were subcultured on Murashige and Skoog solid medium with 0.5 mg·L−1 benzylaminopurine and 0.1 mg·L−1 naphthylacetate at 25 °C under a 16/8-h light/dark photoperiod. Subsequently, 1-month-old apple tissue culture materials were treated with salt (200 mM NaCl) stress in the same sub-proliferation medium formulation, and leaves were collected at 0, 1, 6, 12, and 24 h (Zhou et al. 2021). At each time point, three biological replicates were taken, quickly frozen in liquid nitrogen, and stored in the refrigerator at –80 °C.

mRNA sequencing (RNA-seq) library preparation and sequencing.

We constructed the RNA library as previously described. Briefly, 5 μg of total RNA from each sample was used to isolate mRNA and prepare an RNA-seq library using the NEBNext Poly(A) mRNA Magnetic Isolation Module and NEBNext Ultra Directional RNA Library Prep Kit for Illumina (New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocols. The cDNA library was sequenced from both the 5′ and 3′ ends using a sequencing instrument (HiSeq; Illumina, Inc., San Diego, CA, USA), according to the manufacturer’s instructions, in which 150-bp paired-end reads were obtained.

RNA-seq data processing, transcript assembly, and expression analysis.

RNA-Seq data were downloaded from the National Center of Biotechnology Information (NCBI, Bethesda, MD, USA) database PRJNA908220 (Griffin and Griffin 1995). All raw reads were processed using FastQC (Andrews 2010) to check the read quality and adapter contamination. The raw reads were then processed using quality control of next-generation sequencing (Patel and Jain 2012) to remove low-quality reads and adapters. We mapped the clean reads to the apple reference genome using the HISAT2 (Kim et al. 2015) software with default parameters. Transcript assembly and quantification were conducted using StringTie (Pertea et al. 2015). Differentially expressed genes were detected using the DESeq2 software (Love et al. 2014) with default parameters (P < 0.05 and |log2FC| ≥1).

Principal component analysis.

Principal component analysis was performed using the expression data of all genes in all samples. The R (R Foundation for Statistical Computing, Vienna, Austria) function princomp (Bolar 2019) was adopted to extract the principal components. The results were visualized using the R package factoMineR (Lê et al. 2008).

Gene ontology and pathway enrichment analyses.

We determined differential genes in the region using the R package clusterProfiler ver. 4.0 (Wu et al. 2021). Gene ontology (GO) enrichment analysis was performed, and gene length deviation was accurately corrected by the software. GO terms with a modified P < 0.05 were considered significantly enriched. The R package clusterProfiler ver. 4.0 was used to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Enrichment Analysis. Finally, TBtools (Chen et al. 2020) software was used to complete gene classification and visualization of metabolic and biological stress pathways.

Identification of coexpression modules and visualization of hub genes.

The weighted gene coexpression network analysis (WGCNA) package in R [ver. 1.29 (Langfelder and Horvath 2008)] was employed to construct coexpression networks and test the association with the expression of Salt Overly Sensitive (SOS) gene family and treatment time (Zhang and Horvath 2005). Sequences with an average fragments per kilobase of transcript per million mapped reads (FPKM) >1 from three replicates were used for the WGCNA. Modules were obtained using the automatic network construction function blockwise with default settings, except that the soft power was 11. The power used was considered as a soft threshold of the correlation matrix. The networks were visualized using Cytoscape ver. 2.0.0 (Shannon et al. 2003).

Results

Transcriptome profile of apple tissue culture plantlets upon exposure to salt stress.

To investigate apple transcriptome dynamics in response to salt stress, leave samples of apple tissue cultured in vitro under exposure to NaCl were collected at different time points (1–24 h) and evaluated by RNA-seq. Overall, a total of 475.5 million high-quality paired-end reads (average ∼17.6 million for each sample) were obtained after removing low-quality reads and adaptors, of which 94.46% of the sequences were aligned to the apple genome (Fig. 1A, Supplemental Table 1). Further analysis of the gene expression profile revealed that the genes could be divided into 13 groups (Fig. 1B and C), and the overall trend of each group was about the same. Most genes were in the range of [0, 1] FPKM and accounted for ∼40% of the transcriptome, whereas only a few genes (∼5%) were in the [50, infinity] FPKM range (Fig. 1A, Supplemental Table 2). Pearson correlation analysis and PCA confirmed a good correlation between the biological replicates (Fig. 1B and D).

Fig. 1.
Fig. 1.

Expression profiles of RNA sequencing data at 0, 1, 6, 12, and 24 h under salt stress (200 mM NaCl) in apple (Malus ×domestica). (A) Percentage distribution of expression frequency of transcriptome-sequenced genes in samples at different time points; CK represents control (0 h), NaCl_1–24 h represent different treatment times under salt stress. The ranges of fragments per kilobase of transcript per million mapped reads (FPKM) was divided into four ranges from 0 to infinity (inf). (B) Correlation of expression levels between different samples. (C) Principal component analysis of different samples. (D) Venn diagram of the comparison between CK and salt stress at different time points.

Citation: Journal of the American Society for Horticultural Science 148, 2; 10.21273/JASHS05270-22

Differential gene expression profile of apple tissue culture plantlets upon exposure to salt stress.

Comparative analysis of the expression of all individual genes upon increased exposure to salty conditions revealed 27,013 differentially expressed genes (DEGs) compared with the control [CK (0 h)], of which 5803, 4163, 8926, and 8121 DEGs were detected at 1, 6, 12, and 24 h, respectively. The highest number of up- and down-regulated genes was observed after 12 h of incubation with NaCl (3612 and 5314, respectively), whereas the lowest number was noted after 6 h (1398 and 276, respectively). A total of 1501 DEGs were found to vary at all time points; genes were found to be differently expressed only at 1, 6, 12, and 24 h (Fig. 1C).

Genes involved in signal transduction in apple tissue culture plantlets upon exposure to salt stress.

GO enrichment analysis was performed using the 6723 common and independent DEGs identified. The results showed that these genes played an important role in signal transduction and the response to abiotic stress (Fig. 2A). Given the importance of the response to stress when plants were subjected to salt stress, a heatmap of the differential genes enriched in response to stress was constructed. The responding genes had clearly different expression patterns depending on the time of exposure to the stressor, with the number of highly expressed genes being higher at 0 and 1 h, and at 12 and 24 h. Notably, the levels of the genes that were more expressed at 0 h gradually decreased as the salt stress increased. After 1 h of exposure, a fast response was observed with an almost completely opposite response in gene expression compared with that at 0 h. Moreover, at 12 and 24 h, the more expressed genes were those that were less expressed before salt stress (Fig. 2C).

Fig. 2.
Fig. 2.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the differentially identified genes among the groups: CK represents control (0 h), NaCl_1–24 h represent different treatment times under salt stress (200 mM NaCl). (A) GO enrichment analysis. (B) KEGG enrichment analysis. (C) Heatmap of differentially expressed genes (DEGs) gene expression enriched in GO term 0006950GO response to stress. (D) Heatmap of DEGs gene expression enriched into GO term 0007165 signal transduction.

Citation: Journal of the American Society for Horticultural Science 148, 2; 10.21273/JASHS05270-22

KEGG enrichment analysis of the same common and independent DEGs further revealed that they were mainly involved in 30 signaling pathways. These included, for example, the signaling pathways of plant hormones, the pathways of carbohydrate metabolism, or the pathways of processing environmental information (Fig. 2B). Numerous DEGs were found to be enriched in the mitogen-activated protein kinase (MAPK) signaling pathway in plants. Consistent with the GO data, heatmap analysis of the KEGG results also showed a rapid response to salt stress of apple. The expression of some genes clearly increased rapidly at 1 h and decreased rapidly within 6–24 h. The expression of some genes was high at 0 h but decreased rapidly with increasing salt stress. Among them, the expression level of some genes was low in the first 0 to 6 h and increased with time within 12 to 24 h. Taken together, these results demonstrate that salt stress effectively promotes significant molecular and cellular changes that enable apple to cope with these specific environmental conditions.

Changes in gene expression in signaling pathways with the timing of salt stress.

Consistent with the observed enrichment of the MAPK signaling pathway upon salt stress exposure, we found that the expression of some PYL (MD06G1034000, MD08G1043500, and MD07G1147700), MPK3 (MD15G1147300 and MD11G1121500), and PP2C (MD01G1139200, MD07G1203700, and MD03G1085400) genes were increased after 6 and 12 h, and then decreased. Among them, the expression of MKK3 (MD09G1027900), ABF (MD05G1082000), PYL (MD07G1286000 and MD01G1199800), PP2C (MD07G1291000 and MD01G1220800), and SnRK2 (MD02G1166500) was found to increase with increasing salt stress duration, whereas that of MAPKKK17/18 (MD17G1098800 and MD09G1111000) and MPK7 (MD15G1253700) initially increased and then decreased (Fig. 3A). In addition, SOS1 expression decreased upon salt exposure, whereas that of SOS2 and SOS3 gradually increased with time (Fig. 3B).

Fig. 3.
Fig. 3.

Identification of differentially expressed genes (DEGs) associated with Salt Overly Sensitive (SOS) family by weighted gene coexpression network analysis [WGCNA (Langfelder and Horvath 2008)]. (A) mRNA sequencing was used to analyze the expression of the mitogen-activated protein kinase (MAPK) signaling pathway genes mediated by abscisic acid (ABA)-dependent or independent pathway at different time periods under salt stress. The function of ABA is mediated by its receptors that are a group of proteins termed regulatory component of ABA receptor (RCAR)/pyrabactin resistance 1 (PYR1)/pyrabactin resistance-like (PYL). The RCAR-protein phosphate 2C (PP2C)-SNF1-related protein kinase 2 (SnRK2) regulatory modules have been defined as the core components in ABA signaling. SnRK2s can directly phosphorylate ABA responsive element binding protein/ABRE binding factors (AREB/ABF). A typical MAPK cascade consists of at least three sequentially acting serine/threonine kinases, a MAPK kinase kinase (MAPKKK/MEKK), a MAPK kinase (MAPKK/MKK) and finally, the MAPK itself, with each phosphorylating, and hence activating, the next kinase in the cascade. (B) mRNA sequencing was used to analyze the expression of SOS signaling pathway genes at different time periods under salt stress. SOS3-like calcium-binding protein 8 (SCABP8) has been implicated in the SOS pathway. (C) Hierarchical clustering tree and module-sample relationships. The module with the highest correlation between SOS gene expression, treatment time, and gene expression was indicated by red underlining of the module name.

Citation: Journal of the American Society for Horticultural Science 148, 2; 10.21273/JASHS05270-22

Construction of coexpression modules and selection of important modules.

Next, based on alignment results between Arabidopsis thaliana and apple genomes, the role of SOS1, SOS2, and SOS3 on the regulation of salt tolerance mechanisms in plants was further explored by WGCNA, which allows to identifying candidate hub genes associated with specific functions or traits. A total of 8000 DEGs were included in the analysis, and 10 modules were revealed (Fig. 3C, Supplemental Table 2). We found that the maximum number of genes in modules blue (MEblue) and modules turquoise (MEturquoise) in these 10 modules was 2018 and 2191, respectively. The smallest of these modules was modules gray (MEgray) with only six genes.

In particular, genes in the MEred (highest correlation coefficient was 0.92), MEblue (highest correlation coefficient was 0.77), and MEturquoise (highest correlation coefficient was 0.94) modules were strongly correlated with the expression of SOS family genes (Fig. 3C). GO analysis of MEred, MEblue, and MEturquoise was used to determine the functions associated with their genes (Fig. 4). In particular, MEred genes contributed to response to a stimulus, regulation of a biological process, signaling, and biological regulation and other functions (Fig. 4A). Similarly, MEblue genes also contributed to response to a stimulus and signaling (Fig. 4B). In addition to regulation of a biological process and other functions, the MEturquoise genes were also involved in response to salt stress, response to ethylene, positive regulation of response to a stimulus, response to reactive oxygen species, among other activities (Fig. 4C). The expression of some genes in the three modules was found to be high at 0 h and to then decrease with NaCl exposure time, whereas that of some genes gradually increased with time, and that of others increased first and then decreased (Fig. 5).

Fig. 4.
Fig. 4.

Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) gene in three modules (ME): (A) MEred, (B) MEblue, and (C) MEturquoise.

Citation: Journal of the American Society for Horticultural Science 148, 2; 10.21273/JASHS05270-22

Fig. 5.
Fig. 5.

Network analysis of transcription factors (TFs) in the three modules (ME): (A) MEblue, (B) MEred, and (C) Meturquoise.

Citation: Journal of the American Society for Horticultural Science 148, 2; 10.21273/JASHS05270-22

Identification of hub genes associated with salt stress response in apple.

Hub genes were defined as genes with a highest connectivity in each module (Zhang and Horvath 2005). Many of the DEGs identified in the MEred, MEblue, and MEturquoise modules were annotated as transcription factors, including HD-zip, ERF, and WRKY transcription factors. On the basis of the correlation network of hub genes and their expression patterns, seven transcription factors from the three modules were selected as being of particular interest: homeobox-leucine zipper protein ATHB-7 (MD01G1226600), WRKY33 (MD12G1181000), NAC47 (MD12G1000800), nuclear transcription factor Y subunit A-1 (MD11G1192400), homeobox-leucine zipper protein GLABRA 2 (MD17G1191000), ethylene-responsive transcription factor ERF106 (MD07G1248700), and homeobox-leucine zipper protein HAT5 (MD06G1187600) (Fig. 6).

Fig. 6.
Fig. 6.

Gene expression calorigram for three modules (ME): (A) MEblue, (B) MEred, and (C) Meturquoise.

Citation: Journal of the American Society for Horticultural Science 148, 2; 10.21273/JASHS05270-22

Discussion

Salt stress has serious effects on plant growth and development (Nutan et al. 2020). Inadequate fertilization and irrigation have exacerbated secondary salt damage and affected vegetative growth, reproductive development, and fruit yield and quality, resulting in significant economic losses. Therefore, elucidating the molecular mechanisms underlying salt tolerance in apple can help design selection and breeding protocols for salt-tolerant cultivars.

In this study, gene expression analysis of apple tissue samples revealed that exposure to salt stress induces rapid and significant molecular changes after 1, 6, and 12 h (compared with 0 h), which then tend to stabilize after longer exposure time [12 h vs. 24 h (Fig. 1)]. Further analysis of DEGs showed that there were fewer differentially expressed genes in the group with short-term salt treatment than in the group with long-term salt treatment. These results suggest that only few genes are involved in the first response to salt stress, whereas after 12 h of exposure, more genes began to respond. These findings were consistent with previous data obtained in Brassica napus (Long et al. 2015). Moreover, a detailed analysis of DEGs identified upon salt exposure revealed that many of these genes were involved in signal transduction, catalytic activity, and response to stress in apple. Although significantly enriched GO terms and KEGG pathways might slightly differ between plants, our results are similar to previous findings for Raphanus sativus roots (Zhang et al. 2022a).

To adapt to salt stress, plants rely mainly on signals and pathways that reestablish cellular ionic, osmotic, and reactive oxygen species homeostasis (Lei et al. 2020). Over the past 2 decades, genetic and biochemical analyses have revealed several core stress signaling pathways that participate in salt resistance (Gong et al. 2020). In particular, the SOS signaling pathway is known to play a key role in maintaining ionic homeostasis by extruding sodium ions into the apoplast (Rolly et al. 2020). Moreover, MAPK signaling cascade mediates ionic, osmotic, and reactive oxygen species homeostasis, and the sucrose nonfermenting 1-related protein kinase 2 (SnRK2) contributes to osmotic homeostasis regulation (Zhang et al. 2022a). Herein, we found that many regulatory genes involved in the SOS signaling pathway had the same expression trend as that reported in Zea mays (Cao et al. 2022), which further demonstrates the importance of this pathway to salt stress response in plants. On the basis of the results of WGCNA, the three modules MEblue, MEred, and MEturquoise were found to be highly correlated with the expression of SOS genes and treatment time, and GO enrichment analysis of the three modules revealed that their functions were mainly enriched in response to salt stress and signaling. This also further indicated that the genes in the three modules might play an important role in salt stress response. Noteworthily, HB7, HAT5, WRKY33, NAC047, NFYA1, GL2, and ERF106 were found to be highly relevant SOS-related transcription factors. It has been confirmed that the homeobox leucine zipper protein ATHB-7 can enhance plant salt tolerance by inducing overexpression of the transcription factor HB7 in Mesembryanthemum crystallinum (Pruthvi et al. 2014). In turn, McHB7 can enhance photosynthesis by regulating metabolites (e.g., pyruvate) and proteins (e.g., citrate synthase), increasing leaf chlorophyll content and affecting the tricarboxylic-acid cycle. In addition, McHB7 can regulate the expression of proteins related with stress (e.g., superoxide dismutase, dehydroascorbate reductase, and pyrroline-5-carboxylate synthase B) to eliminate reactive oxygen species and increase the salt tolerance of plants (Zhang et al. 2022b). The question of salt tolerance was also raised in an earlier report on Populus nigra HB7 (Calzone et al. 2021). Overexpression of ZmWRKY33, NFYA1, or HAT5 in A. thaliana was also shown to improve salt stress tolerance in transgenic plants (Li et al. 2013a, 2013b; Trivellini et al. 2016). Furthermore, NAC047 was identified in apple and confirmed to contribute to salt stress tolerance and promote ethylene release (An et al. 2018). It has been previously reported that use of salicylic acid can increase the expression of the homeobox leucine zipper protein GLABRA2, which in turn regulates root hair differentiation and growth, thereby improving salt tolerance (Miao et al. 2020). The ethylene-responsive transcription factor ERF106 was also reported to interact with MYB63 in apple to enhance salt tolerance (Yu et al. 2020).

Conclusions

Using in-depth time-course transcriptome sequence analysis, we found several hypothetical transcription factors (such as WRKY, NAC, and HDZIP), whose functions have already been implicated in the regulation of salt stress in other species. We suggest that these genes may have played an important role in the response of apple to salt stress. However, there are still limitations of our research, and although some genes have been identified, there remain deficiencies in testing their function. Future studies should focus on examining the function of these genes.

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    • Crossref
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  • Miao, YX, Luo, XY, Gao, XX, Wang, WJ, Li, B & Hou, LP. 2020 Exogenous salicylic acid alleviates salt stress by improving leaf photosynthesis and root system architecture in cucumber seedlings Scientia Hortic. 272 109577 https://doi.org/10.1016/j.scienta.2020.109577

    • Crossref
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  • Mohamed, E, Matsuda, R, El-Khatib, AA, Takechi, K, Takano, H & Takio, S. 2015 Characterization of the superoxide dismutase genes of the halophyte Suaeda maritima in Japan and Egypt Plant Cell Rep. 34 12 2099 2110 https://doi.org/10.1007/s00299-015-1854-1

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  • Noman, M, Ahmed, T, Shahid, M, Niazi, MBK, Qasim, M, Kouadri, F, Abdulmajeed, AM, Alghanem, SM, Ahmad, N, Zafar, M & Ali, S. 2021 Biogenic copper nanoparticles produced by using the Klebsiella pneumoniae strain NST2 curtailed salt stress effects in maize by modulating the cellular oxidative repair mechanisms Ecotoxicol Environ Saf. 217 112264 https://doi.org/10.1016/j.ecoenv.2021.112264

    • Crossref
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  • Nutan, KK, Singla-Pareek, SL & Pareek, A. 2020 The Saltol QTL-localized transcription factor OsGATA8 plays an important role in stress tolerance and seed development in Arabidopsis and rice J Exp Biol. 71 2 684 698 https://doi.org/10.1093/jxb/erz368

    • Search Google Scholar
    • Export Citation
  • Osman, MS, Badawy, AA, Osman, AI & Abdel Latef, AA. 2021 Ameliorative impact of an extract of the halophyte Arthrocnemum macrostachyum on growth and biochemical parameters of soybean under salinity stress J Plant Growth Regul. 40 3 1245 1256 https://doi.org/10.1007/s00344-020-10185-2

    • Crossref
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    • Export Citation
  • Patel, RK & Jain, M. 2012 NGS QC toolkit: A toolkit for quality control of next generation sequencing data PLoS One. 7 2 e30619 https://doi.org/10.1371/journal.pone.0030619

    • Crossref
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  • Pertea, M, Pertea, GM, Antonescu, CM, Chang, TC, Mendell, JT & Salzberg, SL. 2015 StringTie enables improved reconstruction of a transcriptome from RNA-seq reads Nat Biotechnol. 33 3 290 295 https://doi.org/10.1038/nbt.3122

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  • Rahman, MM, Rahman, MA, Miah, MG, Saha, SR, Karim, M & Mostofa, MG. 2017 Mechanistic insight into salt tolerance of Acacia auriculiformis: The importance of ion selectivity, osmoprotection, tissue tolerance, and Na+ exclusion Front Plant Sci. 8 155 https://doi.org/10.3389/fpls.2017.00155

    • Search Google Scholar
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  • Rauf, M, Shahzad, K, Ali, R, Ahmad, M, Habib, I, Mansoor, S, Berkowitz, GA & Saeed, NA. 2014 Cloning and characterization of Na+/H+ antiporter (LfNHX1) gene from a halophyte grass Leptochloa fusca for drought and salt tolerance Mol Biol Rep. 41 3 1669 1682 https://doi.org/10.1007/s11033-013-3015-3

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  • Rolly, NK, Imran, QM, Lee, I & Yun, BW. 2020 Salinity stress-mediated suppression of expression of salt overly sensitive signaling pathway genes suggests negative regulation by AtbZIP62 transcription factor in Arabidopsis thaliana Int J Mol Sci. 21 5 1726 https://doi.org/10.3390/ijms21051726

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  • Tang, J, Liu, QQ, Yuan, HY, Zhang, YX, Wang, WL & Huang, SZ. 2018 Molecular cloning and characterization of a novel salt-specific responsive WRKY transcription factor gene IlWRKY2 from the halophyte Iris lactea var. Chinensis Genes Genomics. 40 8 893 903 https://doi.org/10.1007/s13258-018-0698-9

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  • Trivellini, A, Lucchesini, M, Ferrante, A, Carmassi, G, Scatena, G, Vernieri, P & Mensuali-Sodi, A. 2016 Survive or die? A molecular insight into salt-dependant signaling network Environ Exp Bot. 132 140 153 https://doi.org/10.1016/j.envexpbot.2016.07.007

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  • Velasco, R, Zharkikh, A, Affourtit, J, Dhingra, A, Cestaro, A, Kalyanaraman, A, Fontana, P, Bhatnagar, SK, Troggio, M, Pruss, D, Salvi, S, Pindo, M, Baldi, P, Castelletti, S, Cavaiuolo, M, Coppola, G, Costa, F, Cova, V, Dal Ri, A, Goremykin, V, Komjanc, M, Longhi, S, Magnago, P, Malacarne, G, Malnoy, M, Micheletti, D, Moretto, M, Perazzolli, M, Si-Ammour, A, Vezzulli, S, Zini, E, Eldredge, G, Fitzgerald, LM, Gutin, N, Lanchbury, J, Macalma, T, Mitchell, JT, Reid, J, Wardell, B, Kodira, C, Chen, Z, Desany, B, Niazi, F, Palmer, M, Koepke, T, Jiwan, D, Schaeffer, S, Krishnan, V, Wu, C, Chu, VT, King, ST, Vick, J, Tao, Q, Mraz, A, Stormo, A, Stormo, K, Bogden, R, Ederle, D, Stella, A, Vecchietti, A, Kater, MM, Masiero, S, Lasserre, P, Lespinasse, Y, Allan, AC, Bus, V, Chagné, D, Crowhurst, RN, Gleave, AP, Lavezzo, E, Fawcett, JA, Proost, S, Rouzé, P, Sterck, L, Toppo, S, Lazzari, B, Hellens, RP, Durel, CE, Gutin, A, Bumgarner, RE, Gardiner, SE, Skolnick, M, Egholm, M, Van de Peer, Y, Salamini, F & Viola, R. 2010 The genome of the domesticated apple (Malus ×domestica Borkh.) Nat Genet. 42 10 833 839 https://doi.org/10.1038/ng.654

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Supplemental Table 1.

Sequencing reads and reads mapping of RNA-sequencing.

Supplemental Table 1.
Supplemental Table 2.

Gene expression distribution of all the assembled genes from RNA-sequencing. Leaves from 1-month-old apple tissue culture materials of ‘Golden Delicious’ (Malus × domestica) treated with salt stress (200 mM NaCl) were collected at 0, 1, 6, 12, and 24 h and named CK_0 h, NaCl_1 h, NaCl_6 h, NaCl_12 h, and NaCl_24 h, respectively.

Supplemental Table 2.

Contributor Notes

R.W. and F.S. contributed equally to this work.

We thank the Earmarked Fund of the Beijing Natural Science Foundation (6214037), Handan Science and Technology Research and Development Plan project (21422012321), Innovation and Entrepreneurship Training Program for College Students (X202210076061), and the General project of the Natural Science Foundation of Hebei Province (C2022402006) for their support.

R.W. and F.S. are the corresponding authors. E-mail: wuruigang1986@126.com or shenf1028@gmail.com.

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    Fig. 1.

    Expression profiles of RNA sequencing data at 0, 1, 6, 12, and 24 h under salt stress (200 mM NaCl) in apple (Malus ×domestica). (A) Percentage distribution of expression frequency of transcriptome-sequenced genes in samples at different time points; CK represents control (0 h), NaCl_1–24 h represent different treatment times under salt stress. The ranges of fragments per kilobase of transcript per million mapped reads (FPKM) was divided into four ranges from 0 to infinity (inf). (B) Correlation of expression levels between different samples. (C) Principal component analysis of different samples. (D) Venn diagram of the comparison between CK and salt stress at different time points.

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    Fig. 2.

    Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the differentially identified genes among the groups: CK represents control (0 h), NaCl_1–24 h represent different treatment times under salt stress (200 mM NaCl). (A) GO enrichment analysis. (B) KEGG enrichment analysis. (C) Heatmap of differentially expressed genes (DEGs) gene expression enriched in GO term 0006950GO response to stress. (D) Heatmap of DEGs gene expression enriched into GO term 0007165 signal transduction.

  • View in gallery
    Fig. 3.

    Identification of differentially expressed genes (DEGs) associated with Salt Overly Sensitive (SOS) family by weighted gene coexpression network analysis [WGCNA (Langfelder and Horvath 2008)]. (A) mRNA sequencing was used to analyze the expression of the mitogen-activated protein kinase (MAPK) signaling pathway genes mediated by abscisic acid (ABA)-dependent or independent pathway at different time periods under salt stress. The function of ABA is mediated by its receptors that are a group of proteins termed regulatory component of ABA receptor (RCAR)/pyrabactin resistance 1 (PYR1)/pyrabactin resistance-like (PYL). The RCAR-protein phosphate 2C (PP2C)-SNF1-related protein kinase 2 (SnRK2) regulatory modules have been defined as the core components in ABA signaling. SnRK2s can directly phosphorylate ABA responsive element binding protein/ABRE binding factors (AREB/ABF). A typical MAPK cascade consists of at least three sequentially acting serine/threonine kinases, a MAPK kinase kinase (MAPKKK/MEKK), a MAPK kinase (MAPKK/MKK) and finally, the MAPK itself, with each phosphorylating, and hence activating, the next kinase in the cascade. (B) mRNA sequencing was used to analyze the expression of SOS signaling pathway genes at different time periods under salt stress. SOS3-like calcium-binding protein 8 (SCABP8) has been implicated in the SOS pathway. (C) Hierarchical clustering tree and module-sample relationships. The module with the highest correlation between SOS gene expression, treatment time, and gene expression was indicated by red underlining of the module name.

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    Fig. 4.

    Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) gene in three modules (ME): (A) MEred, (B) MEblue, and (C) MEturquoise.

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    Fig. 5.

    Network analysis of transcription factors (TFs) in the three modules (ME): (A) MEblue, (B) MEred, and (C) Meturquoise.

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    Fig. 6.

    Gene expression calorigram for three modules (ME): (A) MEblue, (B) MEred, and (C) Meturquoise.

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  • Miao, YX, Luo, XY, Gao, XX, Wang, WJ, Li, B & Hou, LP. 2020 Exogenous salicylic acid alleviates salt stress by improving leaf photosynthesis and root system architecture in cucumber seedlings Scientia Hortic. 272 109577 https://doi.org/10.1016/j.scienta.2020.109577

    • Crossref
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  • Mohamed, E, Matsuda, R, El-Khatib, AA, Takechi, K, Takano, H & Takio, S. 2015 Characterization of the superoxide dismutase genes of the halophyte Suaeda maritima in Japan and Egypt Plant Cell Rep. 34 12 2099 2110 https://doi.org/10.1007/s00299-015-1854-1

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    • Search Google Scholar
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  • Noman, M, Ahmed, T, Shahid, M, Niazi, MBK, Qasim, M, Kouadri, F, Abdulmajeed, AM, Alghanem, SM, Ahmad, N, Zafar, M & Ali, S. 2021 Biogenic copper nanoparticles produced by using the Klebsiella pneumoniae strain NST2 curtailed salt stress effects in maize by modulating the cellular oxidative repair mechanisms Ecotoxicol Environ Saf. 217 112264 https://doi.org/10.1016/j.ecoenv.2021.112264

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  • Nutan, KK, Singla-Pareek, SL & Pareek, A. 2020 The Saltol QTL-localized transcription factor OsGATA8 plays an important role in stress tolerance and seed development in Arabidopsis and rice J Exp Biol. 71 2 684 698 https://doi.org/10.1093/jxb/erz368

    • Search Google Scholar
    • Export Citation
  • Osman, MS, Badawy, AA, Osman, AI & Abdel Latef, AA. 2021 Ameliorative impact of an extract of the halophyte Arthrocnemum macrostachyum on growth and biochemical parameters of soybean under salinity stress J Plant Growth Regul. 40 3 1245 1256 https://doi.org/10.1007/s00344-020-10185-2

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  • Patel, RK & Jain, M. 2012 NGS QC toolkit: A toolkit for quality control of next generation sequencing data PLoS One. 7 2 e30619 https://doi.org/10.1371/journal.pone.0030619

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  • Pruthvi, V, Narasimhan, R & Nataraja, KN. 2014 Simultaneous expression of abiotic stress responsive transcription factors, AtDREB2A, AtHB7 and AtABF3 improves salinity and rrought tolerance in peanut (Arachis hypogaea L.) PLoS One. 9 12 E111152 https://doi.org/10.1371/journal.pone.0111152

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  • Rahman, MM, Rahman, MA, Miah, MG, Saha, SR, Karim, M & Mostofa, MG. 2017 Mechanistic insight into salt tolerance of Acacia auriculiformis: The importance of ion selectivity, osmoprotection, tissue tolerance, and Na+ exclusion Front Plant Sci. 8 155 https://doi.org/10.3389/fpls.2017.00155

    • Search Google Scholar
    • Export Citation
  • Rauf, M, Shahzad, K, Ali, R, Ahmad, M, Habib, I, Mansoor, S, Berkowitz, GA & Saeed, NA. 2014 Cloning and characterization of Na+/H+ antiporter (LfNHX1) gene from a halophyte grass Leptochloa fusca for drought and salt tolerance Mol Biol Rep. 41 3 1669 1682 https://doi.org/10.1007/s11033-013-3015-3

    • Crossref
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  • Rolly, NK, Imran, QM, Lee, I & Yun, BW. 2020 Salinity stress-mediated suppression of expression of salt overly sensitive signaling pathway genes suggests negative regulation by AtbZIP62 transcription factor in Arabidopsis thaliana Int J Mol Sci. 21 5 1726 https://doi.org/10.3390/ijms21051726

    • Crossref
    • Search Google Scholar
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  • Shannon, P, Markiel, A, Ozier, O, Baliga, NS, Wang, JT, Daniel, R, Amin, N, Schwikowski, B & Ideker, T. 2003 Cytoscape: A software environment for integrated models of biomolecular interaction networks Genome Res. 13 2498 2504 http://www.genome.org/cgi/doi/10.1101/gr.1239303

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  • Tang, J, Liu, QQ, Yuan, HY, Zhang, YX, Wang, WL & Huang, SZ. 2018 Molecular cloning and characterization of a novel salt-specific responsive WRKY transcription factor gene IlWRKY2 from the halophyte Iris lactea var. Chinensis Genes Genomics. 40 8 893 903 https://doi.org/10.1007/s13258-018-0698-9

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trivellini, A, Lucchesini, M, Ferrante, A, Carmassi, G, Scatena, G, Vernieri, P & Mensuali-Sodi, A. 2016 Survive or die? A molecular insight into salt-dependant signaling network Environ Exp Bot. 132 140 153 https://doi.org/10.1016/j.envexpbot.2016.07.007

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Velasco, R, Zharkikh, A, Affourtit, J, Dhingra, A, Cestaro, A, Kalyanaraman, A, Fontana, P, Bhatnagar, SK, Troggio, M, Pruss, D, Salvi, S, Pindo, M, Baldi, P, Castelletti, S, Cavaiuolo, M, Coppola, G, Costa, F, Cova, V, Dal Ri, A, Goremykin, V, Komjanc, M, Longhi, S, Magnago, P, Malacarne, G, Malnoy, M, Micheletti, D, Moretto, M, Perazzolli, M, Si-Ammour, A, Vezzulli, S, Zini, E, Eldredge, G, Fitzgerald, LM, Gutin, N, Lanchbury, J, Macalma, T, Mitchell, JT, Reid, J, Wardell, B, Kodira, C, Chen, Z, Desany, B, Niazi, F, Palmer, M, Koepke, T, Jiwan, D, Schaeffer, S, Krishnan, V, Wu, C, Chu, VT, King, ST, Vick, J, Tao, Q, Mraz, A, Stormo, A, Stormo, K, Bogden, R, Ederle, D, Stella, A, Vecchietti, A, Kater, MM, Masiero, S, Lasserre, P, Lespinasse, Y, Allan, AC, Bus, V, Chagné, D, Crowhurst, RN, Gleave, AP, Lavezzo, E, Fawcett, JA, Proost, S, Rouzé, P, Sterck, L, Toppo, S, Lazzari, B, Hellens, RP, Durel, CE, Gutin, A, Bumgarner, RE, Gardiner, SE, Skolnick, M, Egholm, M, Van de Peer, Y, Salamini, F & Viola, R. 2010 The genome of the domesticated apple (Malus ×domestica Borkh.) Nat Genet. 42 10 833 839 https://doi.org/10.1038/ng.654

    • Crossref
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