Introduction

Environmental stresses represent a significant limiting factor for plant growth and development. Abiotic stresses, including high salinity, cause economic losses through reduction in crop yields and ecological deterioration of the environment (Zhu 2001; Flowers 2004). Worldwide, salinity affects approximately 400 M ha (Szabolcs 1994; Al-Sadi et al. 2010). Increased salinization of arable land has been observed from both natural processes and human activity (Li et al. 2014a, b; Flowers et al. 1997; Ghassemi et al. 1995). Halophytes are salt-tolerant plants able to survive in hyper-saline soils and to complete reproductive life cycles under conditions that would be lethal for most agricultural crops (Flowers and Colmer 2008; Glenn et al. 1999). Endemic halophytes contribute to managing saline soils by preventing further deterioration of fragile ecosystems in saline areas and maintaining biodiversity in saline-alkaline fields (Flowers and Colmer 2008; Panta et al. 2014).

Evolutionary adaptations to diverse habitats have led to the differentiation of two major groups of plants; glycophytes and halophytes. Halophytes (salt tolerant plants) and glycophytes (salt sensitive plants) and are defined by their ability to grow in highly saline environments (Flowers et al. 2010). Most glycophytes suffer severe growth limitations at salt concentrations as low as 50 mol m−3 NaCl (up to 80 mM NaCl for most agricultural crops). In contrast, halophytes are extraordinarily tolerant to saline environments (up to 600 mol m−3 NaCl), approximately the concentration of sea water (Flowers et al. 1986). Halophytes employ a number of strategies to adapt to saline environments (Tester and Davenport 2003) involving modulation of primary and secondary metabolism and stress responsive signal transduction pathways (Guo et al. 2009; Yang and Poovaiah 2003). Halophytes also have developed alternative strategies for ion transport and compartmentalization (Lv et al. 2012; Sairam and Tyagi 2004), accumulation of antioxidants for the detoxification of reactive oxygen species (ROS), as well as synthesis and accumulation of compatible solutes (Sairam and Tyagi 2004; Ungar 1996). To genetically improve salinity tolerance of major agricultural crops, it is necessary to better understand adaptation strategies employed by halophytes. RNA-seq technology has proven to be a valuable approach to identify key genes involved in processes fundamental to salt tolerance in halophytes (Zhang et al. 2008; Yamanaka et al. 2009).

While many studies on salt tolerance mechanisms have been focused on glycophytes such as Arabidopsis, rice, and wheat far less attention has been given to euhalophytes. In addition, recently there has been a concerted effort to focus on studying plants naturally adapted to saline environments (halophytes) (Zhang et al. 2008; Li et al. 2009, 2014a, b). Salicornia europaea L. is a salt-accumulating euhalophyte from the Chenopodiaceae family that can withstand more than 1000 mM NaCl. It is found in coastal areas and inland salt marshes and has shown potential as a model system to study salt adaptation strategies. It has been demonstrated that growth and survival of S. europaea also relies on its ability to accumulate ions in its tissues for turgor maintenance and osmotic adjustment (Lv et al. 2012; Carter and Ungar 2004; Momonoki et al. 1996). Several genes involved in adaptation to stress in Salicornia have also been identified and improve salt stress tolerance when overexpressed in yeast, Arabidopsis and tobacco (Yang et al. 2011; Chen et al. 2011; Wu et al. 2010; Han et al. 2008). The recent publication of proteome reference maps and transcriptome data from different growth stages of S. europaea identified key salt tolerance mechanisms activated by high salinity in this species (Wang et al. 2009; Ma et al. 2013; Fan et al. 2013). However, gene expression changes in S. europaea roots in response to high salinity have not been specifically addressed in these studies. Therefore, existing transcriptomic data sets from S. europaea roots are insufficient to determine key components of salt tolerance. Therefore, the aim of this study is to better understand the role of salt-stress responses on the large-scale transcriptome sequencing of salinized Salicornia roots vs. non-salinized Salicornia roots after 72 h of exposure to 200 mM NaCl. We generated two sets of transcriptomic data with more than 100,000 unigenes from each sample and these were used to identify genes known to be involved, and potential candidates, in salt tolerance and the mechanisms responsible for salt stress tolerance present in S. europaea.

Materials and methods

Plant material preparation and Solexa sequencing

Seeds were collected from a single plant of S. europaea growing in saline soil in Fukang city, Xinjiang Uyghur Autonomous Region, China. This area is a wild field; not categorized as national park or other protected area. Therefore, this study did not use endangered or protected species. Seeds were first sown in ten sand-filled plastic pots (12 × 12 cm) and tap water was used for irrigation. Ten seedlings per pot were kept and grown in a greenhouse with a photoperiod of 16 h and a day/night thermoperiod of 25/20 °C. The relative humidity was maintained at 50 ± 10% and pots were irrigated weekly with Hoagland nutrient solution (half strength). Two months after germination in green-house conditions, seedlings were divided in two groups. The first group served as non-salinized controls (SeCKR) while the second (Se200R) was irrigated with 200 mM NaCl. Roots and shoots from both groups were harvested after 72 h and directly frozen in liquid nitrogen for the extraction of total RNA. Root tissue was used for cDNA library construction and shoot tissue used for qRT-PCR validation. Total RNA of salinized and non-salinized samples were extracted with the QIAGEN RNeasy Plant Mini kit (Qiagen) according to the manufacturer’s protocol. The total RNA was quantified using a NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, Delaware USA). A total of 20 µg RNA for each sample was used for the Illumina RNA-seq. Two tissue-specific cDNA libraries for Illumina sequencing and transcriptome analysis were constructed from these RNA samples. Finally, the cDNA library above was constructed and sequenced using the Illumina HiSeq™ 2000 platform (BGI, Beijing, China).

Raw sequence processing and de novo assembly

As previously described by Ma et al. (2013), after sequencing the cDNA library, nonsense reads were filtered out from raw reads of each library. This also included reads containing reads with an N (unknown bases per read) percentage higher than 5%, adaptor sequences, and low-quality reads (> 50% of the bases with a quality score of Q value ≤ 5). The Trinity program was used to assemble the preprocessed reads (Grabherr et al. 2011). Reads with a sufficient length of overlap were combined first, from reads having a zero N value (no unknown bases). Subsequently, reads were then mapped back to contigs using paired-end reads. Thus, contigs derived the same transcript in addition to the distances between these contigs were detected. These contigs were then connected through Trinity using the value N to denote unknown sequences between each contig pair to form scaffolds. Unigene sets were generated with 0 = N values in the sequence that could not be extended on either of the ends. Afterwards, BLASTX alignment (e value < 0.00001) was performed between the recovered unigenes using Clusters of Orthologous Groups (COG), NCBI Non-Redundant Dataset (Nr protein databases such as) and Swiss-Prot, KEGG (Kyoto Encyclopedia of Genes and Genomes). Sequence direction of the unigenes was determined by aligning the best aligning results. In cases where the results from different databases were in conflict a priority order used when deciding sequence direction: NCBI-Nr, Swiss-Prot, KEGG and COG. For un-aligned unigenes ESTScan was used to determine sequence direction (Iseli et al. 1999).

Gene function analysis and enrichment

We performed the functional annotation of unigenes based on a set BLAST searches, performed sequentially, intended to discover the most extensive annotation for each unigene (Ma et al. 2013). The unique unigenes were compared with sequences in protein databases (COG, Nr, KEGG, and Swiss-Prot) utilizing the BLASTX algorithm (e value < 0.00001) to identify proteins that were functionally annotated with the greatest sequence similarity to the unigenes found in this experiment. To predict and assign potential classification to our unigenes, the COG database was used. Meanwhile, unigenes were enriched in different KEGG pathways according to the KEGG pathways database, which was used for annotation of metabolic pathways. The program, Blast2GO, was used to classify each unigene with the GO terms, molecular function, cellular components and biological processes of the annotated unigenes (Conesa et al. 2005).

Comparison of SeCKR and Se200R transcriptome profiles

To identify differentially expressed genes (DEGs) between SeCKR and Se200R, levels of gene expression were assessed using the RPKM method, the relative formula RPKM = 106 C/10−3 NL and the statistical method FDR as previously described by (Mortazavi et al. 2008). GO functional as well as KEGG pathway analyses were also used on the DEGs data. To clarify commonalities and differences between shoot and root of S. europaea gene expression, the comparison of transcriptome data with our previous study Ma et al. (2013) was performed. Sequences from shoot named Se200S and SeCKS in Ma et al. (2013) were aligned with sequence from Se200R and SeCKR to generate All-Unigenes. Then sequences from different tissues and treatments were compared with All-Unigenes to the differentially expressed gene.

Validation of transcriptome data by RT-PCR and qRT-PCR

Two µg of total RNA (RNase-free and DNaseI-treated) with 500 ng of 1-mer oligo-dT primers and the M-MLV reverse transcriptase (Promega) were used to synthesize the cDNA. The program Primer 5.0 was used to design primers for qRT-PCR. The α-tubulin gene from S. europaea was used as an endogenous control. Quantitative RT-PCR was performed on the CFX96 real-time PCR detection system (Bio-Rad) with 25 µl PCR reaction volume as per the manufacturer’s protocol of the SYBR Premix Ex Taq Kit (TaKaRa Corp. Beijing, China). Amplification of cDNA was done at 95 °C for 60 s, followed by 40 cycles of 10 s at 95 °C, 30 s at 55 °C and 30 s at 72 °C. Melting curve analysis was carried out from 55 and 95 °C to detect the specificity of each PCR reaction. Quantitative variation was done using the quantitative method (ΔΔCt) (Ma et al. 2013).

Mining for EST-SSRs and characterization of SSRs markers

MIcroSAtellite (MISA, http://www.pgrc.ipk-gatersleben.de/misa) and Primer 5.0 were used to carry out SSRs and larger-scale primer design from 131,594 All-Unigenes according to the Han’s methods (Ma et al. 2013; Han et al. 2015) from transcriptome sequencing in S. europaea.

Result and discussion

Deep sequencing and de novo assembly

S. europaea requires approximately 200 mM NaCl in the root-zone for optimal growth, whereas the absence of salt inhibits normal plant growth (Fig. 1). Most glycophytic species would be negatively affected by similar NaCl concentrations. To investigate the transcriptional changes in S. europaea roots grown in salt-free and salt-enriched soil, total RNA was extracted from the root tissues and two sequencing libraries were constructed from salt-free (SeCKR) and 200 mM NaCl salt-treated (Se200R) samples. Based on sequencing results from the Illumina HiSeq™ 2000 platform adapter and low quality and sequences were eliminated from raw reads. A total of 41,146,244 (SeCKR) and 39,039,970 (Se200R) clean reads were generated from SeCKR and Se200R roots cDNA libraries with 97.24 and 97.61% Q20 percentages, respectively. All the Illumina reads generated in this study are deposited and available at the NCBI SRA browser (SRA number: SRS465161 for Se200R and SRA number: SRS465158 for SeCKR). The total length of all the reads was 7.17 giga bases (GB). All clean reads were used for de novo assembly. In addition, reads from both libraries were then clustered into 216,849 (SeCKR) and 276,224 (Se200R) contigs using the program Trinity. The average contig size was 263 bp for SeCKR and 240 bp for Se200R. Contig sizes were found to range from 100 to 3000 bp. All contigs were assembled into 122,728 (SeCKR) and 140,086 (Se200R) unigenes with 427 and 404 bp average lengths with size distribution ranging from 200 to 3000 bp to reduce sequence redundancy. The last step was performed to reduce redundancy and obtain longer unigenes following the combination of the data generated by the two library sets. A total of 131,594 All-Unigenes were generated and their nucleotide sequences are shown in the (supplementary file S1). All-Unigenes, unigenes, and the length distributions of contigs and are given in Table 1.

Fig. 1
figure 1

Phenotype of S. europaea grown under field conditions and different NaCl concentrations. a Plants grown in the field, b half-strength Hoagland nutrient solution, c half-strength Hoagland nutrient solution with 200 mM NaCl

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Table 1 Summary of S. europaea root transcriptome sequencing and assembly results
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Functional annotation and pathways

The sequences of All-Unigene from S. europaea generated from plant roots were first blasted using two databases: Swiss-Prot protein and NCBI non-redundant (nr) imposing a cut-off e value of 10−5. Of the 131,594 All-Unigenes, 58,065 (44.12%) were found to have significant matches with the NCBI nr protein database and 42,845 (32.56%) aligned with the Swiss-prot database (supplementary file S2).

Gene Ontology (GO) was used to classify functions of All-unigenes annotated. Utilizing the Blast2GO analysis, 26,932 of All-Unigenes (20.47%) were categorized into 44 terms involved in biological processes from three different ontologies: (16,000, 12.16%), cellular components (17,479, 13.28%) and molecular function (21,214, 16.12%), respectively (Fig. 2). A cluster of Orthologous Groups (COG) classification was further performed using the COG database to predict and then classify gene’s possible functions. In total, 21,712 All-Unigenes were grouped into 25 functional classes (Fig. 3). “The general function prediction only” was the largest group with 6324 genes classified in this category. Moreover, the categories of “inorganic ion transport and metabolism”, “intracellular trafficking, secretion, and vesicular transport”, “amino acid transport and metabolism” included more than 1000 genes which are predicted to be involved in the process of ion selective absorption, ion transport and compartmentalization associated with adaption to high salinity. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to define the cellular pathways in which the identified unigenes were involved. A total of 24,349 All-Unigenes were assigned to 120 different KEGG pathways. These All-Unigenes were assigned to: biosynthetic of secondary metabolites, plant-pathogen interactions, and metabolic pathways (supplementary file S2).

Fig. 2
figure 2

GO annotations of annotated non-redundant sequences of All-Unigenes. S. europaea unigenes generated from root were classified into 44 terms from three ontologies involved in biological processes, cellular components and molecular functions. X axis indicates the number of genes in a category. The Y axis (left) indicates all categories in the three main categories

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Fig. 3
figure 3

Clusters of orthologous groups (COG) classification of All-Unigenes. A total of 21,712 unigenes out of the All-Unigenes set were aligned to the COG database and classified into 25 functional-categories

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Identification of differentially expressed genes in SeCKR and Se200R libraries

Identification of DEGs in SeCKR and Se200R, a gene expression was performed according to the occurrence-frequency of reads from the two data sets utilizing the RPKM (Reads per kb per million reads) method and using threshold values FDR (false discovery rates) ≤ 0.001 and |log2 ratio| from the two data sets using the Reads per kb million reads (RPKM) method. Our results showed that 22,244 out of 131,594 total All-Unigenes were found to be differentially expressed within roots of S. europaea exposed or not exposed to NaCl treatment for 72 h. Among those DEGs responding to S. europaea exposed to high salinity, 13,299 were annotated and 8945 had no BLAST hits. In addition, a total of 10,275 unigenes were up-regulated in SeCKR and also 11,969 unigenes were up-regulated in Se200R library. Notwithstanding, there were 18,966 DEG existing in both libraries and another 2200 and 1078 were present only in SeCKR and Se200R, respectively (Fig. 4, supplementary file S3).

Fig. 4
figure 4

Se200R-vs-SeCKR differentially expressed genes. DEGs were filtered with FDR ≤ 0.001 and log2ratio ≥ 1 as a threshold. Red spots indicate up-regulated genes, and green spots indicate down-regulated genes. Blue spots represent those genes which did not show obvious changes between two treatments

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Enrichment analysis was applied to give an indication of the biological functions of DEGs identified in this study. The majority of DEGs were classified into three GO ontologies (biological processes, cellular components and molecular function) and 42 terms with the threshold P value ≤ 0.05 (Fig. 5, supplementary file S4). To predict the pathways in which DEGs were involved, a total of 6168 DEGs were then assigned to 117 pathways from the KEGG database. Most of these genes were mapped to metabolic pathways (1882 DEGs, 30.51%), biosynthesis of secondary metabolites (1064 DEGs, 17.25%), plant-pathogen interaction (485 DEGs, 7.86%), phenylalanine metabolism (157 DEGs, 2.55%) (Supplementary file S5). In total, 142,721 All-Unigenes were generated after alignment the sequence from four samples. The comparison results were list in supplementary file S6.

Fig. 5
figure 5

GO annotations of DEGs between Se200R and SeCKR. DEGs between Se200R and SeCKR were classified into three GO ontologies (biological processes, cellular components and molecular function) and 42 terms with the threshold P value ≤ 0.05. Y axis indicates the number of genes in a category. The X axis indicates all categories in the three main categories

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Ion uptake and transporter genes

Ions are primarily absorbed from the rhizosphere and into the root, where they are subsequently distributed throughout the rest of the plant. Ions translocation across membranes is primarily mediated by several types of ion transporters (Maathuis and Sanders 1996, 1997; Gierth et al. 2005; Shabala et al. 2003). Many ion transporters in plants have been identified and their role in ion uptake, acquisition and storage has been demonstrated (Maathuis and Sanders 1996; Rubio et al. 2000). Our transcriptome data identified a number of homologue of ion transporters related to Na+, K+, Ca2+, Zn2+, NH4+ uptake, transport and distribution (supplementary file S2).

Absorption and sequestration of Na+ from soil solution to the cell vacuole seems to be particularly effective in S. europaea, which actually experiences optimal growth with 200 mM NaCl in the root medium. However, the molecular mechanisms of influx, efflux, and intracellular compartmentation of ions in this euhalophyte have not yet been clearly described. Current evidence suggests that the principal mechanism of Na+ efflux and accumulation in plants is primarily controlled by the gene family of HKT, NHX, or Na+/H+ antiporters (Munns and Tester 2008; Rodríguez-Navarro and Rubio 2006). Three HKT1 genes, one of which was homologous to HKT1 from Populus trichocarpa and two other homologs of Suaeda salsa HKT1 were isolated from the roots of S. europaea. Unigene16272_All is similar to P. trichocarpa HKT1 occurring in both conditions, but with higher expression levels in salt-free plants. HKT1 (Unigene136795_All and Unigene33328_All) from Suaeda salsa was only detected under salt-free conditions. The transcript patterns of HKT1 under salt-free conditions indicated that HKT family may mediate Na+ transport and provide Na+ accumulation necessary for normal growth in saline environments in S. europaea. Alternatively, it may suggest that S. europaea possess ion selectivity and transport mechanisms in the roots that differ from other plants. A similar transcript pattern was found for a sodium symporter (Unigene42911_All), which was down-regulated almost tenfold in salt-treated plants. Furthermore, a sodium-dependent pyruvate transporter, the sodium/hydrogen exchanger salt overly sensitive 1 (SOS1), a sodium/calcium exchanger protein, and a sodium bile acid symporter-like protein were all found to be up-regulated in salt-free conditions but down-regulated in salt-treated conditions. Ion homeostasis is regulated by the SOS signaling pathway which consists of SOS1, SOS2, SOS3 components in Arabidopsis (Ji et al. 2013). Among them, SOS1 encodes a plasma membrane antiporter (Na+/H+) that is responsible for sodium extrusion from the cytosol and sodium transport from the root to the shoot (Shi et al. 2000, 2002). In higher plants SOS1 is conserved, present in monocots as well as dicots (Olías et al. 2009; Tang et al. 2010; Martínez-Atienza et al. 2007). Up-regulation of SOS1 in S. europaea under low salinity is consistent with previous findings showing that loss of SOS1 functionality in T. salsuginea causes loss of halophytism (Oh et al. 2009). It is probable that when a lack of basal of Na+ is perceived by the euhalophyte S. europaea the plant compensates for Na+ deficiency.

Nine ZIP transporter genes, implicated in Zn, Fe, Cu, Mn ion homeostasis were suppressed more than fivefold when S. europaea was exposed to 200 mM NaCl. Two additional ZIP transporter genes were up-regulated twofold under salt-treatment, whereas two putative Zn2+ transporter genes (Unigene3584_All and Unigene46509_All) were up-regulated in the absence of salt, showing RPKM values from 1.36 to 7.04 and from 5.47 to 66.7, respectively. Heavy metals such as Cd, Pb and Co have been shown to accumulate in shoots and roots of many halophytes (Manousaki and Kalogerakis 2009; Duarte et al. 2010; Van Oosten and Maggio 2015). The transport properties and roles of ZIP family members in root of S. europaea have not been sufficiently characterized and insights into the roles of these ZIPS family members would help elucidate the adaptation strategies of S. europaea.

We detected 11 ammonium transport related genes; of which nine were symbiotic ammonium transporters, eight ammonium transporters and two high-affinity ammonium transporters with higher transcript levels under salt-free than salt-treated conditions. These were probably responsible for ammonium uptake by plant cells at the plasma membrane and distribution to intracellular compartments such as vacuoles, mitochondria and chloroplasts (Howitt and Udvardi 2000; Öztürk and Demir 2002). The role of ammonium transport related genes in S. europaea is unclear and further studies are in progress in our laboratory to clarify the function of different members of ammonium transports from S. europaea in saline habitats.

Osmotic stress responsive genes

Halophytes may utilize similar salt tolerance regulatory pathways and mechanisms that have been reported in glycophytes (Zhu 2001). We found that several genes with known function in osmotic stress adaptation (Table 2), including those regulating proline, sucrose, mannose, betaine, sorbitol and trehalose synthesis/accumulation were upregulated in roots of S. europaea under both salt-treated and salt-free libraries. Among all of these osmolytes, proline is known to rapidly accumulate in large amounts in when exposed to environmental stresses in most glycophytes (Öztürk and Demir 2002, Hsu et al. 2003; Kishor et al. 2005). The primary functions of proline include buffering cellular redox potential, augmenting osmotic adjustment, enhanced stabilization of membranes and sub-cellular structures, and (Kishor et al. 2005; Stewart and Lee 1974). In our analysis, we found unigenes annotated with proline-rich protein 3, betaine/proline transporters, hydroxyproline-rich glycoprotein 1, and proline-rich extensin-like family protein, proline-rich cell wall protein 1 that had high expression levels but altered expression patterns under salt-free and salt-treated conditions. Several proline dehydrogenase genes with increased transcript levels were identified in salt-treated S. europaea. Considering that (1) proline dehydrogenases are enzymes responsible for the conversion of proline to glutamate and (2) proline may act as an inhibitor of growth under stress (Delauney and Verma 1993; Elthon and Stewart 1981). It is possible that proline levels must be maintained low in S. europaea to ensure growth under high salinity, whereas the function of osmolytes can be played by other organic molecules. Sucrose is the most abundant sugar which is accumulated under saline conditions in several halophytic grasses (Hester et al. 2001). There are many sucrose related genes such as sucrose synthase, sucrose transporters and sucrose-proton symporters which were identified in our transcriptome data. Unigene28286_All is homologue to sucrose synthase-1 with high reads occurrence in both libraries (119,030 in Se200R and 29,447 in SeCKR). In contrast, one sucrose transporter 5 gene (Unigene55114_All) was more highly expressed under salt-free (810 reads) than salt-treated (427 reads) conditions.

Table 2 Identification of differentially expressed genes between SeCKR and Se200R libraries
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Genes involved in ROS detoxification

Most glycophytes are negatively affected even at low salt concentrations and produce reactive oxygen species (ROS) that can damage lipids, proteins, and DNA damage (Verma and Dubey 2003). The salt concentrations that activate ROS accumulation in euhalophytes are higher than those of glycophytes, since a basal level of salt is required for these plants to grow (Ellouzi et al. 2011; Chaparzadeh et al. 2004). It is likely that growth of halophytes in salt-free and high salt environments may induce ROS production since these two conditions deviate from their normal growth habitat. Over-expression of antioxidants and enzymes like ascorbic acid (ASC), glutathione (GSH), peroxidase (POD), ascorbate peroxidase (APX), catalase (CAT), dehydroascorbate reductase (DHAR), superoxide dismutase (SOD), monodehydroascorbate reductase (MDHAR) are associated with the ROS detoxification system shared by both halophytes and glycophytes (Munns and Tester 2008). We found about 225 peroxidase-related genes in S. europaea among transcripts that were differentially expressed when exposed to salt-free and salt-treated conditions. The expression pattern analysis indicated that the most members (79 unigenes) of the peroxidase gene family were expressed with higher transcript levels in salt-free as compared to salt-treated conditions. Transcripts of Unigene132726_All, Unigene40102_All, Unigene132730_All, Unigene132677_All, and Unigene141574_All were more than 10 fold higher in salt-free than salt-treated medium (Fig. 6; Table 2). Peroxidases are key enzymes which regulate intracellular H2O2 through its conversion into water in plants (Abogadallah 2010). Conceivably, these peroxidases genes were up-regulated in salt-free conditions, which is an adverse condition for normal growth of S. europaea, but decreased with further exposure to a salinity level that is required for optimal growth by this species. This indicates that ROS would accumulate and injure the normal growth of euhalophytes when grown under salt-free conditions (Parida and Jha 2010).

Fig. 6
figure 6

Hierarchical clustering of peroxidase-related genes expression profiles under salt-free and salt-treated conditions. Clustering was performed on the software Cluster 3.0 with log transformed data. Horizontal rows indicate individual unigenes and two vertical rows indicate the two samples. Se200R: treatment with 200 mM NaCl. SeCKR: treatment without NaCl. Red and green represent the transcript level above and below the median (black), respectively; grey indicates that RPKM = 0

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Other peroxidase related antioxidant enzymes such as cationic peroxidase, ascorbate peroxidase, and a class III peroxidase were also detected in salt-free samples with high expression levels. Copper/zinc superoxide dismutase, Fe-superoxide dismutase, manganese superoxide dismutase, and a chloroplast iron superoxide dismutase occurred in our transcriptome data. However, the manganese superoxide dismutase had a distinct expression pattern clustering with other transcripts presenting higher expression level in salt treated roots (Se200R) (Supplementary Table S2). Unraveling the antioxidative machinery in halophytic species may provide useful insights on the molecular mechanisms of defense against oxidative stress generated under salt stress conditions.

Other differentially expressed genes that may contribute to stress tolerance in S. europaea

Other differentially expressed genes with possible functions in adapting to saline environments were also identified (Supplementary file S2). Among these, Unigene49746_All is unique with 1008 bp nucleotides and homologous to the Arabidopsis lipid transfer proteins (LTPs) (gi: 30682157). This gene was highly expressed in the roots of S. europaea grown in salt-free conditions but its expression significantly decreased upon salt-treatment. In previous studies, different functions were suggested for LTPs including: involvement in cutin synthesis, β-oxidation, plant signaling and defense against pathogens (Kader 1996; Wang et al. 2014). Recently, two LTP3 genes named ZmLTP3 and AtLTP3 were shown to improve plant’s ability to tolerate both salt and drought stress (Zou et al. 2013; Guo et al. 2013). There were also other five LTPs groups detected in our transcriptome data. Two of them (gi: 18403453, gi: 186512422) were up-regulated under salt-free conditions and other three (gi: 145332667, gi: 334186550, gi: 238480901) were up-regulated upon salt-treatment. Although LTPs were found to have distinct expression patterns and different transcript levels in the roots of S. europaea under salt-treated and salt-free environments, their function is currently unknown.

Unigene30013_All, an osmotin-like protein similar to that found in Atriplex nummularia, was upregulated under salt-free conditions but down regulated in the presence of salt. Osmotin is characterized as a stress response protein, which is induced by both biotic and abiotic stress conditions. It is a 26 kDa cationic protein and belongs to the PR-5 family (Parkhi et al. 2009; Singh et al. 1985). The osmotin protein may function as an osmotically active solute that helps to cope with these stresses (Singh et al. 1987; Subramanyam et al. 2012). It has been constitutively expressed in transgenic cotton, tobacco and strawberry to protect plants against drought and salinity stress (Parkhi et al. 2009; Subramanyam et al. 2012; Barthakur et al. 2001; Husaini and Abdin 2008). Osmotins are proteins found in both halophytes and glycophytes that play an important role in coping with abiotic stresses (drought and salinity) and biotic stresses (pathogens).

Unigene 42197_All and Unigene45617_All, which were identified in our transcript data, are homologous to the yellow-leaf-specific gene 7 (YLS7). This was annotated as a YLS7 cDNA encoding a novel hypothetical protein from Arabidopsis. In Arabidopsis, the function of YLS7 is not clear, but transcript accumulation of YLS7 has been associated with leaf senescence after 48–72 h of darkness (Yoshida et al. 2001). Previous studies have showed that these kinds of genes are also induced by pathogen infection and dehydration (Butt et al. 1998; Weaver et al. 1998). Two YLS7 homologs showed higher transcript levels in salt-free (SeCKR) than salt-treated (Se200R) libraries. Low ion concentrations may cause an increase in cellular water potentials in halophytes and induce physiological water loss, which can be a source of osmotic stress. Indeed salt-free conditions negatively affected the growth of S. europaea. Therefore, YLS7 can be used as molecular marker for distinguishing the growth condition of S. europaea under different saline environments (Yoshida et al. 2001).

Unigene27229_All, Unigene27233_All and Unigene27230_All were classified as vacuolar H+-pyrophosphate (AVP1) homologues. Unigene27233_All and Unigene27230_All were found to be down-regulated in salt-treated plants, but Unigene27229_All was up-regulated in salt treated plants. AVP1 functions as a proton pump and its overexpression results in an elevated proton gradient at across the tonoplast, which contributes to ion homeostasis. Expression of AVP1 from Arabidopsis in cotton improved tolerance to drought and salinity and increased yield for fiber in field experiments (Pasapula et al. 2011).

Confirmation of de novo assembled genes by qRT-PCR

To experimentally confirm our transcriptome data, a further 12 unigenes were analyzed via qRT-PCR. These transcripts were selected as representatives based upon their annotations that indicate a role in salt tolerance. QRT-PCR results for the 12 selected unigenes reported that most real time PCR were in general agreement with their transcript abundance measured by RNA-seq. This indicates a good level of reliability for the transcriptomic profiling results (Fig. 7). Shoot expression levels are included for comparison with root expression levels.

Fig. 7
figure 7

Validation of Transcriptome profiling of expression with qRT-PCR. Relative expression of 12 selected genes from the transcriptome profiling data are shown above each gene. Relative transcript levels were obtained by real-time PCR using S. europaea alpha-tubulin gene as the standard. Three biological replicates were performed

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Development of simple sequence repeats (SSRs) in Salicornia

EST-SSR markers were designed from coding region of gene and, therefore, they are useful for the detection of genes that tightly linked to variety function in organism and analysis of genetic diversity and breeding of plants. Based on the results of transcriptome sequencing, totally 131,594 containing 76,938,640 bp non-redundant unigenes were assembled and were used to SSR mining and primer design. A total of 8639 SSRs were identified and 5 types (di- to hexanucleotide repeats) were detected according to unit sizes, among of which the percentage of hexanucleotides was highest (3635), followed by trinucleotide repeats (3083) and dinucleotide repeats (710), and tetranucleotide repeats were the lowest (418) (Fig. 8). Then 4539 non-redundant primers pairs were developed (Supplementary file S7), which will be useful for further genetic mapping construct, molecular breeding and identification in Salicornia europaea in the future.

Fig. 8
figure 8

The number distribution of SSR types from di- to hexanucleotide repeats. Motifs between two and six nucleotides long were considered and five types from di- to hexanucleotide repeats were detected according to unit sizes

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Conclusions

The goal of this study was to better understand salt-stress responses using the large-scale transcriptome sequencing of salinized Salicornia roots vs. non-salinized Salicornia roots. Previous studies have examined responses to high salinity, while in this study we used the absence of salinity to identify potential mechanisms of salt stress tolerance present and the genes that contribute to this tolerance in S. europaea. Combined with other studies on high salinity, these data provide further resources for studies on molecular adaptation mechanisms of euhalophytes roots under saline environments. Identification of the key pathways responsible for the extreme tolerance of euhalophytes will aid in the development of tolerance traits that can be transferred into economically important crops.

Author contribution statement

YYA, TCY and MJB designed the experiments. MJB, XXL and LL carried out RNA isolation, prepared samples for RNA-seq, carried out differential expression analysis, and drafted the manuscript. MJB and SYF participated in the plant culture, sample collection and qRT-PCR analysis. AM, MJB, MJV, ZDY, HG and OAM assembled the text, drafted the discussion and prepared the manuscript. All authors read and approved the final manuscript.