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Transcriptomic analysis of differentially expressed genes in leaves and roots of two alfalfa (Medicago sativa L.) cultivars with different salt tolerance

Abstract

Background

Alfalfa (Medicago sativa L.) production decreases under salt stress. Identification of genes associated with salt tolerance in alfalfa is essential for the development of molecular markers used for breeding and genetic improvement.

Result

An RNA-Seq technique was applied to identify the differentially expressed genes (DEGs) associated with salt stress in two alfalfa cultivars: salt tolerant ‘Halo’ and salt intolerant ‘Vernal’. Leaf and root tissues were sampled for RNA extraction at 0 h, 3 h, and 27 h under 12 dS m− 1 salt stress maintained by NaCl. The sequencing generated a total of 381 million clean sequence reads and 84.8% were mapped on to the alfalfa reference genome. A total of 237 DEGs were identified in leaves and 295 DEGs in roots of the two alfalfa cultivars. In leaf tissue, the two cultivars had a similar number of DEGs at 3 h and 27 h of salt stress, with 31 and 49 DEGs for ‘Halo’, 34 and 50 for ‘Vernal’, respectively. In root tissue, ‘Halo’ maintained 55 and 56 DEGs at 3 h and 27 h, respectively, while the number of DEGs decreased from 42 to 10 for ‘Vernal’. This differential expression pattern highlights different genetic responses of the two cultivars to salt stress at different time points. Interestingly, 28 (leaf) and 31 (root) salt responsive candidate genes were highly expressed in ‘Halo’ compared to ‘Vernal’ under salt stress, of which 13 candidate genes were common for leaf and root tissues. About 60% of DEGs were assigned to known gene ontology (GO) categories. The genes were involved in transmembrane protein function, photosynthesis, carbohydrate metabolism, defense against oxidative damage, cell wall modification and protection against lipid peroxidation. Ion binding was found to be a key molecular activity for salt tolerance in alfalfa under salt stress.

Conclusion

The identified DEGs are significant for understanding the genetic basis of salt tolerance in alfalfa. The generated genomic information is useful for molecular marker development for alfalfa genetic improvement for salt tolerance.

Peer Review reports

Background

Alfalfa (Medicago sativa L.) is an important forage legume in the world. Cultivated alfalfa is an outcrossing autotetraploid (2n = 4x = 32) with a genome size of 800–1000 Mb [1]. Although alfalfa is regarded as moderately tolerant to salinity [2], alfalfa yield reduces by approximately 6–7% for each dS m− 1 increase above a salinity of 2 dS m− 1 [3]. To stabilize alfalfa production under saline regions, the development of superior salt tolerant cultivars becomes an important breeding goal. Identification of candidate genes for salt tolerance can increase the accuracy of parental selection as this trait has low heritability [4]. Salt tolerance is a complex trait controlled by multiple genes, involving different signaling pathways, osmotic tolerance, ion transport, compartmentalization of salt ions in vacuoles, the synthesis of plant hormones and photosynthesis [5].

Next-generation sequencing technologies have been used to identify candidate genes involved in salt tolerance of alfalfa. Transcriptomic studies in the 1-week old root tissue of alfalfa under salt stress found 1165 DEGs, including 86 transcription factors, which are responsible for stress tolerance, kinase, hydrolase, and oxidoreductase activities [6]. Luo et al. [7] identified 8861 DEGs in 12-day old seedlings of alfalfa under salt stress, which are responsible for ion homeostasis, antiporter, signal perception, signal transduction, transcriptional regulation, and antioxidative defense. Lei et al. [8] revealed 2237 DEGs between salt tolerant and intolerant alfalfa cultivars and found a salt tolerant alfalfa cultivar maintained relatively stable expression of genes responsible for reactive oxygen species and Ca2+ pathway, phytohormone biosynthesis and Na+/K+ transport under stress. Gruber et al. [9], using bulked genotypes as replications, studied transcriptomes in alfalfa and found genes responsible for numerous functions in a salt intolerant alfalfa cultivar. In recent years, genetic modification of certain genes controlling salt tolerance have also been conducted in alfalfa. Overexpression of salt responsive genes or transcription factors had improved salt tolerance in transgenic alfalfa. Such genes include Alfin1 [10], AVP1 [11], GmDREB1 [12], SsNHX1 [13], TaNHX2 [14], GsCBRLK [15], GsZFP1 [16], OsAPX2 [17], SeNHX1 [18], AtNDPK2 [19], AgcodA [20], and GsWRKY20 [21]. These studies have advanced our understanding of the genetic control for salt tolerance in alfalfa. However, most studies mainly focused on single time point sampling of root tissue at the seedling stage after salt stress, limiting the analysis of the temporal expression of genes affecting salt tolerance.

Tissue specific protein induction is regulated during salinity stress and is unique to roots and shoots [22]. Thus, there should be tissue specific transcriptomic responses [23,24,25]. Although the root is the first receptor of salt stress [6, 7], leaf tissue is the main energy source for plant growth and stress tolerance during active growth and developmental stages. To advance our knowledge about the temporal gene expression in different tissues for the genetic control under salt stress between tolerant and intolerant cultivars, we conducted a RNA-Seq analysis with the objective to simultaneously analyze gene expressions of leaf and root tissues of two alfalfa cultivars with different tolerance to salinity after exposing them to 12 dS m− 1 of electrical conductivity salt stress for 0 h, 3 h, and 27 h. The analysis was fruitful with the identification of many unique genes conditioning salt tolerance in alfalfa.

Results

High throughput sequencing and assembly

A total of 408 million raw sequence reads were generated using the Illumina HiSeq sequencing platform. The reads were reduced to 93.5% (381 million clean reads) by removing adapter contamination and reads with length lower than 36 bp (Table 1). There were 84.8% of clean reads mapped to the alfalfa reference genome using STAR (v2.6.1a). The samples showed high percentages (78.8–92.4%) of mapping with the alfalfa reference genome except for ‘Halo’ root tissue sampled at 27 h of salt stress.

Table 1 Summary of Illumina sequencing data and mapped sequence reads for the assayed alfalfa samples

Differentially expressed genes (DEGs)

In leaf tissue, there were 237 DEGs identified between the two alfalfa cultivars. Among them, 34 DEGs were expressed at all three time points (0 h, 3 h, and 27 h) and 17 DEGs expressed after exposing to salt stress (3 h and 27 h) (Fig. 1a, b; Additional file 1: Table S1). Of these DEGs, 39, 31, and 49 DEGs were specific to ‘Halo’, and 34, 34, and 50 DEGs were specific to ‘Vernal’ at 0 h, 3 h and 27 h of salt stress, respectively (Fig. 1b). The number of DEGs in leaf tissue decreased after 3 h compared to 0 h treatment. Then, the number of DEGs increased from 3 h to 27 h of salt stress for both cultivars (Fig. 1b).

Fig. 1
figure1

Differentially expressed genes (DEGs) between salt tolerant ‘Halo’ and intolerant ‘Vernal’ alfalfa cultivars in leaf tissue at three different time-points: control (0 h), 3 h and 27 h after salt stress. a Venn diagram for number of DEGs in leaf tissue of two alfalfa cultivars (‘Halo’ vs. ‘Vernal’) at three different time-points (0 h, 3 h, and 27 h). Number in the parenthesis represents total number of DEGs. Numbers in each intersection represent the number of DEGs detected in two or three time points. b Number of DEGs identified in leaf tissue at each time-point (0 h, 3 h, and 27 h) between tolerant and intolerant alfalfa cultivars

In root tissue, a total of 295 DEGs were identified between the two alfalfa cultivars. There were 33 DEGs expressed at all three time points and 5 DEGs expressed after exposing to salt stress (Fig. 2a, b; Additional file 1: Table S2). Of these DEGs, 68, 55, and 56 DEGs were specific to ‘Halo’ at 0 h, 3 h and 27 h, whereas 64, 42, and 10 DEGs were specific to ‘Vernal’, respectively (Fig. 2b). The number of DEGs in root tissue decreased at 3 h as compared to 0 h treatment for both cultivars, but the decrease was greater for ‘Vernal’ than for ‘Halo’. The main difference of DEGs between the two cultivars in the root was from 3 h to 27 h, with a 76% decrease in DEGs in ‘Vernal’ while there was almost no change for ‘Halo’ (Fig. 2b). After 27 h of salt stress in root tissue, the number of DEGs in ‘Halo’ were five times more than that of ‘Vernal’ (Fig. 2b).

Fig. 2
figure2

Differentially expressed genes (DEGs) between salt tolerant ‘Halo’ and intolerant ‘Vernal’ alfalfa cultivars in root tissue at three different time-points: control (0 h), 3 h and 27 h after salt stress. a Venn diagram for number of DEGs in root tissue of two alfalfa cultivars (‘Halo’ vs. ‘Vernal’) at three different time-points (0 h, 3 h, and 27 h). Number in the parenthesis represents total number of DEGs. Numbers in each intersection represent the number of DEGs detected in two or three time points. b number of DEGs identified in root tissue at each time-point (0 h, 3 h, 27 h) between tolerant and intolerant alfalfa cultivars

Functional annotation of DEGs

To understand what biological processes are implicated in response to salinity, we assigned the DEGs to known Gene Ontology (GO) categories. Among 237 DEGs in leaf tissue, 148 (62.4%) DEGs were assigned to three ontology classes. In ‘Halo’ leaf tissue, the most noticeable DEGs [false discovery rate (FDR) < 0.05] were “drug binding” (GO:0008144, 5), “anion binding” (GO:0043168, 8), “ion binding” (GO:0043167, 15) and “catalytic activity” (GO:0003824, 24) among molecular functions (Fig. 3a) while there was no significantly enriched functional groups from biological process and cellular component. For ‘Vernal’ leaf tissue, “cofactor binding” (GO:0048037, 7) and “oxidoreductase activity” (GO:0016491, 11) were predominant (FDR < 0.05) among molecular functions (Fig. 3b) and “oxidation-reduction process” (GO:0055114, 10) (Fig. 3c) in biological process, but there was not any significantly enriched functional groups from cellular component.

Fig. 3
figure3

Gene ontology (GO) analysis of differentially expressed genes in leaf tissues of two alfalfa cultivars in response to salt stress (a, salt tolerant ‘Halo’ alfalfa; b and c, salt intolerant ‘Vernal’ alfalfa). Each box shows the GO term number, p-value in parenthesis, and GO term

Among the 295 DEGs in root tissue, 180 (61.0%) DEGs were annotated to three gene ontology classes. In root tissue of ‘Halo’, “anion binding” (GO:0043168, 9), “ion binding” (GO:0043167, 18) , “structural constituent of ribosome” (GO:0003735, 7), and “structural molecule activity” (GO:0005198, 7) among molecular functions (Fig. 4a) were noticeable, while “organo-nitrogen compound metabolic process” (GO:1901564, 15) was dominant among biological processes (Fig. 4b). “Ribosome” (GO:0005840, 7), “ribonucleoprotein complex” (GO:1990904, 8), “intracellular ribonucleoprotein complex” (GO:0030529, 8) were predominant in cellular components (Fig. 4c). For root tissue of ‘Vernal’, “anion binding” (GO:0043168, 9) and “drug binding” (GO:0008144, 5) (Fig. 4d) were significantly (FDR < 0.05) enriched, while no other functional group from biological processes and cellular components.

Fig. 4
figure4

Gene ontology (GO) analysis of differentially expressed genes in leaf tissues of two alfalfa cultivars in response to salt stress (a, salt tolerant ‘Halo’ alfalfa; b and c, salt intolerant ‘Vernal’ alfalfa). Each box shows the GO term number, p-value in parenthesis, and GO term

To identify pathways involved in salt tolerance, we carried out Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis of the DEGs. In total, 64 (27%) DEGs from leaf tissue and 86 (29.15%) DEGs from root tissue were assigned to 65 KEGG pathways (Table 2). In both tissues, the most significant DEGs were represented in the pathways of metabolism and biosynthesis of secondary metabolites. Of these, five pathways were common among different time points and alfalfa tissues. The highest level of enriched DEGs were in 14 pathways in leaf tissue and 6 pathways in root tissue after 27 h of salt stress. Among these pathways, the three highest enriched DEGs were involved in plant hormone signal transduction.

Table 2 Number of differentially expressed genes (DEGs) and corresponding pathways in leaf and root of salt tolerant ‘Halo’ and salt intolerant ‘Vernal’ alfalfa cultivars at 0, 3 and 27 h of salt stress

Candidate genes to enhance salt tolerance in alfalfa

The detected DEGs can be classified into two major groups for the candidate genes responsible for salt tolerance in alfalfa: 1) genes consistently expressed under short-term and long-term salt stress (3 h and 27 h) in ‘Halo’, and 2) the genes consistently expressed at all three time points in ‘Halo’. In the first group, there were 13 genes (11 in leaf; 2 in root) consistently expressed at both 3 h and 27 h of salt stress. While in the second group, there were 46 genes (17 in leaf, 29 in root) consistently expressed at all three time points. Thirteen candidate genes were highly expressed in both leaf and root tissues of ‘Halo’ as compared to ‘Vernal’, while 15 and 18 candidate genes revealed tissue specific expression in the leaf and root tissues of ‘Halo’, respectively (Tables 3, 4, and 5). Among the genes expressed in both tissues, MS.gene029203 (F-box/LRR-repeat protein 4) showed increasing expression with time in both leaf and root tissues of ‘Halo’, while MS.gene049294 (caffeic acid 3-O-methyltransferase) showed increasing expression with time in leaf tissue and MS.gene01091 (T-complex protein 1 subunit gamma) and MS.gene32989 (hypothetical protein TSUD_06780) showed increasing expression with time only in root tissue. Among the genes with leaf tissue specific expression, MS.gene029201 (replication protein A 70 kDa DNA-binding subunit C), MS.gene029206 (FAD synthetase 1, chloroplastic), and MS.gene24098 (thioredoxin-like protein CDSP32 chloroplastic-like) showed increasing expression with time. Among the genes with root tissue specific expression, MS.gene011517 (14 kDa proline-rich protein DC2.15) and MS.gene013923 (histone lysine N-methyltransferase, H3 lysine-9 specific SUVH1), had higher and consistent expression with time under salt stress.

Table 3 List of 13 salt responsive candidate genes simultaneously highly expressed in both leaf and root tissues of salt tolerant alfalfa cultivar ‘Halo’
Table 4 List of 15 salt responsive candidate genes highly expressed in leaf tissue of salt tolerant alfalfa cultivar ‘Halo’
Table 5 List of 18 salt responsive candidate genes highly expressed in root tissue of salt tolerant alfalfa cultivar ‘Halo’

In addition, there were also genes consistently expressed under salt stress in leaf (Additional file 1: Table S1) and root (Additional file 1: Table S2) tissues of ‘Vernal’. In ‘Vernal’, there were 21 (17 in leaf; 4 in root) genes consistently expressed at all three time points and 9 (6 in leaf; 3 in root) genes consistently expressed at both 3 h and 27 h of salt stress.

Identification of single nucleotide polymorphisms (SNPs)

The relative distribution of identified SNPs over alfalfa chromosome are presented in Fig. 5. A total of 74,705 SNPs were identified in this study, among which 37,527 were from 'Halo' and 37,178 were from 'Vernal'. Minimum number of SNPs were found in Chr6.4 while maximum number of SNPs were detected in Chr4.4 (Fig. 5).

Fig. 5
figure5

Distribution of SNPs identified over 32 allelic chromosomes of alfalfa (Medicago sativa L.) is represented with the Circos diagram. Histogram (1–70) showing distribution of SNPs per Mb bins across genome of alfalfa. The 8 alfalfa chromosomes (Chr1-8) are shown on outermost circle, middle (blue) and innermost (orange) circles represent SNPs distribution of salt intolerant 'Vernal' and salt tolerant 'Halo' alfalfa

Discussion

This study generated a unique set of differentially expressed genes associated with salt tolerance in alfalfa. This finding is not only significant for understanding the temporal expression of genes conditioning salt tolerance in alfalfa, but also can be used to characterize alfalfa breeding material and develop molecular markers for salt tolerance selection. First, 84.8% of sequence reads were mapped onto the alfalfa reference genome. Secondly, 237 DEGs in leaf and 295 DEGs in root tissues were identified between the two alfalfa cultivars. Third, this study was able to determine candidate genes consistently expressed under short-term and long-term salt stress in the salt tolerant cultivar. Fourth, this study found 74,705 SNPs which are valuable marker for future alfalfa breeding for salt tolerance. Fifth, we found ‘Halo’ under salt stress maintained 5 five times more DEGs in the root than ‘Vernal’. Finally, this study found seven candidate genes for salt tolerance (MS.gene32989, MS.gene065734, MS.gene24746, MS.gene81767, MS.gene044457, MS.gene049840, and MS.gene46459) with unknown functions, suggesting a need for further research to understand their role in salt tolerance.

Due to polyploidy and its out-crossing nature, alfalfa has encountered many challenges in genomic studies [26] as compared to self-pollinated crops such as wheat [27] and soybean (Glycine max) [28]. Thus, this transcriptomic study had considered several factors to overcome certain technical difficulties. First, identical clones were sampled at different time points from different alfalfa tissues. Unlike previous alfalfa transcriptomic studies, two technical replicates for each treatment were included to minimize technical errors. Furthermore, this study focused on both leaf and root tissues of alfalfa cultivars to capture tissue specific gene expression. These considerations seemed to be effective in capturing about 381 million high quality reads, which likely represents most of the genome of M. sativa. The raw reads showed a high percentage of mapping with the reference genome. These outputs should have enhanced our detection of DEGs. For example, both alfalfa cultivars showed a similar trend in the number of DEGs in leaf tissue with the increase of salt exposure time. In this study, we also selected three different time points (0 h, 3 h, and 27 h) to capture gene activation under short- and long- term salt stress. It has been established that salt responsive defense response is activated within 24 h of stress [29].

One of the main differences between the two cultivars was the number of DEGs in roots. In the root of salt tolerant alfalfa, the number of DEGs was similar between 3 h and 27 h of salt stress, but a sharp decrease was observed between 3 h and 27 h in the intolerant cultivar ‘Vernal’. We speculate that such earlier activation of salt responsive genes and maintenance of a large number of DEGs might be a key characteristic for salt tolerance in alfalfa, suggesting alfalfa tolerance is associated with upregulation of key genes from short term salt stress. About 60% of DEGs were assigned to GO categories, while KEGG pathways for less than 30% DEGs were identified in this study. The DEGs were mainly involved in metabolic pathways as revealed by KEGG pathway analysis. Although certain pathways involved in salt tolerance may be conserved in plant species such as in halophytes, there was still variation among plant species, cultivars, and tissues [5]. This study demonstrated that transcriptional variation in adaptation to salt stress exists not only among the alfalfa cultivars but also between the different tissues. ‘Ion binding’ (GO:0043167) was significantly enriched in both leaf and root tissues of ‘Halo’, but not in ‘Vernal’ under salt stress. This suggested that the genes responsible for ‘ion binding’ should be unique for salt tolerance of ‘Halo’ alfalfa. Therefore, the tissue- and genotype-specific salt responsive genes might be useful in identification of salt tolerant genotypes in the future.

Among 13 candidate genes expressed in leaf and root tissues of ‘Halo’ under salt stress (Table 3) in this study, two genes (MS.gene013222 and MS.gene52595) are responsible for transmembrane protein function. These transmembrane proteins control gateways and selective transport of salt ions to facilitate salt tolerance in plants. Likewise, MS.gene013211, a homologous gene to ribonuclease TUDOR1, is involved in stress adaptation and highly expressed in leaf and root tissues of ‘Halo’ in our study [30]. MS.gene93979, a homologous gene to NF-X1-type zinc finger protein, is part of mechanisms that regulate growth under salt stress and was highly expressed in leaf and root tissues of ‘Halo’ in our study [31]. In addition, MS.gene029202 (E3 ubiquitin-protein ligase CIP8), MS.gene029203 (F-box/LRR-repeat protein 4), MS.gene36780 and MS.gene36960 (elongation factor 1-alpha) were highly expressed in leaf and root tissues of salt tolerant alfalfa in our study. These genes are involved in regulation of a number of biological processes including biotic and abiotic stress tolerances [32,33,34]. For example, MS.gene049294, which is a homologous gene of O-methyltransferase, was found to improve salt tolerance in transgenic Arabidopsis [35]. MS.gene01091, a homologous gene to the T-complex protein 1 subunit gamma, showed high expression in both root and leaf tissue and is involved in intracellular assembly and folding of various proteins [36]. MS.gene029200, a homologous gene to replication factor A protein, was highly expressed in both leaf and root tissues of ‘Halo’ in our study, which might play a role in binding, replication, repair, and recombination of DNA under stress conditions [37].

In this study, we found 15 and 18 candidate genes specific to leaf and root tissues of salt tolerance ‘Halo’ alfalfa (Tables 4, 5). In leaf tissue, nine genes showed consistent expression under salt stress, while six of them were expressed at all three time points. In our study, salt tolerant alfalfa showed an increased expression of MS.gene024018 and MS.gene24098 with putative functions of chloroplastic glutaredoxin and thioredoxin-like protein CDSP32, respectively. The two genes (MS.gene024018, MS.gene24098) were found to be important for defense against protein oxidative damage in other studies [38, 39]. This is important because salt stress results in the formation of reactive oxygen species, which damage protein, membrane lipids, and nucleic acids [40]. MS.gene63155, a homologous gene to receptor-like kinases (RLKs), are a family of transmembrane proteins, showed lowered expression with time under salt stress. This gene is involved in plant growth as well as stress response [41]. Two nucleoporin proteins (MS.gene037960 and MS.gene39381) were expressed consistently under salt stress in leaf tissue of ‘Halo’. These proteins connect cytoplasm and nucleoplasm, and are involved in abiotic stress tolerance [42]. MS.gene038586 is a homologous gene to kinesin super family proteins which plays a significant role in intracellular transport and are critical for cellular functioning and survival [43]. MS.gene029206, a homologous gene to FAD synthetase 1, is a co-factor for various enzymes that participate in numerous metabolic processes like photosynthesis, electron transport, fatty acid oxidation and biosynthesis of secondary metabolites [44]. MS.gene36621, a homologous gene to stem 28 kDa glycoprotein, which is known as a vegetative storage protein, was highly expressed under salt stress in our study. This protein plays a certain role as a somatic storage protein during early seedling development [45]. Salt tolerant alfalfa showed a high expression of MS.gene07287 in leaf, a homologous gene to calvin cycle protein CP12-2. This gene is involved in photosynthesis and improved plant growth [46]. The Calvin–Benson cycle is the primary pathway of carbon fixation, producing carbon compounds. CP12 facilitates the formation of a complex between glyceraldehyde-3-phosphate dehydrogenase and phosphoribulokinase, thereby increasing the photosynthetic capacity of the plant [46]. MS.gene99197, a homologous gene to zeaxanthin epoxidase (ZEP), was highly expressed at all three time points in leaf tissue of ‘Halo’. It is an important enzyme in ABA biosynthesis and plays an important role in osmotic tolerance [47].

In root tissue, one (MS.gene61130) of the 18 genes detected was consistently expressed under salt stress, while the rest were expressed at all three time points in our study (Table 5). MS.gene002389, a homologous gene to secretory carrier-associated membrane proteins, is involved in membrane trafficking and found to influence accumulation of secondary cell wall components in Poplus [48]. MS.gene011517, a homologous gene to 14-kDa proline-rich protein DC2.15, is involved in cell wall modification and organization [49]. The plant cell wall is not only a physical barrier between the plant and the environment but also is a responsive part of the plant to biotic and abiotic stresses. The finding of tissue specific salt tolerant candidate genes responsible for the plant cell wall is promising and underlines the need for further research on its role in response to salt stress. In addition, salt stress causes lipid peroxidation, resulting in damage of membrane lipids and eventual cell leakage. This study showed salt tolerant alfalfa had an increased expression of MS.gene049130, a homologous gene to aldehyde dehydrogenase, responsible for oxidation of aldehydes produced during lipid peroxidation thereby detoxifying cells [50]. MS.gene95536 is a homologous gene to acyl-CoA-binding domain-containing protein 6, which is associated with phospholipid metabolism. This gene also was shown to play a role in the freezing tolerance of Arabidopsis [51]. MS.gene070486, a homologous gene to phosphatidylinositol transfer proteins, plays an important role in signal transduction and facilitates lipid transfer between membranes [52]. MS.gene056386, a homologous gene to fructokinases, are important enzymes catalyzing fructose phosphorylation and are involved in plant growth and development [53]. MS.gene058673, a homologous gene to heavy-metal-associated domain-containing protein conferring tolerance to abiotic stress [54]. MS.gene073760, a homologous gene to probable E3 ubiquitin-protein ligase LOG2, which induces amino acid secretion. This is the main form of organic nitrogen in the plant [55]. MS.gene02427, a homologous gene to soluble inorganic pyrophosphatase, is tightly linked with carbohydrate metabolism. It plays an important role in stress adaptive responses [56]. Carbohydrate metabolism produces soluble carbohydrates that are important for salt tolerance because of its osmotic adjustment function in the root.

Conclusion

Our study generated a unique set of DEGs for alfalfa salt tolerance studies and breeding efforts. The information is useful for better understanding of temporal expression of genes in response to salt stress. Furthermore, GO annotation and KEGG pathway analysis of the DEGs provided insights to the different molecular and biological processes between salt tolerant and intolerant alfalfa cultivars. In particular, ‘ion binding activity’ was found as a key molecular activity specific to salt tolerant alfalfa cultivar ‘Halo’. Based on this finding, salt tolerance in alfalfa appears to be associated with consistent expression of genes for selective transport of salt ions and compounds, increasing photosynthetic capacity as well as carbohydrate metabolism, enhancing defense against oxidative damage, modification of root cell wall and protection against lipid peroxidation. The SNPs discovered in this study will be valuable for molecular marker-assisted breeding for the development of salt tolerant alfalfa.

Methods

Plant material and salt treatment

Two alfalfa cultivars, ‘Halo’ (obtained from Agriculture and Agri-Food Canada, Swift Current Research and Development Centre) and ‘Vernal’ (sourced from Dr. Biligetu’s lab, Crop Development Centre, University of Saskatchewan) were chosen for the study. Cultivar ‘Halo’ was selected for improved salinity tolerance for germination, seedling growth, and mature plant regrowth at 100 mM NaCl in the greenhouse conditions [57], and cultivar ‘Vernal’ was considered as a salinity intolerant cultivar [58, 59]. Four genotypes (biological replicates) of each cultivar were grown from seeds in the College of Agriculture and Bioresources greenhouse at the University of Saskatchewan (45 Innovation Blvd., Saskatoon, SK) for 12 weeks. Six identical clones of each biological replicate were produced by stem cuttings. Salt stress of 120 mM NaCl approximately corresponding to 12 dS m− 1 electrical conductivity was applied on 4 week old seedlings. Salt stress of 12 dS m− 1 was selected from our earlier greenhouse study where alfalfa was grown at various gradients of salt stress and alfalfa cultivars showed variation in response to salt stress at 12 dS m− 1, with increase in salt stress from 12 dS m− 1 all alfalfa cultivars showed very high mortality (Bhattarai et al., unpublished). Leaf and root samples were collected immediately before salt treatment (control, 0 h), and at 3 h and 27 h of salt treatments. The samples were immediately frozen in liquid nitrogen and then stored at − 80 °C for 2 weeks until total RNA extraction carried out.

Tissue sample and RNA isolation

About 100 mg of tissue samples were disrupted using TissueLyser II and total RNA was extracted with RLT buffer using the Qiagen RNeasy Plant Mini Kit (Qiagen Inc., Mississauga, ON, Canada) according to the manufacturer’s protocol. DNase treatment was performed using the Ambion DNA-free DNase treatment and removal reagents (Life Technologies, Carlsbad, CA, USA) to remove contaminant genomic DNA from the isolated total RNA. Nanodrop 2000 (Thermo Fisher Scientific, Wilmington, DE, USA) was used to measure the total RNA concentration. RNA integrity number was evaluated for 12 samples using RNA 6000 Nano labchip on 2100 Agilent Bioanalyzer (Agilent Technologies, Waldbronn, Germany) (Additional file 1: Table S3; Additional file 2: Fig. S1).

Library preparation and sequencing

Poly (A) RNA was purified from total RNA using Magnosphere MS150 OligodT beads according to the manufacturer’s protocol. The RNA samples were subsequently used in cDNA library preparation. Two cDNA libraries were prepared using Lexogen’s SENSE mRNA-Seq Library Prep Kit V2 (Lexogen, Vienna, Austria). To minimize technical errors, two technical replicates of each treatment were divided into two cDNA libraries. The technical replicates represented two clones of the same genotype (biological replicate) by separately extracting RNA. Thus, 96 samples (2 cultivars × 2 tissue types × 3 time points × 4 biological replicates × 2 technical replicates) were collected for the study. The cDNA libraries were sequenced using the Illumina HiSeq v4 system at the National Research Council of Canada, Saskatoon, Canada. Raw reads were deposited in the National Center for Biotechnology Information (NCBI) and received BioProject ID PRJNA657410.

Reference-based mapping, differential gene expression analysis and annotation

The quality of the raw sequence was assessed using the FastQC software [60]. The raw reads were cleaned by removing adapters and low-quality sequences using Trimmomatic v.0.36 based on the default setting of paired-end mode, phred 33 and threads 6 [61]. The trimmed high-quality reads of samples from the two technical replicates were merged and mapped with the alfalfa reference genome (https://0-doi-org.brum.beds.ac.uk/10.6084/m9.figshare.12327602.v3) [62, 63] using STAR (v2.6.1a) [64] with “quantMode” as “GeneCounts”. The obtained “ReadsPerGene” of each sample were extracted as count matrix and the differentially expressed genes were analyzed using DeSeq2 package [65] where data were normalized by the median of the ratios. The threshold of padj < 0.001 and the Log fold change (Log2FC) > 2 were used to determine the significance of gene expression differences. The functional annotation of the DEGs were also extracted via searches of NR databases as available in “query.blastp.db.out” and gene ontologies were obtained via searches of the GO databases as available in “Msa.GO.list.up” likewise Kyoto Encyclopedia of Genes and Genomes (KEGG) Ortholog (KO) were obtained via search of KO databases as available in “query.ko” from Zeng [63]. Gene ontology analysis of the DEGs was done for biological process, cellular components, and molecular function by AgriGO v2.0 software [66]. Venn diagrams were produced using the Venny tool [67].

Identification of single nucleotide polymorphisms (SNPs)

SNPs calling was done using freebayes software using the bam file generated in the mapping process where at least 5 supporting observations were required to be consider a variant [68]. To visualize the relative distribution of SNPs over chromosomes, Circos tool was used [69].

Availability of data and materials

Raw reads have been deposited in the National Center for Biotechnology Information (NCBI) and received BioProject ID PRJNA657410. The data will be accessible with the following link: “https://0-www-ncbi-nlm-nih-gov.brum.beds.ac.uk/bioproject/PRJNA657410”.

Abbreviations

ABA:

Abscisic acid

AVP1:

Arabidopsis type I proton-pumping pyrophosphatase

DEGs:

Differentially expressed genes

dS m− 1 :

DeciSiemens per metre

DREB:

Dehydration-responsive element binding protein

NHX:

Na+/H+ antiporter

CBRLK:

Calcium/calmodulin-binding receptor-like kinase

ZFP:

Zinc finger protein

APX:

Ascorbate peroxidase

NDPK2:

Nucleoside diphosphate kinase 2

codA:

Choline oxidase

RLK:

Receptor-like kinase

FAD:

Flavin adenine dinucleotide

ZEP:

Zeaxanthin epoxidase

References

  1. 1.

    Blondon F, Marie D, Brown S, Kondorosi A. Genome size and base composition in Medicago siativa and M. truncatula species. Genome. 1994;37(2):264–70. https://0-doi-org.brum.beds.ac.uk/10.1139/g94-037.

    Article  PubMed  CAS  Google Scholar 

  2. 2.

    Maas EV, Hoffman GJ. Crop salt tolerance-current assessment. J Irrig Drain Div. 1977;103(2):115–34. https://0-doi-org.brum.beds.ac.uk/10.1061/JRCEA4.0001137.

    Article  Google Scholar 

  3. 3.

    Johnson DW, Smith SE, Dobrenz AK. Selection for increased forage yield in alfalfa at different NaCl levels. Euphytica. 1992;60(1):27–35. https://0-doi-org.brum.beds.ac.uk/10.1007/BF00022255.

    Article  CAS  Google Scholar 

  4. 4.

    Gregorio GB, Senadhira D. Genetic analysis of salinity tolerance in rice (Oryza sativa L.). Theoret Appl Genet. 1993;86:333–8.

    Article  CAS  Google Scholar 

  5. 5.

    Munns R, Tester M. Mechanisms of salinity tolerance. Annu Rev Plant Biol. 2008;59(1):651–81. https://0-doi-org.brum.beds.ac.uk/10.1146/annurev.arplant.59.032607.092911.

  6. 6.

    Postnikova OA, Shao J, Nemchinov LG. Analysis of the alfalfa root transcriptome in response to salinity stress. Plant Cell Physiol. 2013;54(7):1041–55. https://0-doi-org.brum.beds.ac.uk/10.1093/pcp/pct056.

    Article  PubMed  CAS  Google Scholar 

  7. 7.

    Luo D, Zhou Q, Wu YG, Chai XT, Liu WX, Wang YR, et al. Full length transcript sequencing and comparative transcriptomic analysis to evaluate the contribution of osmotic and ionic stress components towards salinity tolerance in the roots of cultivated alfalfa (Medicago sativa L.). BMC Plant Biol. 2019;19:32.

    Article  Google Scholar 

  8. 8.

    Lei Y, Xu Y, Hettenhausen C, Lu C, Shen G, Zhang C, et al. Comparative analysis of alfalfa (Medicago sativa L.) leaf transcriptomes reveals genotype-specific salt tolerance mechanisms. BMC Plant Biol. 2018;18(1):35. https://0-doi-org.brum.beds.ac.uk/10.1186/s12870-018-1250-4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. 9.

    Gruber M, Xia J, Yu M, Steppuhn H, Wall K, Messer D, et al. Transcript analysis in two alfalfa salt tolerance selected breeding populations relative to a non-tolerant population. Genome. 2017;60(2):104–27. https://0-doi-org.brum.beds.ac.uk/10.1139/gen-2016-0111.

    Article  PubMed  CAS  Google Scholar 

  10. 10.

    Winicov I. Alfin1 transcription factor overexpression enhances plant root growth under normal and saline conditions and improves salt tolerance in alfalfa. Planta. 2000;210(3):416–22. https://0-doi-org.brum.beds.ac.uk/10.1007/PL00008150.

    Article  PubMed  CAS  Google Scholar 

  11. 11.

    Bao AK, Wang SM, Wu GQ, Xi JJ, Zhang JL, Wang CM. Overexpression of the Arabidopsis H+-PPase enhanced resistance to salt and drought stress in transgenic alfalfa (Medicago sativa L.). Plant Sci. 2009;176:232–40.

    Article  CAS  Google Scholar 

  12. 12.

    Jin T, Chang Q, Li W, Yin D, Li Z, Wang D, et al. Stress-inducible expression of GmDREB1 conferred salt tolerance in transgenic alfalfa. Plant Cell Tissue Organ Cult. 2010;100(2):219–27. https://0-doi-org.brum.beds.ac.uk/10.1007/s11240-009-9628-5.

    Article  CAS  Google Scholar 

  13. 13.

    Li W, Wang D, Jin T, Chang Q, Yin D, Xu S, et al. The vacuolar Na+/H+ antiporter gene SsNHX1from the halophyte Salsola soda confers salt tolerance in transgenic alfalfa (Medicago sativa L.). Plant Mol Biol Rep. 2011;29(2):278–90. https://0-doi-org.brum.beds.ac.uk/10.1007/s11105-010-0224-y.

    Article  CAS  Google Scholar 

  14. 14.

    Zhang YM, Liu ZH, Wen ZY, Zhang HM, Yang F, Guo XL. The vacuolar Na+/H+ antiport gene TaNHX2 confers salt tolerance on transgenic alfalfa (Medicago sativa L.). Funct Plant Biol. 2012;39(8):708–16. https://0-doi-org.brum.beds.ac.uk/10.1071/FP12095.

    Article  PubMed  CAS  Google Scholar 

  15. 15.

    Bai X, Liu J, Tang L, Cai H, Chen M, Ji W, et al. Overexpression of GsCBRLK from Glycine soja enhances tolerance to salt stress in transgenic alfalfa (Medicago sativa). Funct Plant Biol. 2013;40(10):1048–56. https://0-doi-org.brum.beds.ac.uk/10.1071/FP12377.

    Article  PubMed  CAS  Google Scholar 

  16. 16.

    Tang L, Cai H, Ji W, Luo X, Wang Z, Wu J, et al. Overexpression of GsZFP1enhances salt and drought tolerance in transgenic alfalfa (Medicago sativa L.). Plant Physiol Biochem. 2013;71:22–30. https://0-doi-org.brum.beds.ac.uk/10.1016/j.plaphy.2013.06.024.

    Article  PubMed  CAS  Google Scholar 

  17. 17.

    Zhang Q, Ma C, Xue X, Xu M, Li J, Wu JX. Overexpression of a cytosolic ascorbate peroxidase gene, OsAPX2, increases salt tolerance in transgenic alfalfa. J Integr Agric. 2014a;13(11):2500–7. https://0-doi-org.brum.beds.ac.uk/10.1016/S2095-3119(13)60691-7.

    Article  CAS  Google Scholar 

  18. 18.

    Zhang LQ, Niu YD, Huridu H, Hao JF, Qi Z, Hasi A. Salicornia europaea L. Na+/H+ antiporter gene improves salt tolerance in transgenic alfalfa (Medicago sativa L.). Genet Mol Res. 2014b;13(3):5350–60. https://0-doi-org.brum.beds.ac.uk/10.4238/2014.July.24.14.

    Article  PubMed  CAS  Google Scholar 

  19. 19.

    Wang Z, Li H, Ke Q, Jeong JC, Lee HS, Xu B, et al. Transgenic alfalfa plants expressing AtNDPK2 exhibit increased growth and tolerance to abiotic stresses. Plant Physiol Biochem. 2014;84:67–77. https://0-doi-org.brum.beds.ac.uk/10.1016/j.plaphy.2014.08.025.

    Article  PubMed  CAS  Google Scholar 

  20. 20.

    Li H, Wang Z, Ke Q, Ji CY, Jeong JC, Lee H, et al. Overexpression of codA gene confers enhanced tolerance to abiotic stresses in alfalfa. Plant Physiol Biochem. 2014;85:31–40. https://0-doi-org.brum.beds.ac.uk/10.1016/j.plaphy.2014.10.010.

    Article  PubMed  CAS  Google Scholar 

  21. 21.

    Tang L, Cai H, Zhai H, Luo X, Wang Z, Cui L, et al. Overexpression of Glycine soja WRKY20 enhances both drought and salt tolerance in transgenic alfalfa (Medicago sativa L.). Plant Cell Tissue Organ Cult. 2014;118(1):77–86. https://0-doi-org.brum.beds.ac.uk/10.1007/s11240-014-0463-y.

    Article  CAS  Google Scholar 

  22. 22.

    Ramagopal S. Salinity stress induced tissue-specific proteins in barley seedling. Plant Physiol. 1987a;84(2):324–31. https://0-doi-org.brum.beds.ac.uk/10.1104/pp.84.2.324.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. 23.

    Ramagopal S. Differential mRNA transcription during salinity stress in barley. Proc Natl Acad Sci U S A. 1987b;84(1):94–8. https://0-doi-org.brum.beds.ac.uk/10.1073/pnas.84.1.94.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. 24.

    Kumar S, Beena AS, Awana M, Singh A. Salt-induced tissue-specific cytosine methylation downregulates expression of HKT genes in contrasting wheat (Triticum aestivum L.) genotypes. DNA Cell Biol. 2017;36:283–94.

    Article  CAS  Google Scholar 

  25. 25.

    Villarino GH, Hu Q, Scanlon MJ, Mueller L, Bombarely A, Mattson NS. Dissecting tissue-specific transcriptomic responses from leaf and roots under salt stress in Petunia hybrida Mitchell. Genes. 2017;8(8):195. https://0-doi-org.brum.beds.ac.uk/10.3390/genes8080195.

    Article  PubMed Central  CAS  Google Scholar 

  26. 26.

    Liu Z, Chen T, Ma L, Zhao Z, Zhao PX, Nan Z, et al. Global transcriptome sequencing using the Illumina platform and the development of EST-SSR markers in autotetraploid alfalfa. PLoS One. 2013;8(12):e83549. https://0-doi-org.brum.beds.ac.uk/10.1371/journal.pone.0083549.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. 27.

    Feldman M, Levy AA. Allopolyploidy – a shaping force in the evolution of wheat genomes. Cytogenet Genome Res. 2005;109(1-3):250–8. https://doi.org/10.1159/000082407.

    Article  PubMed  CAS  Google Scholar 

  28. 28.

    Gill N, Findley S, Walling JG, Hans C, Ma J, Doyle J, et al. Molecular and chromosomal evidence for allopolyploidy in soybean. Plant Physiol. 2009;151(3):1167–74. https://0-doi-org.brum.beds.ac.uk/10.1104/pp.109.137935.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. 29.

    Hernandez JA, Almansa MS. Short-term effects of salt stress on antioxidant systems and leaf water relations of pea leaves. Physiol Plant. 2002;115(2):251–7. https://0-doi-org.brum.beds.ac.uk/10.1034/j.1399-3054.2002.1150211.x.

    Article  PubMed  CAS  Google Scholar 

  30. 30.

    Yan C, Yan Z, Wang Y, Yan X, Han Y. Tudor-SN, a component of stress granules, regulates growth under salt stress by modulating GA20ox3 mRNA levels in Arabidopsis. J Exp Bot. 2014;65(20):5933–44. https://0-doi-org.brum.beds.ac.uk/10.1093/jxb/eru334.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. 31.

    Lisso J, Altmann T, Müssig C. The AtNFXL1 gene encodes a NF-X1 type zinc finger protein required for growth under salt stress. FEBS Lett. 2006;580(20):4851–6. https://0-doi-org.brum.beds.ac.uk/10.1016/j.febslet.2006.07.079.

    Article  PubMed  CAS  Google Scholar 

  32. 32.

    Mazzucotelli E, Belloni S, Marone D, De Leonardis A, Guerra D, Di Fonzo N, et al. The e3 ubiquitin ligase gene family in plants: regulation by degradation. Curr Genomics. 2006;7(8):509–22. https://0-doi-org.brum.beds.ac.uk/10.2174/138920206779315728.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. 33.

    Song JB, Wang YX, Li HB, Li BW, Zhou ZS, Gao S, et al. The F-box family genes as key elements in response to salt, heavy metal and drought stresses in Medicago truncatula. Funct Integr Genomics. 2015;15(4):495–507. https://0-doi-org.brum.beds.ac.uk/10.1007/s10142-015-0438-z.

    Article  PubMed  CAS  Google Scholar 

  34. 34.

    Gao Y, Ma J, Zheng JC, Chen J, Chen M, Zhou YB, et al. The elongation factor GmEF4 is involved in the response to drought and salt tolerance in soybean. Int J Mol Sci. 2019;20(12):3001. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms20123001.

    Article  PubMed Central  CAS  Google Scholar 

  35. 35.

    Niron H, Türet M. A putative common bean chalcone o-methyltransferase improves salt tolerance in transgenic Arabidopsis thaliana. J Plant Growth Regul. 2020;39(3):957–69. https://0-doi-org.brum.beds.ac.uk/10.1007/s00344-019-10040-z.

    Article  CAS  Google Scholar 

  36. 36.

    Bhaskar KN, Goyal N. Cloning, characterization and sub-cellular localization of gamma subunit of T-complex protein-1 (chaperonin) from Leishmania donovani. Biochem Biophys Res Commun. 2012;429:70–4.

    Article  CAS  Google Scholar 

  37. 37.

    Longhese MP, Plevani P, Lucchini G. Replication factor A is required in vivo for DNA replication, repair, and recombination. Mol Cell Biol. 1994;14(12):7884–90. https://0-doi-org.brum.beds.ac.uk/10.1128/mcb.14.12.7884-7890.1994.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. 38.

    Broin M, Rey P. Potato plants lacking the CDSP32 plastidic thioredoxin exhibit overoxidation of the BAS1 2-cysteine peroxiredoxin and increased lipid peroxidation in thylakoids under photooxidative stress. Plant Physiol. 2003;132(3):1335–43. https://0-doi-org.brum.beds.ac.uk/10.1104/pp.103.021626.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. 39.

    Cheng NH, Liu JZ, Brock A, Nelson RS, Hirschi KD. AtGRXcp, an Arabidopsis chloroplastic glutaredoxin, is critical for protection against protein oxidative damage. J Biol Chem. 2006;281(36):26280–8. https://0-doi-org.brum.beds.ac.uk/10.1074/jbc.M601354200.

    Article  PubMed  CAS  Google Scholar 

  40. 40.

    Foyer CH, Noctor G. Oxidant and antioxidant signaling in plants: a re-evaluation of the concept of oxidative stress in a physiological context. Plant Cell Environ. 2005;28(8):1056–71. https://0-doi-org.brum.beds.ac.uk/10.1111/j.1365-3040.2005.01327.x.

    Article  CAS  Google Scholar 

  41. 41.

    Shiu SH, Bleecker AB. Expansion of the receptor-like kinase/Pelle gene family and receptor-like proteins in Arabidopsis. Plant Physiol. 2003;132(2):530–43. https://0-doi-org.brum.beds.ac.uk/10.1104/pp.103.021964.

    Article  PubMed  CAS  Google Scholar 

  42. 42.

    Dong CH, Hu X, Tang W, Zheng X, Kim YS, Lee BH, et al. A putative Arabidopsis nucleoporin, AtNUP160, is critical for RNA export and required for plant tolerance to cold stress. Mol Cell Biol. 2006;26:9533–43.

    Article  CAS  Google Scholar 

  43. 43.

    Hirokawa N, Noda Y. Intracellular transport and kinesin superfamily proteins, KIFs: structure, function, and dynamics. Physiol Rev. 2008;88(3):1089–118. https://0-doi-org.brum.beds.ac.uk/10.1152/physrev.00023.2007.

    Article  PubMed  CAS  Google Scholar 

  44. 44.

    Sandoval FJ, Zhang Y, Roje S. Flavin nucleotide metabolism in plants: monofunctional enzymes synthesize fad in plastids. J Biol Chem. 2008;283(45):30890–900. https://0-doi-org.brum.beds.ac.uk/10.1074/jbc.M803416200.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. 45.

    Mason HS, Guerrero FD, Boyer JS, Mullet JE. Proteins homologous to leaf glycoproteins are abundant in stems of dark-grown soybean seedlings. Analysis of proteins and cDNAs. Plant Mol Biol. 1988;11(6):845–56. https://0-doi-org.brum.beds.ac.uk/10.1007/BF00019524.

    Article  PubMed  CAS  Google Scholar 

  46. 46.

    López-Calcagno PE, Abuzaid AO, Lawson T, Raines CA. Arabidopsis CP12 mutants have reduced levels of phosphoribulokinase and impaired function of the Calvin-Benson cycle. J Exp Bot. 2017;68(9):2285–98. https://0-doi-org.brum.beds.ac.uk/10.1093/jxb/erx084.

    Article  CAS  Google Scholar 

  47. 47.

    Park HY, Seok HY, Park BK, Kim SH, Goh CH, Lee BH, et al. Overexpression of Arabidopsis ZEP enhances tolerance to osmotic stress. Biochem Biophys Res Commun. 2008;375(1):80–5. https://0-doi-org.brum.beds.ac.uk/10.1016/j.bbrc.2008.07.128.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. 48.

    Obudulu O, Mähler N, Skotare T, Bygdell J, Abreu IN, Ahnlund M, et al. A multi-omics approach reveals function of secretory carrier-associated membrane proteins in wood formation of Populus trees. BMC Genomics. 2018;19(1):11. https://0-doi-org.brum.beds.ac.uk/10.1186/s12864-017-4411-1.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. 49.

    Fan W, Lou HQ, Gong YL, Liu MY, Wang ZQ, Yang JL, et al. Identification of early Al-responsive genes in rice bean (Vigna umbellata) roots provides new clues to molecular mechanisms of Al toxicity and tolerance. Plant Cell Environ. 2014;37(7):1586–97. https://0-doi-org.brum.beds.ac.uk/10.1111/pce.12258.

    Article  PubMed  CAS  Google Scholar 

  50. 50.

    Koncitikova R, Vigouroux A, Kopecna M, Andree T, Bartos J, Sebela M, et al. Role and structural characterization of plant aldehyde dehydrogenases from family 2 and family 7. Biochem J. 2015;468(1):109–23. https://0-doi-org.brum.beds.ac.uk/10.1042/BJ20150009.

    Article  PubMed  CAS  Google Scholar 

  51. 51.

    Chen QF, Xiao S, Chye ML. Arabidopsis ACBP6 is an acyl-CoA-binding protein associated with phospholipid metabolism. Plant Signal Behav. 2008;3(11):1019–20. https://0-doi-org.brum.beds.ac.uk/10.4161/psb.6762.

    Article  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Garner K, Hunt AN, Koster G, Somerharju P, Groves E, Li M, et al. Phosphatidylinositol transfer protein, cytoplasmic 1 (PITPNC1) binds and transfers phosphatidic acid. J Biol Chem. 2012;287(38):32263–76. https://0-doi-org.brum.beds.ac.uk/10.1074/jbc.M112.375840.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. 53.

    Stein O, Granot D. Plant Fructokinases: evolutionary, developmental, and metabolic aspects in sink tissues. Front Plant Sci. 2018;9:339. https://0-doi-org.brum.beds.ac.uk/10.3389/fpls.2018.00339.

    Article  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Sun XH, Yu G, Li JT, Jia P, Zhang JC, Jia CG, et al. A heavy metal-associated protein (AcHMA1) from the halophyte, Atriplex canescens (Pursh) Nutt., confers tolerance to iron and other abiotic stresses when expressed in Saccharomyces cerevisiae. Int J Mol Sci. 2014;15(8):14891–906. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms150814891.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. 55.

    Pratelli R, Guerra DD, Yu S, Wogulis M, Kraft E, Frommer WB, et al. The ubiquitin E3 ligase LOSS OF GDU2 is required for GLUTAMINE DUMPER1-induced amino acid secretion in Arabidopsis. Plant Physiol. 2012;158(4):1628–42. https://0-doi-org.brum.beds.ac.uk/10.1104/pp.111.191965.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. 56.

    Lee SK, Jeon JS. Review: Crucial role of inorganic pyrophosphate in integrating carbon metabolism from sucrose breakdown to starch synthesis in rice endosperm. Plant Sci. 2020;298:110572. https://0-doi-org.brum.beds.ac.uk/10.1016/j.plantsci.2020.110572.

    Article  PubMed  CAS  Google Scholar 

  57. 57.

    Steppuhn H, Acharya SN, Iwaasa AD, Gruber M, Miller DR. Inherent responses to root-zone salinity in nine alfalfa populations. Can J Plant Sci. 2012;92(2):235–48. https://0-doi-org.brum.beds.ac.uk/10.4141/cjps2011-174.

    Article  Google Scholar 

  58. 58.

    Peel MD, Waldron BL, Jensen KB, Chatterton NJ, Horton H, Dudley LM. Screening for salinity tolerance in alfalfa. Crop Sci. 2004;44(6):2049–53. https://0-doi-org.brum.beds.ac.uk/10.2135/cropsci2004.2049.

    Article  Google Scholar 

  59. 59.

    Rahman MA, Alam I, Kim YG, Ahn NY, Heo SH, Lee DG, et al. Screening for salt responsive proteins in two contrasting alfalfa cultivars using a comparative proteome approach. Plant Physiol Biochem. 2015;89:112–22. https://0-doi-org.brum.beds.ac.uk/10.1016/j.plaphy.2015.02.015.

    Article  PubMed  CAS  Google Scholar 

  60. 60.

    Schmieder R, Edwards R. Quality control and preprocessing of metagenomic datasets. Bioinformatics. 2011;27(6):863–4. https://0-doi-org.brum.beds.ac.uk/10.1093/bioinformatics/btr026.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. 61.

    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. https://0-doi-org.brum.beds.ac.uk/10.1093/bioinformatics/btu170.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. 62.

    Chen H, Zeng Y, Yang Y, Huang L, Tang B, Zhang H, et al. Allele-aware chromosome-level genome assembly and efficient transgene-free genome editing for the autotetraploid cultivated alfalfa. Nat Commun. 2020;11(1):2494. https://0-doi-org.brum.beds.ac.uk/10.1038/s41467-020-16338-x.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. 63.

    Zeng Y. Genome fasta sequence and annotation files. figshare. Dataset; 2020. https://0-doi-org.brum.beds.ac.uk/10.6084/m9.figshare.12327602.v3. Accessed 28 Dec 2020

    Book  Google Scholar 

  64. 64.

    Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21. https://0-doi-org.brum.beds.ac.uk/10.1093/bioinformatics/bts635.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. 65.

    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. https://0-doi-org.brum.beds.ac.uk/10.1186/s13059-014-0550-8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. 66.

    Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, et al. AgriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res. 2017;45(W1):W122–9. https://0-doi-org.brum.beds.ac.uk/10.1093/nar/gkx382.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. 67.

    Oliveros JC. VENNY. An interactive tool for comparing lists with Venn Diagrams. 2007. https://bioinfogp.cnb.csic.es/tools/venny/index.html. Accessed 28 Feb 2021.

    Google Scholar 

  68. 68.

    Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. 2012. arXiv:1207.3907.

    Google Scholar 

  69. 69.

    Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639–45. https://0-doi-org.brum.beds.ac.uk/10.1101/gr.092759.109.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

We would like to thank Carolee Horbach, and Gregory Peterson at the Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada, Saskatoon, SK, for their technical assistance in RNA extraction and library preparation and Fangqin Zeng and Raju Chaudhary for their help and suggestions during data analysis. This research was enabled in part by support provided by WestGrid and Compute Canada. We would also like to thank greenhouse staff at the College of Agriculture and Bioresources, University of Saskatchewan, for their support and assistance.

Funding

The research was funded by an NSERC Discovery grant.

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Contributions

B.B. conceived the project; S.B., B.B. designed experiments; K.T. provided guidance on the salt stress system; B.B. prepared the study materials; S.B. performed experiments; S.B., Y.-B.F., B.B. analyzed data; S.B. wrote a first version of the manuscript and Y.-B.F., B.C., B.B., C.K., K.T. substantially contributed to the last version of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Bill Biligetu.

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Supplementary Information

Additional file 1

: Table S1. List of 237 differentially expressed genes in leaf tissue at the control (0 h), 3 h, and 27 h of salt stress between salt tolerant ‘Halo’ and salt intolerant ‘Vernal’ cultivars of alfalfa. Table S2. List of 295 differentially expressed genes in root tissue at the control (0 h), 3 h, and 27 h of salt stress between salt tolerant ‘Halo’ and salt intolerant ‘Vernal’ cultivars of alfalfa. Table S3. RNA quality of 12 RNA samples determined with 2100 Agilent Bioanalyzer.

Additional file 2

: Fig. S1. Electropherogram of 12 RNA samples.

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Bhattarai, S., Fu, YB., Coulman, B. et al. Transcriptomic analysis of differentially expressed genes in leaves and roots of two alfalfa (Medicago sativa L.) cultivars with different salt tolerance. BMC Plant Biol 21, 446 (2021). https://0-doi-org.brum.beds.ac.uk/10.1186/s12870-021-03201-4

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Keywords

  • Alfalfa
  • Differentially expressed genes
  • Salt stress
  • Transcriptome