1. Introduction
Most of the semi-arid and arid agrarian regions in the world suffer from boron (B) toxicity [1], which largely reduces crop production. A number of countries including the US, Türkiye, Syria, Serbia, Russia, Peru, Pakistan, Morocco, Mexico, Malaysia, Libya, Jordan, Italy, Israel, Iraq, India, Hungary, Egypt, Chile and Australia have been reported to have excessive soil B [2,3]. B-rich irrigation water and B-rich soil with reduced leaching causes precipitation of B in the topmost layer of soil, decreasing crop production [4,5]. Though the deficiency of B in crops can be dealt with the supply of B fertilizers, toxicity is difficult to handle as the washing of agricultural soil is not realistic [6]. Plants take in B through passive diffusion in deficient or sufficient B conditions, while they need borate exporters and boric acid channels to carry B under deficient and excess-B supply [7]. Crucial processes such as carbohydrate metabolism, antioxidant defense strategy, cell wall stability, cell division, and photosynthesis are influenced by excess B in plants, damaging the biochemical, physiological, and molecular mechanisms [8,9]. B toxicity not only decreases the root growth but also causes the yellowing of leaf tips along with the localized death of cells in the leaf tips [10,11].
The concentration of B in cells is maintained by different gene families, particularly borate exporters which take part in B efflux. Moreover, plant adaptation to B toxicity is enhanced with the breakdown of the mRNA of primary intrinsic protein NIP5 [12]. In roots, B efflux is regulated by BOR1 homologs that consequently control the movement of B to the shoots [7]. TaBOR1.2 is up-regulated under high B to remove surplus B out of the tissues. The wheat ortholog Ta-BOR2 is expressed to reduce the amount of root B mostly in tolerant genotypes [13]. B toxicity is suppressed through the prevention of B entrance into the xylem, which is decreased by the differential regulation of BOR4 in root tissues [14].
Wheat is one of the most broadly cultivated crops in the world, fulfilling the food demand of developed and developing countries [15]. A number of studies reported reduced wheat yields under boron toxicity [16,17,18,19,20,21,22]. The variable critical shoot boron concentrations have been reported for different wheat genotypes in different studies regulating the plants’ response to B toxicity [23,24,25,26]. The older leaves are firstly influenced by high B with necrosis and chlorosis on the leaf tips and brown lesions on different parts of the wheat plants. B toxicity decreases wheat emergence, foliation, shoot length, dry biomass, number of spikes per plant, grain weight, and yield [16,20,24,27]. Reduction in B concentrations of tissues, lessening of cellular active B, and improvement in plant biological tolerance are some of the mechanisms involved in the mitigation of boron toxicity (BT) [28]. Moreover, identifying B-tolerant genotypes and employing them in breeding programs to produce tolerant lines is another important approach to address B toxicity [28,29].
Wild wheat relatives and the available primitive forms are known to be a great resource of tolerance towards environmental stress conditions. The cultivated emmer wheat [Triticum turgidum subsp. dicoccum (Schrank) Thell.] with the AuAuBB genome and hulled grains is one of the most primitive types of cultivated crops in the world [30]. The tetraploid species developed from the domestication of wild emmer wheat (Triticum turgidum subsp. dicoccoides) around 10,000 years ago in the Karaca Dag Mountain of Türkiye [31,32]. Several studies have reported its complete genomic compatibility with durum wheat [30], making it a potential target for breeding programs. Although the T. dicoccum species is well-known for its valuable traits such as tillering, grain weight, and resistance to several biotic stresses [30], it is least explored for its tolerance towards boron (B) toxicity in soil, which is a significant agricultural problem around the world. Moreover, although several investigations focused on wheat response towards B toxicity and reported differentially expressed genes (DEGs) related to B tolerance in durum and bread wheat accessions [3,33], no study has reported a B-tolerant T. dicoccum genotype and its differentially regulated genes under B toxicity stress.
Considering the lack in this research area, after a thorough screening (unpublished data), a B-toxicity-tolerant T. dicoccum accession, PI94655, was recognized in one of our previous studies. To explore the molecular mechanisms behind the high B tolerance of this identified T. dicoccum genotype, PI94655, we analyzed the shoot transcriptome of the genotype treated with normal and high boron via RNA sequencing (RNA seq). RNA sequencing is used to determine the amount of available RNA and, subsequently, the level of gene expression at a certain moment [3,34]. The genome-wide differential regulation of genes, novel transcripts, and involved transcriptional pathways and factors in plant tissues suffering from a particular stress can be recognized via RNA sequencing.
The method has been extensively used to assess the transcriptional changes in several plants grown under B toxicity. However, it was not used before to understand the transcriptional differences in any boron-tolerant T. dicoccum genotype grown under B toxicity as compared to controlled growth conditions. Consequently, the hypothesis was that there would be significant transcriptional changes in the B-toxicity-tolerant T. dicoccum accession, PI94655, under high-boron treatment in comparison to control. Accordingly, the objective of the experiment was to report differentially expressed genes (DEGs), involved metabolic pathways, gene ontology and other molecular features of T. dicoccum genotype grown under a high-B environment as compared to normal growth conditions. This would not only provide further knowledge of molecular mechanisms underlying the B-tolerant T. dicoccum wheat response to high B, but might also suggest potential candidate genes for functional characterization and future use in upcoming breeding programs to improve wheat tolerance to B toxicity.
2. Materials and Methods
2.1. Plant Material, Boron Treatment and Estimation of Physiological Parameters
Initially, we screened 158 accessions comprising different wild and neglected wheat species for B tolerance and recognized a high-B-tolerant T. dicoccum genotype, PI94655 (our unpublished data). Hexaploid wheat cultivar Bolal 2973, whose high-B tolerance has been well-established in several previous studies [35,36], was employed as the reference cultivar to estimate the extent of B tolerance of PI94655. The accessions were hydroponically grown in a chamber with 45–55% humidity, 16/8 h light/dark photoperiod, 22 ± 10 °C temperature, and 16,000 Lx/day light intensity. Three replicates of both the T. dicoccum genotype and Bolal 2973 were allowed to grow in both the control [1/5th Hoagland with 3.1 µM B] and the highly toxic B treatment [10 mM B]. Seeds were initially kept for germination at room temperature without light for 3 days. Further, triplicates of five germinated seedlings of each accession were moved to pots with 1/5th Hoagland solution in two different sets (one set for every treatment). Thus, one biological replicate was composed of five plants and three replicates comprised a total of 15 plants per genotype for each treatment. B treatments were followed by three days of growth with continuous treatment for seven days and the solutions were replaced after every three days. After seven days, plants were harvested (at the tillering stage, Feekes scale 4–5) and growth parameters of genotypes including shoot length (SL), root length (RL), shoot fresh weight (SFW), root fresh weight (RFW), shoot dry weight (SDW), and root dry weight (RDW) were measured. In addition, for molecular analysis, three replicates of shoots of T. dicoccum genotype were taken from both treatments using liquid nitrogen and stored at −80 °C for RNA isolation.
2.2. RNA Extraction, Formation of cDNA Libraries, Shoot Transcriptome Sequencing of T. dicoccum Genotype
RNA isolation from the triplicate shoot samples of the T. dicoccum genotype, PI94655, was carried out using the manual total RNA extraction method as provided by Pandey et al. [3]. QIAzol-Lysis reagent was used for extraction and the received RNA pellet was diluted in 100 μL double distilled nuclease-free water. The quantity and quality, along with the RNA integrity score (RIS) values, were assessed employing a nanodrop spectrophotometer, 1% agarose gel, and the QIAxcel advanced fragment analyzer, respectively. The samples from two treatments (control and high B) were prepared for RNA sequencing using all the three biological replicates of the T. dicoccum PI94655 genotype by mixing equal amounts of their total RNA. Both the samples with RIN values higher than 7 were used to prepare cDNA libraries. MGI sequencing was conducted employing the DNBseq platform. With >97% of Q20 bases and >90% of Q30 bases, ~76 million high-quality paired end reads were developed per sample employing the oligoDT selection. The good quality reads with a phred score >30 from both treatment samples were deployed as clean reads for reference genome mapping and quantification of transcripts.
2.3. Assessment of Differentially Expressed Genes
HISAT2 (Hierarchical Indexing for Spliced Alignment of Transcripts) software was employed to align acquired clean reads with the Triticum aestivum reference genome (IWGSC_CS_RefSeq_v2.1), whereas Bowtie2 was used to align clean reads with the reference genes. Additionally, gene expression of each sample was assessed using RSEM. Cufflinksv2.2.2 software was used to normalize the expression of genes/transcripts employing the fragments per kilobase of transcript per million fragments mapped (FPKM) method. FPKM values were used to determine the differential fold change of the genes and FDR (false discovery rate) values. Smaller FDR values of genes denote their higher fold change and significant expression difference. Significantly differentially expressed genes (DEGs) were those with adjusted p value ≤ 0.01, false discovery rate (FDR) ≤ 0.001, and log2FoldChange ≥ 1. The iDEG R package was used to identify statistical significance of the differential expression of genes under two treatments in the absence of replicates [37,38].
2.4. Functional Assessment and Enrichment Analysis of DEGs
Enrichment of a specific gene in a specific pathway, molecular function and the biological process are determined via the enrichment analysis. The details of the significant DEGs-enriched GO functional terms were obtained via gene ontology (GO) enrichment analysis and the DEGs linked to particular biological processes were extracted. The alignment of DEGs to each entry in the gene ontology database provides information about significantly enriched GO functions. The p values and Q values were estimated to depict the statistical significance of enriched GO terms, and a Q value (corrected p value) ≤ 0.05 shows significant enrichment of GO terms in DEGs. Significantly enriched metabolic pathways and signal transduction pathways in DEGs were identified employing KEGG pathway enrichment analysis. The most significantly enriched biochemical, metabolic, and signaling pathways in DEGs were those with a Q value ≤ 0.05.
2.5. Involved Transcription Factors (TFs)
The transcription factor-encoding genes that were differentially expressed were identified and their transcription factor families were categorized.
2.6. RT-qPCR Based Expression Analysis
RNA samples from three biological replicates were employed to conduct reverse transcription and quantitative PCR (RT-qPCR). RT-qPCR was conducted to validate the differential expression of genes obtained from RNA sequencing. The normalization of target genes was carried out using Glyceraldehyde-3-phosphate dehydrogenase gene (TaGAP) as the internal control [33,36]. The NCBI Primer-BLAST program was used to design primers for four randomly selected genes for RT-qPCR (Table 1). Following the manufacturer’s instructions, the Transcriptor First Strand cDNA Synthesis Kit (Roche) and oligo-dT primers were used to reverse-transcribe cleaned total RNA samples into cDNA. The 1:10 dilutions of cDNA were used for final qPCR reactions of 20 μL that were performed in LightCycler® 96 (Roche, Germany) following the method and materials described by Pandey et al. [3]. Three biological and three technical replicates were used for qPCR reactions of each gene from both treatments. The levels of expression of target and reference genes and average errors of the means for two treatments were calculated. Melting curves revealed the sensitivity of individual samples and the ΔCt method proposed by Livak and Schmittgen [39] was employed to identify relative quantification.
3. Results
3.1. Physiological Changes in T. dicoccum, PI94655 and Bolal 2973 under B toxicity Stress
Several studies have shown the utility of measuring root–shoot growth parameters to understand the tolerance level of wheat genotypes [36,40,41,42]. In this experiment, B-toxicity-tolerance of T. dicoccum PI94655 genotype was determined in comparison with the check cultivar Bolal 2973, which is a well-known B-toxicity-tolerant genotype. Less yellowing of the leaves was observed in T. dicoccum PI94655 under high-B treatment in comparison with Bolal. High B significantly affected all the estimated growth parameters (p value < 0.0001) and it was revealed that PI94655 was less influenced by high B as compared to Bolal 2973 (Table 2 and Table S1). While the RL and SL of Bolal decreased by 50% and 38%, respectively, under high B as compared to control, the RL of PI94655 decreased by only 2% and shoot length increased by 4% under high B.
Likewise, a decrease of 108% and 30% was observed in the RFW and SFW of Bolal, but PI94655 showed an increase of 3% and a decrease of only 7%, respectively, for these two parameters under high B. High B reduced the DW of Bolal roots by 53% as compared t the no stress conditions, while it did not negatively affect the roots of PI94655, showing an increase of 10% in RDW. The SDW of Bolal neither increased nor decreased under B toxicity. While the SDW of PI94655 increased 16%, check cultivar showed no (0%) effect under B toxicity. On the other hand, the RDW of PI94655 increased only 10%, and check cultivar showed 53% decrease under B toxicity.
3.2. Transcriptome Sequencing and Genome Mapping of Sequencing Reads
RNA samples mixed from three biological replicates of shoots from both treatments and totaling 15 plants each were used for RNA sequencing analysis of the B-tolerant PI94655 genotype. Sequencing of RNA samples from control and high-B treatment gave a total of 152.19 million clean reads with an average of 76 million reads from each sample (Table 3). A total of approximately 180 million clean reads were obtained at the Q30 level (Table 3). The Triticum aestivum reference genome (IWGSC_CS_RefSeq_v2.1) was mapped to 14.69 and 16.68 high-quality clean reads from two libraries, with a unique mapping ratio of 4.84 and 5.50%, respectively (Table 3). A total of 43,852 and 44,921 genes, as well as 49,471 and 51,449 transcripts, were found in the control and treatment libraries, respectively (Table 3). Determining novel genes and/or transcripts is one of the major benefits of RNA sequencing [43]. In this study, we determined a total 3237 novel genes and 12,206 novel transcripts, respectively.
3.3. Differentially Regulated Genes of T. dicoccum Shoots under High B
The two shoot libraries showed a differential regulation of a total of 50,862 genes. Among these, 483 genes were significantly differentially expressed in the shoots of PI94655 under high B. Out of these significantly regulated genes, 112 were found to be down-regulated, while 371 genes were up-regulated (Figure 1).
3.4. Gene Ontology (GO) Analysis of Differentially Expressed Genes
Gene ontology functional enrichment was conducted to gain a better understanding of the roles played by the DEGs of B-tolerant T. dicoccum under high-B treatment. The DEGs of cellular component, biological process, and molecular function were categorized in to 3, 16, and 11 groups, respectively (Figure 2 and Figure S1). In the cellular components, genes associated with cellular anatomical entity, intracellular and protein-containing complexes were enriched. In the biological process, the genes associated with the cellular process, the metabolic process, the response to stimulus, and biological regulation were most enriched. In the molecular functions, genes linked with binding and catalytic activity were rich, followed by the genes associated with transporter activity.
3.5. KEGG Pathway Enrichment (Functional Regulatory Network Analysis) of DEGs of T. dicoccum under High B
Pathway-dependent analysis is used to understand biological functions that are affected by the interaction of genes. The KEGG (Kyoto Encyclopedia of Genes and Genomes) database is used to perform pathway enrichment analysis of DEGs. The pathway annotation of 456 DEGs was observed in the analysis that were grouped in five key KEGG classes covering 85 KEGG pathways (Figure S2). The pathways with the highest number of DEGs included metabolic pathways, biosynthesis of secondary metabolites, and oxidative phosphorylation (Table 4). The global and overview maps, energy metabolism, carbohydrate metabolism, translation and transcription comprised most of the DEGs of level 2. Photosynthesis–antenna proteins, followed by the caffeine metabolism, revealed maximum rich ratio in the KEGG pathway enrichment (Figure 3).
3.6. High-B-Responsive Transcription Factors of PI94655
A number of transcription factors regulating the response to boron toxicity stress have been identified in other Triticum species [3]. The gene expression is controlled by the binding of transcription factors (TFs) to their specific cis-acting elements. In T. dicoccum shoots, differential expression of 28 TFs from 10 TFs families was observed under high B as compared to the control. The highest percentages of differentially expressed TFs were from the AP2-EREBP, MYB, C3H, G2-like, GRAS, and NAC families. These transcription factors have already been shown to affect the plants’ response to abiotic stress (Figure 4).
3.7. RT-qPCR Analysis for Confirmation of Sequencing Results
RNA sequencing results were validated through the RT-qPCR of four candidate genes responsive to high boron (Table 1). The RNA sequencing results corroborated the RT-qPCR outcomes for four of the selected genes. Based on the obtained RT-qPCR results, TdG1 (TraesCS3B02G001500) and TdG2 (TraesCS3B02G252900) revealed an up-regulation of few folds under high B in comparison to control. TdG3 (TraesCS3B02G191500) and TdG4 (TraesCS3B02G388100) genes showed a significant increase of several folds in the expression (Figure 5).
4. Discussion
The modern wheat crop has become more susceptible to the continuously changing environment as its genetic diversity is largely reduced during the process of breeding and domestication [5]. Thus, wheat progenitors, either wild or cultivated types, have greater chances of tolerance to biotic and abiotic stress conditions. Thus, screening of different wheat progenitors and identifying their adaptation level to a particular stress may provide efficient genetic resources for breeding programs [1]. Furthermore, finding the genes that may be involved in providing tolerance to these genotypes of underutilized species and introducing them into contemporary cultivars can be a successful strategy for enhancing stress tolerance in current genotypes. T. dicoccum is one of the oldest cultivated cereal crops and it is still consumed in countries such as Türkiye, Italy and Switzerland as bread and pasta [44]. Cultivated emmer is regarded as suitable for planting in challenging environmental conditions and in small cultivation areas because it requires little agricultural input and does not require the use of pesticides. Despite its popularity for several traits, T. dicoccum has not been explored at all for high B tolerance. Here, we discuss how the high B supply affected the growth and transcriptome of the high-B-tolerant T. dicoccum genotype PI94655.
4.1. Higher B Toxicity Tolerance in T. dicoccum PI94655 as Compared to Bolal 2973
As compared to Bolal 2973, T. dicoccum PI94655 demonstrated reduced physiological consequences of B toxicity. Plant growth parameters are largely employed to predict B tolerance in wheat genotypes [1,5,26,36,40,41,42,45]. All the evaluated growth parameters revealed that PI94655 was less affected by high B as compared to Bolal 2973. The growth parameters of PI94655 either increased or decreased very little under high B in comparison to the check cultivar. This was comparable to earlier experiments that showed that B toxicity had less of an impact on wild or neglected wheat genotypes growth parameters as compared to the check cultivars used in the studies [1,5]. Root–shoot dry matter content is an important criterion to understand the level of tolerance of genotypes towards various stresses [1,41,46]. Our results of greater root length of more tolerant T. dicoccum genotype in comparison to the check cultivar under high B corroborated with those of Schnurbusch et al. [47], and Pallotta et al. [36]. Schnurbusch et al. [47] revealed that other than a few exceptions, the B tolerance levels of the examined 94 wheat lines under high B was associated with the root length of the genotypes. For root–shoot biomass, similar to our study, Torun et al. [26] also found that the SDW of tolerant genotypes was greater as compared to less tolerant genotypes. In one of our previous studies [1], high increment and less decrement in SDW and RDW of B-tolerant Aegilops genotypes was observed under B toxicity. In line with this study, the B-tolerant T. zhukovskyi genotype showed much less effect of B toxicity on root–shoot dry matter as compared to the check genotype Bolal [3]. On the basis of lesser increase and greater decrease in RDW of PI94655 and check cultivar, respectively, under B toxicity as compared to SDW, B toxicity seems to have more diminishing effect on roots as compared to shoots independent of the B tolerance level of the genotype [3,48].
4.2. Gene Ontology Analysis
Gene ontology functional analyses of DEGs revealed that in the biological process of B-tolerant T. dicoccum shoots, the maximum enrichment of DEGs was observed in the cellular process, metabolic process, response to stimulus, biological regulation, regulation of biological process and localization subgroups. Some of the enriched subgroups under high B were in agreement with the previous experiments conducted on high B (Figure 2) [3,49] and should be focused for further studies. Similarly, structural molecule activity, transporter activity, catalytic activity, and binding subgroups were most enriched with DEGs in the molecular functioning of B-tolerant T. dicoccum shoots. The enrichment of these subgroups in T. dicoccum under B toxicity corroborated with the studies on Puccinellia sp. [49] and T. zhukovskyi [3]. Interestingly, the enrichment of cellular anatomical entity, intracellular and protein-containing complex subgroups in cellular components of B-tolerant T. dicoccum shoots in this study was not in agreement with the above-mentioned literature. In most of the GO terms, the number of up-regulated genes was higher than that of the down-regulated genes. As expected in shoot tissues, in cellular components, the genes related to plastid, chloroplast, thylakoid and related membranes, photosynthetic membrane, organelle subcompartment, photosystem I, photosystem II, cytoplasm (GO:0009536, GO:0009507, GO:0009535, GO:0055035, GO:0042651, GO:0034357, GO:0009534, GO:0031976, GO:0009579, GO:0031984, GO:0009521, GO:0009523, GO:0005737, GO:0009522) were significantly enriched in high B stress. In the molecular function, genes associated with chlorophyll binding (GO:0016168), quinone binding (GO:0048038), oxidoreductase activity, acting on NAD(P)H, quinone or similar compound as acceptor (GO:0016655), NADH dehydrogenase (quinone) activity (GO:0050136), and NADH dehydrogenase activity (GO:0003954) were significantly enriched in high B stress. The enriched genes in biological processes included genes involved in photosynthesis, light reaction, light harvesting (GO:0015979 GO:0019684 GO:0009765), generation of precursor metabolites and energy (GO:0006091), protein–chromophore linkage (GO:0018298), and electron transport chain (GO:0022900).
4.3. Involved Transcription Factors
Transcription factors (TFs) are known to control multiple stress-responsive genes and may thus be used in genetic engineering to create stress-tolerant crops [50]. The crops’ ability to withstand stress can be improved by modifying the TFs of several families including the ones that were observed in our study, i.e., AP2-EREBP, MYB, C3H, G2-like, GRAS, and NAC. In this study, interestingly, all the TFs were up-regulated. Among these, the AP2/EREBP (APETALA2/ethylene-responsive element-binding proteins) family revealed maximum enrichment in the TFs of T. dicoccum shoots under high B (Figure 4).
AP2/EREBP TFs are known to regulate abiotic stresses such as freezing, salt, heat, drought and cold via participation in redox, sugar and hormone signaling [51]. A combination of many responsive elements or the conserved cis-elements found in the promoter regions of AP2/ERFs regulates AP2/ERFs expression. In Arabidopsis, several regulators of the AP2/EREBP family have been reported to be involved in cold, drought, salt and heat stress [52]. A significant enrichment of eight DEGs of the AP2/EREBP TF family under high B was observed in our study. In agreement with our study, Kayihan et al. [33] reported differential regulation of three AP2 transcription factor genes (ta.27316.1.s1_at, taaffx.80154.2.s1_at, ta.21124.1.s1_x_at) in wheat leaves of B-toxicity-tolerant and susceptible genotypes grown under high B.
MYB TFs that are extensively disseminated in plants regulate plants’ responses to environmental changes, and show direct involvement in several physiological and biochemical processes. A significant enrichment of three DEGs of the MYB TF family under high B was observed in our study. It has been established that R2R3 MYB TFs in barley play responsive roles towards high B [53]. Two Myb TFs of Arabidopsis thaliana, AtMYB13 and AtMYB68, provided B toxicity tolerance to wild-type yeast by confirming their involvement in maintaining B equilibrium in plants [54]. Contrary to our study, the leaves of B-susceptible and B-tolerant wheat genotypes showed down-regulation of two MYB transcription factor genes, ta.27337.1.s1_at and taaffx.81130.1.s1_at, respectively, under high B [33].
Several abiotic stresses including cold, salinity, and drought are regulated by the NAC (NAM, ATAF and CUC) gene family, which is one of the major plant-specific TFs families [55]. In the present study, high B significantly enriched two up-regulated DEGs from the NAC gene family (100499184 and 123060990). This was concurrent with a study on barley leaves where 10 mM B supply up-regulated the expression of the NAC domain TF (HM07L17r_at) [56]. In addition, in rice, B toxicity tolerance was developed with the down-regulation of BORON EXCESS TOLERANT1 (BET1) gene, which is a NAC-Like TF gene [57].
The cysteine3Histidine (C3H) gene family is a subgroup of the zinc finger protein (ZFP) family, which is one of the major TFs families in plants, and is known to play a significant role in regulating plant development, growth, and responses to environmental changes [58]. In our study, a total of three C3H family genes (123068901, 123060371 and 123189473) were significantly enriched in T. dicoccum shoots under high B, all of which were up-regulated. Golden 2-like (G2-like) genes are affiliated with the newly characterized GARP superfamily of transcription factors and are known to regulate the chloroplast development [59]. Several G2-like TF genes were observed to be differentially expressed in cold stress in mulberry [60], drought and cold stress conditions in maize [59], cold stress and osmotic stress in moso bamboo [61], and cold, salt, and drought stress in tomato [62]. In our study, two G2-like genes were up-regulated under B toxicity. The GRAS transcription factors (TFs) are a significant family of plant-specific TFs that have a variety of biological roles in plants, including symbiosis, biotic and abiotic stress tolerance, cell signaling, growth, development, and phytochrome signaling [63]. In wheat, elevated light up-regulated the expression of the GRAS gene TaSCL14, which is involved in delayed leaf senescence, protection from photooxidative stress, reduction in membrane injury under environmental stresses and increment in photosynthetic capacity [63,64].
As per the literature, the enrichment of the C3H, G2-like and GRAS TF genes in wheat genotypes grown under high B has not been previously reported. This can be due to a comparatively lesser number of transcriptomic studies on B stress in wheat. In addition, the specific enrichment of the C3H, G2-like and GRAS TF families presented in this study can be attributed to the experimental B-tolerant genotype (PI94655) or experimental species (T. dicoccum), as the transcriptome of both of them has not been previously explored for B toxicity tolerance.
4.4. Transporters
To date, several transporters have been reported for B uptake by roots, entry into the xylem and its distribution among leaves, thus balancing B equilibrium in plants [3,7,65,66,67]. ABC transporters deliver the B-anthocyanin complexes, internally detoxify B and facilitate the transmembrane movement of substrates [33,56]. Our results showed significant up-regulation of 4 ABC transporters that directed towards their involvement in maintaining B equilibrium in T. dicoccum shoots grown under high B. Two of these transporters were ABC transporter C subfamily members (genes 123069100, 123060539) and one was an ABC transporter B subfamily member (gene 123190482). While our results were not completely in line with the outcomes obtained in P. distans showing down-regulation of these transporters [65,68], these were concurrent with the ones obtained in wheat [33] and B-susceptible barley [56] showing up-regulation of these genes.
B toxicity in soil strongly regulates the expression of transporter-encoding genes such as B exporters, nodulin-26-like intrinsic proteins (NIPs) and plasma membrane intrinsic proteins (PIP). Aquaporins, which are intrinsic membrane proteins, not only assist the water exchange at the transmembrane, but also allow the diffusion of uncharged molecules [69,70]. In our study, six aquaporins, including TIP2-2 (genes 100037531 (up-regulated), 100037645 (up-regulated)), PIP2-7 (gene 123112894 (down-regulated)), NIP2-2 (genes 123151130; 123,160,605 (down-regulated)), and PIP2-2 (gene 123137541 (down-regulated)), were significantly differentially regulated under B toxicity in T. dicoccum shoots. The down-regulation of NIPs in our study corroborated the findings obtained in zhukovskyii wheat [3], bread wheat [33], Citrus macrophylla [71], and barley [56]. PIP2-7 (gene 123112894) and NIP2-2 (gene 123151130) were homologs to Aegilops tauschii. Other than ABC and B transporters, several other transporters, including peptide/histidine transporters, potassium transporters, copper transporter, amino acid transporters, silicon efflux transporter, proton coupled transmembrane transporters, were significantly differentially expressed in high B stress in T. dicoccum shoots.
4.5. Involved KEGG Pathways
In KEGG pathway analysis, the most significant enrichment was observed in the photosynthesis–antenna proteins and caffeine metabolism pathways. The highest number of enriched DEGs in high B stress was observed in metabolic pathways, biosynthesis of secondary metabolites, and oxidative phosphorylation (Figure 3). The metabolic pathways comprised 109 up-regulated and 63 down-regulated genes; the biosynthesis of secondary metabolites comprised 37 up-regulated and 25 down-regulated genes; and the oxidative phosphorylation comprised 27 up-regulated and 5 down-regulated genes. Similar to our study, the metabolic pathways were most enriched in the leaves of barley plants grown in high B [53]. In plants, different abiotic stress conditions trigger the production of secondary metabolites [72]. The activity of ABC transporters increases with the accumulation of secondary plant metabolites, such as indole alkaloids, anthocyanins, phenylpropanoids, and flavonoids in vacuoles [73,74]. In line with the present study, T. zhukovskyi roots showed up- and down-regulated genes involved in the biosynthesis of secondary metabolites in high B stress [3]. Different from our study, all genes taking part in secondary plant metabolisms were down-regulated in black poplar under high B [75].
A number of studies have reported the activation of plant defense responses via the photosynthesis–antenna proteins pathway on exposure to biotic and abiotic stresses [76]. Interestingly, in our study, all the genes of photosynthesis–antenna proteins were down-regulated under high boron. These outcomes corroborated the study on wheat where powdery mildew down-regulated the enzymes involved in the photosynthesis–antenna proteins pathway [76]. However, the results were different from those obtained in soybean seedlings grown under light deficiency stress, where most of the genes of photosynthesis–antenna proteins pathway were up-regulated [77]. The genes of this pathway in our study were participants in the light-harvesting chlorophyll protein complex (LHC) (light-harvesting complex II chlorophyll a/b binding protein 1). Plants’ thylakoid membranes include an array of protein and chlorophyll molecules called LHCs, which absorb light and transmit it to the photosynthetic reaction center (RC) [78]. The down-regulation of LHC-associated genes may lead to a decrease in light absorption, consequently reducing the photosynthesis rate. This can be a reason for the enrichment of the genes in GO terms related to plastid, chloroplast, thylakoid and related membranes, photosynthetic membrane, organelle subcompartment, photosystem I, photosystem II, cytoplasm in high B in our study.
4.6. Annotated Genes Confirmed with RT-qPCR
RT-qPCR validated the up-regulation (Figure 5) of the TdG1 gene (TraesCS3B02G001500) of T. dicoccum, which is a homolog of the Triticum dicoccoides swi5-dependent recombination DNA repair protein 1 (LOC119274246) gene. The gene showed 10-fold and 0.5-fold up-regulation in transcriptome sequencing and RT-qPCR. In line with our study, a change of two folds was observed in the expression of this wheat gene in response to low temperature as compared to control [79].
The TdG2 gene (TraesCS3B02G252900) of T. dicoccum that revealed increased expression in high B in our study (Figure 5) is a homolog of the Triticum dicoccoides ATP-dependent zinc metalloprotease FTSH 9 chloroplastic/mitochondrial (LOC119276292) gene. In agreement with our study, the increased expression of FTSH protein was recorded in response towards salinity stress in chickpea genotypes [80]. Several studies have reported the direct involvement of genes of the thylakoid FtsH complex in the stress response [81].
The TdG3 gene (TraesCS3B02G191500) of T. dicoccum that showed an up-regulation of approximately four times in high B in our study (Figure 5) is a homolog of the Triticum dicoccoides DDB1- and CUL4-associated factor (DCAF) 13-like (LOC119275595) gene. The result obtained was in agreement with a study on Arabidopsis where DCAF1 was up-regulated after ABA treatment and salinity stress [82]. In addition, a DCAF protein, DDI1, was shown to be up-regulated by salt, mannitol and UV-C treatment in tomato.
The TdG4 gene (TraesCS3B02G388100) of T. dicoccum that showed an up-regulation of approximately three times in high B stress in our study (Figure 5) is a homolog of the Triticum dicoccoides UDP-glucuronic acid decarboxylase 1-like (LOC119277519) gene. These results corroborated the ones obtained by Zhang et al. [83], where the gene was up-regulated by the powdery mildew and stripe rust in wheat line N9134. The NAD-dependent decarboxylation of UDP-glucuronic acid to UDP-xylose is catalyzed via this gene and the gene is required for the synthesis of the primary tetrasaccharide in glycosaminoglycan biosynthesis.
5. Conclusions
Wheat production and quality have been significantly restrained due to the negative impact of boron toxicity stress [45]. For the first time, we report the results of RNA sequencing of a high-B-tolerant T. dicoccum genotype, PI94655, grown under normal and high-B stress. The results suggest that several mechanisms in T. dicoccum interact in boron toxicity stress. Transcriptional profiling successfully identified putative functional candidate genes involved in B toxicity tolerance in T. dicoccum via differential regulation of different transporters including ABC transporters, aquaporins (NIP, PIP, TIP) and transmembrane proteins. Metabolic pathways, biosynthesis of secondary metabolites, and oxidative phosphorylation revealed the highest number of DEGs along with the highest enrichment in photosynthesis–antenna proteins and caffeine metabolism pathways. Moreover, TFs genes AP2-EREBP, MYB, C3H, G2-like, GRAS, and NAC families can be additional potential candidates for enhancing boron toxicity tolerance in wheat genotypes. Despite being one of the oldest cultivated cereal species, the potential of T. dicoccum has not been well-explored for biotic and abiotic stress tolerances. Due to its closeness with modern durum wheat and compatibility of producing fertile hybrids, the reported B-tolerant T. dicoccum genotype PI94655 in this study can be effectively utilized as a source of B toxicity tolerance in breeding programs and to further conduct further omics studies in wheat crop. In addition, the reported high B responsive candidate genes can be futuristically employed by plant breeders and molecular biologists for combining high B tolerance in high yielding wheat accessions. Being the first transcriptomic study on the high B tolerance of the T. dicoccum genotype, the obtained results should be focused, and the functional characterization of potential candidate genes should be conducted to elucidate the gene function in providing tolerance to high B.
Conceptualization: M.K.K. and A.P.; methodology: M.K.K. and A.P.; validation: M.K.K. and A.P.; formal analysis: M.K.K., A.P., M.H., V.R.R., T.V. and S.N.R.; investigation, M.K.K., A.P., A.T. and S.G.; writing—original draft preparation: M.K.K. and A.P.; writing—review and editing: M.K.K., A.P., M.H., V.R.R., T.V., A.T., S.N.R. and S.G.; project administration: M.K.K. and A.P.; funding acquisition: A.P. All authors have read and agreed to the published version of the manuscript.
We thank the National Small Grains Collection (NSGC), U.S. Department of Agriculture—Agricultural Research Service, USA, for providing the Triticum dicoccum genotype PI94655 genotype to A.P. for performing the research work of TUBITAK 1001 (No. 119O455) project.
The authors declare no conflict of interest.
Footnotes
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Enlarge this image.Figure 1. MA plot showing genes differentially expressed (blue and red dots) in high-B (TB 10 mM)-treated shoots of the T. dicoccum (Td) genotype PI94655 compared to 3.1 μM B (control) treatment. Y axis (M) and X axis (A) denote log2 transformed fold change and log2 transformed mean expression level, respectively.
Enlarge this image.Figure 2. Figure shows gene ontology classification of genes differentially expressed in high-B (TB 10 mM)-treated shoots of the T. dicoccum (Td) genotype PI94655 compared to 3.1 μM B (control) treatment. While the gene ontology term is denoted by Y axis, the X axis denotes the number of DEG in the biological process, cellular component, and molecular function.
Enlarge this image.Figure 3. KEGG pathway functional enrichment of genes differentially expressed in high-B (TB 10 mM)-treated shoots of the T. dicoccum (Td) genotype, PI94655 compared to 3.1 μM B (control) treatment. While the enrichment factor is presented on the X axis, the pathway name is shown on the Y axis. The lower (blue) q-value denotes the more significant enrichment, while the higher (white) q-value denotes the less significant enrichment. Point size shows the number of DEGs.
Enlarge this image.Figure 4. Abundance of transcription factors in transcription factor families in highly toxic B (TB 10 mM)-treated shoots of the T. dicoccum (Td) genotype, PI94655 compared to control (3.1 μM B) treatment.
Enlarge this image.Figure 5. Relative expression of TdG1 (TraesCS3B02G001500), TdG2 (TraesCS3B02G252900), TdG3 (TraesCS3B02G191500) and TdG4 (TraesCS3B02G388100) of high-B (TB 10 mM)-treated shoots of the T. dicoccum (Td) genotype, PI94655 compared to 3.1 μM B (control) treatment in relation to the reference gene, TaGAP. The values are provided as average expression of three individual replicates with standard error mean normalized to control.
Details of the differentially expressed genes (DEGs) of T. dicoccum shoots chosen from RNA sequencing results for RT-qPCR confirmation and the designed primers.
| Gene Code | Selected Gene | Annotated Gene Information | log2 Fold Change |
Primer Type | Sequence (5’->3’) |
|---|---|---|---|---|---|
| TdG1 | TraesCS3B02G001500 | PREDICTED: Triticum dicoccoides swi5-dependent recombination DNA repair protein 1 homolog (LOC119274246), mRNA | 10.68 | Forward primer | CCACTGTAAACGGCGCTAGA |
| Reverse primer | GGATCGGTTGGGGTTGCTTT | ||||
| TdG2 | TraesCS3B02G252900 | PREDICTED: Triticum dicoccoides ATP-dependent zinc metalloprotease FTSH 9, chloroplastic/mitochondrial (LOC119276292), mRNA | 14.69 | Forward primer | GCTGAGAAGTGCATCACGCT |
| Reverse primer | GTTTCCTTTAAACAATGGCGAGGCA | ||||
| TdG3 | TraesCS3B02G191500 | PREDICTED: Triticum dicoccoides DDB1- and CUL4-associated factor 13-like (LOC119275595), mRNA | 8.69 | Forward primer | CTTGCAAACCTTGGACAGCG |
| Reverse primer | ACAGCGATTGATTGACGGAGG | ||||
| TdG4 | TraesCS3B02G388100 | PREDICTED: Triticum dicoccoides UDP-glucuronic acid decarboxylase 1-like (LOC119277519), mRNA | 13.04 | Forward primer | GCCGCGTGGTTAGCAATTTT |
| Reverse primer | GCCATCAATCCAGCAACCAG |
Percentage changes in the physiological parameters of the Triticum dicoccum genotype PI94655 and check cultivar Bolal 2973 grown in high-B (10 mM B) conditions as compared to control.
| Accessions | PI94655 | Bolal 2973 |
|---|---|---|
| Traits/Species | Triticum turgidum subsp. dicoccum | Triticum aestivum subsp. aestivum |
| Root Length | −2 | −50 |
| Shoot Length | 4 | −38 |
| Root Fresh Weight | 3 | −108 |
| Shoot Fresh Weight | −7 | −30 |
| Root Dry Weight | 10 | −53 |
| Shoot Dry Weight | 16 | 0 |
Quality estimation results of sequencing data of shoots of T. dicoccum (Td) grown in high-B (10 mM B) conditions as compared to control (3.1 μM B), and the statistics of reference genome alignment.
| Parameters/Sample | Td_Control | Td_TB_ |
Parameters/Sample | Td_Control | Td_TB_ |
|---|---|---|---|---|---|
| Total Clean Reads (M) | 76.92 | 75.27 | Uniquely Gene Mapping Ratio (%) | 51.28 | 48.54 |
| Total Clean Bases (Gb) | 7.69 | 7.53 | Total Gene Number | 43,852 | 44,921 |
| Clean Reads Q20 (%) | 97.43 | 97.42 | Known Gene Number | 42,227 | 43,309 |
| Clean Reads Q30 (%) | 90.39 | 90.30 | Novel Gene Number | 1625 | 1612 |
| Total Genome Mapping Ratio (%) | 14.69 | 16.68 | Total Transcript Number | 49,471 | 51,449 |
| Uniquely Genome Mapping Ratio (%) | 4.84 | 5.50 | Known Transcript Number | 43,458 | 45,256 |
| Total Gene Mapping Ratio (%) | 87.60 | 85.93 | Novel Transcript Number | 6013 | 6193 |
Significant 15 KEGG pathways based on genes differentially expressed in high-B (TB 10 mM)-treated shoots of the T. dicoccum (Td) genotype, PI94655 compared to 3.1 μM B (control) treatment.
| Pathway | Pathway ID | No. of Genes Annotated in this Pathway | Level 1 | Level 2 |
|---|---|---|---|---|
| Metabolic pathways | ko01100 | 172 | Metabolism | Global and overview maps |
| Biosynthesis of secondary metabolites | ko01110 | 62 | Metabolism | Global and overview maps |
| Oxidative phosphorylation | ko00190 | 32 | Metabolism | Energy metabolism |
| Photosynthesis—antenna proteins | ko00196 | 21 | Metabolism | Energy metabolism |
| Ribosome | ko03010 | 19 | Genetic Information Processing | Translation |
| RNA transport | ko03013 | 19 | Genetic Information Processing | Translation |
| mRNA surveillance pathway | ko03015 | 18 | Genetic Information Processing | Translation |
| RNA polymerase | ko03020 | 17 | Genetic Information Processing | Transcription |
| Starch and sucrose metabolism | ko00500 | 17 | Metabolism | Carbohydrate metabolism |
| Phenylpropanoid biosynthesis | ko00940 | 16 | Metabolism | Biosynthesis of other secondary metabolites |
Supplementary Materials
The following supporting information can be downloaded at:
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; Pandey, Anamika 1
; Hamurcu, Mehmet 1 ; Rajpal, Vijay Rani 2 ; Vyhnanek, Tomas 3
; Topal, Ali 4 ; Raina, Soom Nath 5 ; Sait Gezgin 1 1 Department of Soil Science and Plant Nutrition, Faculty of Agriculture, Selcuk University, Konya 42079, Türkiye
2 Department of Botany, Hansraj College, University of Delhi, Delhi 110007, India
3 Department of Plant Biology, Faculty of AgriSciences, Mendel University in Brno, 61300 Brno, Czech Republic
4 Department of Field Crops, Faculty of Agriculture, Selcuk University, Konya 42079, Türkiye
5 Amity Institute of Biotechnology, Amity University, Noida 201313, India