Transcriptome-level dissection provides unique insights into the salt tolerance in spelt (Triticum spelta L.)

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Shengmao Zou, Guohao Han, Yanmin Qie, Siqi Li, Yuanwei Sui, Mengyi Liu, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9250361/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Soil salinity severely limits wheat production. Spelt ( Triticum spelta . L.) represents a valuable genetic resource for improving the salt tolerance of common wheat, but its underlying mechanisms remains poorly understood. Results Field evaluation of 22 spelt accessions identified 12 salt-tolerant genotypes. Further screening under a NaCl gradient (0–200 mM) selected three superior accessions CWI44398, CWI78968, and CWI44183. Under 150 mM NaCl, these three accessions exhibited greater shoot growth than the salt-tolerant control Jimai 22, while root development was more sensitive. Transcriptomic analysis revealed distinct expression patterns among genotypes, with common pathways including abiotic stress response and MAPK signaling, alongside genotype-specific pathways such as sulfur metabolism and fatty acid elongation. Expression patterns analysis under salt stress further confirmed the RNA-seq results, identifying four positively regulated genes and two genes not contributing to salt tolerance. Conclusions This study identified three salt-tolerant spelt accessions and elucidated conserved and genotype-specific molecular mechanisms, providing valuable resources for salt tolerance breeding in wheat. Spelt Salt tolerance RNA-seq Expression patterns Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Agricultural output worldwide faces a severe threat from increasing soil salinization [ 1 – 3 ]. The problem is widespread, impacting 20% of total arable land and 33% of irrigated areas, and is a key factor in reducing the yield of major food crops by over half [ 4 – 6 ]. This challenge is expected to intensify due to climate change [ 7 ], and its impact is pervasive, disrupting virtually all developmental stages of crops [ 8 , 9 ]. Understanding the molecular basis of salt tolerance is therefore essential for breeding stress-resilient cultivars and sustaining global food security. Common wheat ( Triticum aestivum L., AABBDD) is a major staple food crop cultivated globally [ 10 , 11 ]. However, Among cereal crops, wheat is classified as moderately salt-tolerant, with a higher salinity tolerance than rice, yet lower than that of sorghum and barley [ 12 , 13 ]. Spelt ( T . s pelta L.) is an ancient wheat sub-species cultivated as early as 6000 − 5000 BCE in the Near East and across Europe [ 14 ]. It is still grown on a small scale in countries, such as Germany, Sweden, and Switzerland. Spelt shares the same genomic constitution (AABBDD) as common wheat but is taxonomically classified as a subspecies of common wheat, distinguished by characteristics such as spike morphology [ 15 , 16 ]. Consequently, exploring the unique gene pool and elite traits of spelt could provide novel genetic resources for common wheat breeding. As an ancient wheat germplasm with rich genetic diversity and full cross-compatibility with common wheat, spelt wheat offers a scientifically sound and technically feasible strategy for mining salt tolerance genes, Particularly when combined with contemporary multi-omics analyses and gene editing technologies, this approach offers an effective means of investigating plant responses to abiotic stress [ 17 – 19 ]. Transcriptome analysis has been widely employed to identify salt stress-responsive genes in wheat at the genome-wide level, and a considerable number of related studies have been documented to date [ 20 – 22 ]. Among the regulatory mechanisms underlying salt tolerance in wheat, the HKT-mediated sodium ion exclusion pathway and the SRO-mediated reactive oxygen species (ROS) homeostasis pathway are two of the most well-established and intensively investigated systems [ 3 , 23 ]. Recent efforts have also focused on elucidating salt tolerance mechanisms in landrace wheat germplasms using RNA-seq-based approaches. As an example, a time-course transcriptome analysis was performed on seedlings of the Chinese elite cultivar Xiaoyan 22, resulting in the identification of 11,842 differentially expressed genes (DEGs) across six time points following salt treatment. Functional enrichment analysis revealed that these DEGs were predominantly associated with seven biological processes related to salt adaptation, including hormone signaling, oxidative stress defense, ion homeostasis, osmotic adjustment, water stress response, salt perception and signal transduction, as well as transcription factor-mediated regulatory networks [ 24 – 26 ]. These observations underscore the utility of transcriptome profiling in capturing dynamic gene expression changes and pinpointing candidate genes with specific temporal response patterns under salt stress [ 17 , 22 ]. This approach provides a robust framework for deciphering the molecular components and regulatory circuits that govern salt tolerance in plants. In wheat, transcriptomic analyses have been applied across different growth stages and tissues, although the majority of studies to date have concentrated on roots, stems, and leaves at the seedling stage [ 19 , 27 ]. Despite the progress made in wheat salt tolerance, investigations into the salt tolerance mechanisms of spelt remain limited [ 28 – 30 ]. In particular, transcriptome-based studies comparing spelt accessions with contrasting salt tolerance are rarely reported. Therefore, genome-wide identification of salt stress-responsive genes through transcriptome analysis in spelta offers a promising opportunity to elucidate its underlying regulatory mechanisms and holds significant research relevance [ 31 ]. In the present study, we screened a panel of spelt germplasm and identified accessions exhibiting differential salt tolerance at the seedling stage. Subsequently, we conducted a comparative transcriptomic analysis to characterize the early salt stress response in the leaves of spelt accessions with contrasting salinity tolerance, aiming to uncover the transcriptional dynamics and molecular pathways that distinguish their adaptive responses. Results Identification and selection of salt-tolerant spelt wheat genotypes Field evaluation of 22 spelt accessions under saline conditions in Dongying, China, revealed substantial variation in salt tolerance. Based on adult-stage agronomic traits, including plant height, thousand-kernel weight (TKW), and grain yield per plant (GYPP) (Table 1), 12 accessions were classified as salt-tolerant. The remaining 10 accessions showed severe salt sensitivity. Among them, CWI17370, CWI17942, CWI18042 and CWI18043 were failed germination. CWI18080, CWI18090, CWI18453, CWI18476, CWI44218 and CWI80462 showed growth arrest, leaf necrosis, or premature senescence before reaching the adult stage, with no effective panicle formation. To determine the appropriate salt concentration and identify the most suitable genotypes for subsequent seedling-stage salt tolerance assays and transcriptome sequencing, a preliminary screening was conducted using these 12 salt-tolerant spelt accessions under a NaCl concentration gradient (0, 50, 100, 150 and 200 mM). After seven days of treatment, seedling phenotypes were evaluated. The results showed that under 50 mM NaCl, no significant phenotypic differences were observed among these accessions compared to the control, indicating a mild stress condition insufficient for discriminating salt tolerance levels. At 100 mM level, moderate growth inhibition was observed, but the phenotypic variation among accessions remained limited (Table S1 ). In contrast, under 150 mM level, clear and consistent phenotypic divergence emerged, with three accessions CWI44398, CWI78968, and CWI44183 exhibiting superior growth performance, characterized by higher shoot and root biomass and less severe chlorosis compared to the other nine accessions. Under 200 mM level, severe stress symptoms, including pronounced growth arrest and leaf necrosis, were observed across most accessions, making it difficult to effectively distinguish tolerance levels. Based on these observations, 150 mM level was selected as the optimal concentration for further experiments, and these three accessions (CWI44398, CWI78968, and CWI44183) showing superior salt tolerance at this concentration were chosen for subsequent transcriptome sequencing analysis. Phenotypic variation among three spelt accessions under salt stress Under 150 mM NaCl treatment, with wheat cultivar Jimai 22 serving as the salt-tolerant control, CWI44398, CWI78968, and CWI44183 exhibited superior salt tolerance, while their root development was more sensitive to salt stress (Fig. 1 ). To investigate the phenotypic differences among the genotypes, multiple salt tolerance-related traits were measured. Comparative analysis of phenotypic variations revealed significant differences between salt-treated and control groups in shoot length, primary root length, shoot fresh weight, root fresh weight, total root fresh weight, shoot dry weight, and root dry weight. These findings indicate the sustained effect of salt treatment on the three salt-tolerant spelt genotypes. Notably, under salt stress, the shoot length of the three salt-tolerant spelt wheat genotypes demonstrated superior salt tolerance compared to the Jimai 22. Regarding root dry weight, CWI78968 and CWI44183 exhibited higher salt tolerance than CWI44398, suggesting genotype-specific responses to salt treatment (Fig. 2 ). Transcriptomic differences between control and salt-treated groups at the seedling stage Given that early salt tolerance in wheat is critically influenced by the seedling stage, we profiled the transcriptomes of CWI44398, CWI78968, and CWI44183 under both control and salt-treated conditions to elucidate the biological basis for differential salt tolerance. Principal Component Analysis (PCA) was performed using the first three principal components to distinguish differences among sample groups. The results revealed clear separations between the control and salt-treated groups for the genotypes CWI44398, CWI78968, and CWI44183, indicating substantial genome-wide transcriptional differences across treatment conditions and high reproducibility within each sample group (Fig. 3 ). DEGs were then obtained for each comparison group (Table S2 ). Subsequently, DEGs under salt stress compared to control conditions were identified for each genotype. In CWI44398 and CWI78968, the numbers of up-regulated DEGs during the seedling stage significantly exceeded those of down-regulated DEGs. In contrast, CWI44183 exhibited a significantly higher number of down-regulated than up-regulated ones, suggesting differential salt tolerance responses among these genotypes (Fig. 4 A). The DEGs were further classified into genotype-specific and shared categories. Under salt stress, CWI44398 displayed 1,005 genotype-specific down-regulated and 2,049 up-regulated genes; CWI78968 exhibited 915 down-regulated and 770 up-regulated genes; and CWI44183 showed 2,441 down-regulated and 547 up-regulated genes. Additionally, 399 genes were commonly down-regulated and 665 genes commonly up-regulated across all the three genotypes (Fig. 4 B). It can be observed that under salt stress and control conditions, the highly expressed DEGs were clustered in distinct regions. Moreover, across different wheat varieties subjected to the same treatment, the highly expressed DEGs were mostly concentrated in similar regions. These patterns reveal the differences in DEGs between the salt stress and control groups, and also suggest that the three spelt accessions share a similar salt tolerance mechanism (Fig. 4 C). Functional categories and pathways associated with seedling-stage salt tolerance Based on a multi-dimensional transcriptomic analysis, all DEGs were categorized into four groups: common DEGs shared among the three genotypes, and genotype-specific DEGs for CWI44398, CWI78968, and CWI44183, respectively. These distinct categories of DEGs provide complementary insights into the biological basis of salt tolerance in wheat. Specifically, the common DEGs reflect conserved transcriptional responses associated with salt tolerance shared across CWI44398, CWI78968, and CWI44183, whereas the genotype-specific DEGs highlight unique adaptive mechanisms characteristic of each individual genotype. To elucidate the functional categories and regulatory pathways associated with salt tolerance during the wheat seedling stage, all DEGs were used for GO and KEGG analyses (Table S3 ). GO analysis showed that DEGs identified at this stage were predominantly enriched in biological process terms, followed by molecular function terms. Enrichment analysis based on common DEGs shared among CWI44398, CWI78968, and CWI44183 revealed several conserved pathways under salt stress. These included response to abiotic stimulus (GO:0009628), xenobiotic transmembrane transport (GO:0006855), polysaccharide metabolic process (GO:0005976), oxidoreductase activity (GO:0016491), and vitamin binding (GO:0019842). These findings suggest that these biological processes represent common features of the salt stress response in these genotypes. The salt tolerance of CWI44398 was specifically associated with sulfur compound metabolic process (GO:0006790), oligosaccharide metabolic process (GO:0009311), calcium ion binding (GO:0005538), and amylase activity (GO:0004553). For CWI78968, specific associations included small molecule metabolic process (GO:0044281), cellular polysaccharide biosynthetic process (GO:0034637), carboxy-lyase activity (GO:0016831), and primary active transmembrane transporter activity (GO:0015399). In contrast, the salt tolerance of CWI44183 was specifically linked to metal ion transmembrane transporter activity (GO:0046873). In summary, the enriched GO terms derived from the genotype-specific DEGs differed substantially among CWI44398, CWI78968, and CWI44183, highlighting distinct molecular mechanisms underlying their differential salt tolerance (Fig. 5 A-C). KEGG enrichment analysis showed that biosynthesis of amino acids (ko01230), starch and sucrose metabolism (ko00500), α-Linolenic acid metabolism (ko00592), and MAPK signaling pathway – plant (ko04016) were identified as core metabolic pathways commonly associated with salt tolerance across all three wheat genotypes. Arginine biosynthesis (ko00220), Fatty acid metabolism (ko01212), and nitrogen metabolism (ko00910) were specifically enriched in the salt-tolerant genotype CWI44398. Fatty acid elongation (ko00062) was uniquely associated with CWI78968, while glyoxylate and dicarboxylate metabolism (ko00630) was specific to CWI44183 (Fig. 5 D). These findings further elucidate the distinct molecular mechanisms underlying salt tolerance in these spelta genotypes. . Expression pattern analysis under salt stress Six DEGs from the transcriptome analysis, including TraesCS3A03G0366700 , TraesCS2B03G0234400 , TraesCS3D03G0353700 , TraesCS2A03G0589200 , TraesCS7A03G0921600 and TraesCS2B03G0309400 were selected for qRT-PCR validation in CWI44398, CWI78968, and CWI44183 (Table S4 ). Four genes were identified as positive regulators of salt tolerance in spelt, based on their up-regulation under salt stress. TraesCS3A03G0366700 , another ubiquitin-conjugating enzyme (UBC), and TraesCS2B03G0234400 , encoding a dirigent protein with a jacalin-like lectin domain, were significantly up-regulated, with the latter potentially contributing to cell wall modification and antioxidant defense (Fig. 6 A& 6 B). TraesCS3D03G0353700 , encoding a ubiquitin-conjugating enzyme E2, was up-regulated, suggesting its involvement in protein degradation pathways related to ion homeostasis (Fig. 6 C). TraesCS2A03G0589200 , encoding a carboxylesterase 15, was also up-regulated, implicating it in membrane stability and Na⁺/K⁺ balance (Fig. 6 D). The consistent up-regulation of these four genes in both qRT-PCR and RNA-seq analyses confirms their positive contribution to salt tolerance in the three spelt genotypes. Conversely, two genes exhibited expression patterns inconsistent with a positive role in salt tolerance. TraesCS7A03G0921600 , encoding a polyamine oxidase (PAO), was up-regulated under salt stress. Despite the known roles of PAO enzymes in stress signaling, this expression pattern suggests that the mechanism encoded by this gene is not a major driver of salt tolerance in these genotypes (Fig. 6 E). Similarly, TraesCS2B03G0309400 , encoding a class III peroxidase, was down-regulated under 150 mM NaCl treatment, as confirmed by both qRT-PCR and RNA-seq, indicating that this peroxidase-mediated pathway does not contribute to the observed salt tolerance (Fig. 6 F). Discussion Salt tolerance is a complex trait governed by multiple genes and is closely associated with both environmental and genetic factors [ 32 , 33 ]. Wheat responds to salt stress through diverse morphological and physiological pathways, making it difficult to accurately assess salt tolerance using a single criterion [ 34 , 35 ]. In this study, we integrated field-based phenotypic screening with seedling-stage physiological and transcriptomic analyses to identify and characterize salt-tolerant spelt accessions. Three accessions CWI44398, CWI78968, and CWI44183 were selected for their superior salt tolerance at both adult and seedling stages. Our findings reveal that these accessions exhibit enhanced shoot growth under salt stress compared to the reference cultivar Jimai 22, while showing greater sensitivity in root development with distinct genotype-specific variation. Transcriptomic profiling further uncovered both conserved and genotype-specific molecular pathways underlying their differential salt tolerance, providing valuable insights into the complex regulatory networks governing salt stress responses in spelt. The differential responses between shoot and root tissues observed in this study are consistent with previous reports indicating that roots are often more sensitive to salt stress due to direct exposure to the rhizosphere environment [ 36 ]. The superior shoot growth of the three spelt accessions under 150 mM NaCl suggests that these genotypes maintain efficient ion exclusion or compartmentalization mechanisms that protect photosynthetic tissues from salt-induced damage. However, the greater reduction in root biomass, particularly in CWI44398, indicates that root sensitivity may be a trade-off for shoot tolerance. Such genotype-specific root responses have been documented in other wheat relatives, including wild emmer wheat ( T. dicoccoides ) and Aegilops species, where root architecture plasticity contributes to overall salt adaptation [ 36 ]. The variation in root dry weight among the three accessions further supports the notion that salt tolerance is a complex trait governed by multiple genetic determinants that may act independently in different tissues. The transcriptomic analysis revealed distinct expression patterns among the three accessions, providing molecular evidence for the phenotypic divergence observed. PCA clearly separated control and salt-treated groups, indicating robust transcriptional reprogramming in response to salt stress. Notably, CWI44398 and CWI78968 exhibited more up-regulated than down-regulated DEGs, whereas CWI44183 showed the opposite pattern. This contrasting transcriptional landscape suggests that CWI44183 may rely more on the suppression of growth-related genes or the activation of stress-avoidance strategies, a phenomenon observed in other stress-tolerant plant species [ 37 ]. GO enrichment analysis revealed common biological processes among the three accessions, including response to abiotic stimulus and polysaccharide metabolism, representing core salt stress responses. Genotype-specific GO terms indicated distinct adaptive strategies: CWI44398 was associated with sulfur and oligosaccharide metabolism, suggesting osmotic adjustment; CWI78968 showed enrichment in polysaccharide biosynthesis, implicating cell wall remodeling; and CWI44183 was uniquely enriched in metal ion transport, pointing to ion homeostasis. These divergent enrichments highlight multiple molecular routes to salt tolerance in spelt wheat, consistent with the concept of ‘alternative adaptive pathways’ proposed in recent plant stress studies [ 38 ]. KEGG pathway analysis further supported these findings. The plant MAPK signaling pathway, identified as a common pathway across all three accessions, is a well-established regulator of stress responses that mediates signal transduction from stress perception to downstream transcriptional activation [ 39 ]. Starch and sucrose metabolism, another common pathway, likely reflects adjustments in carbon partitioning and energy metabolism under stress, as previously reported in salt-tolerant rice and barley genotypes [ 40 ]. The genotype-specific pathways arginine biosynthesis and nitrogen metabolism in CWI44398, fatty acid elongation in CWI78968, and glyoxylate and dicarboxylate metabolism in CWI44183 further underscore the diversity of metabolic adjustments employed by different genotypes to cope with salinity. Four genes were then identified as positive regulators based on their consistent up-regulation under salt stress. TraesCS3D03G0353700 and TraesCS3A03G0366700 , encoding ubiquitin-conjugating enzymes (E2), are involved in the ubiquitin-26S proteasome pathway, which mediates targeted protein degradation critical for ion homeostasis [ 41 ]. TraesCS2A03G0589200 , encoding a carboxylesterase, likely contributes to membrane stability and Na⁺/K⁺ balance [ 42 ]. TraesCS2B03G0234400 , encoding a dirigent protein, is implicated in cell wall reinforcement [ 43 ]. The coordinated up-regulation of these genes across the three accessions suggests they represent core components of salt tolerance in spelt wheat. Conversely, two genes exhibited expression patterns inconsistent with positive regulatory roles. TraesCS2B03G0309400 , encoding a class III peroxidase, was down-regulated under salt stress, despite its typical association with stress responses [ 44 ]. TraesCS7A03G0921600 , encoding a PAO, was up-regulated, yet this expression pattern may not translate into functional contribution, possibly due to post-transcriptional regulation or tissue-specific expression not captured in whole-seedling RNA-seq analysis [ 45 ]. Spelt, as a progenitor of cultivated hexaploid wheat, harbors substantial genetic diversity that can be exploited for introgression breeding [ 46 ]. These three salt-tolerant spelt accessions identified in this study represent valuable genetic resources for wheat improvement. Conclusion In this study, three salt-tolerant spelt accessions CWI44398, CWI78968, and CWI44183 were identified through field screening and seedling-stage evaluation. Under 150 mM NaCl treatment, these accessions exhibited superior shoot growth compared to the salt-tolerant control Jimai 22, while root development was more sensitive with genotype-specific variation. Transcriptomic analysis revealed both conserved pathways and genotype-specific pathways underlying salt tolerance. Quantitative real-time (qRT-PCR) validation confirmed the expression patterns of key genes, identifying four positive regulators and two genes not contributing to tolerance. These findings provide valuable genetic resources and molecular insights for improving salt tolerance in wheat. Materials and Methods Plant materials and salt treatment A total of 22 spelt accessions were provided by Prof. Hongxing Xu from Henan University, Kaifeng, China. Wheat cultivar Jimai 22 served as the salt-tolerant control [ 47 ]. All 22 spelt accessions were firstly evaluated for salt tolerance in a saline-alkali field at Maotuo, Dongying, China [ 12 ]. At harvest, plant height, grains per spike, the thousand-kernel weight (TKW) and grain yield per plant (GYPP) were recorded for each genotype. Following the screening and identification of salt-tolerant wheat varieties, a preliminary experiment was conducted using a salt stress gradient to evaluate the phenotypes of the selected varieties. Among the salt-tolerant spelt accessions, three ones with superior phenotypic performance were selected for further assessment of seedling-stage salt tolerance. For each accession, 100 plump and uniformly sized seeds were selected. The seeds were surface-sterilized with 1.5% sodium hypochlorite for 10 minutes, thoroughly rinsed with distilled water, and then germinated on moistened filter paper in Petri dishes (9 cm diameter) for 2–3 days at 25℃ [ 19 ]. Uniformly germinated seeds were transferred to hydroponic culture in a greenhouse and grown in half-strength Hoagland’s solution. After 7–10 days, the seedlings were subjected to two treatments for 7 days: (1) Control (Hoagland’s solution only) and 150 mM NaCl. The experiment was arranged in a completely randomized design with three biological replicates per treatment. At 7 days post-treatment, leaf samples were collected from the seedlings, immediately frozen in liquid nitrogen, and stored at − 80°C for subsequent RNA-seq analysis. Simultaneously, shoot height, root length, shoot fresh weight, root fresh weight, shoot dry weight, and root dry weight were measured to evaluate salt tolerance. RNA extraction, library construction, and transcriptome sequencing Total RNA was isolated using RNAprep Pure Polysaccharide Polyphenol Plant Total RNA Extraction Kit (Tiangen Biotech, Beijing, China) according to the manufacturer’s protocol. The concentration and purity of the extracted RNA were assessed using the Agilent 5400 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA), with the OD260/280 and OD260/230 ratios monitored to ensure protein and polyphenol/polysaccharide contamination were within acceptable limits (OD260/280 ≥ 1.8, OD260/230 ≥ 1.5). The integrity of the RNA was evaluated by agarose gel electrophoresis to visualize distinct 28S and 18S ribosomal RNA bands. Furthermore, the RNA integrity number (RIN) was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Only high-quality RNA samples with a RIN value ≥ 8.0 were used for subsequent cDNA library construction. A total of 1 µg of high-quality RNA per sample was used as input material for library preparation. Sequencing libraries were generated using Fast RNA-seq Lib Prep Kit V2 (ABclonal, Wuhan, Hubei, China) following the manufacturer’s recommendations. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads and then fragmented. The first-strand cDNA was synthesized using random hexamer primers and reverse transcriptase, followed by second-strand cDNA synthesis. After library construction, the double-stranded cDNA was subjected to end repair, A-tailing, and ligation with Illumina adapters. The library fragments were purified and enriched by PCR amplification to create the final cDNA library. The library quality was assessed on the Agilent 2100 Bioanalyzer to ensure the correct insert size, and the concentration was quantified using Qubit® 2.0 Fluorometer (Invitrogen, CA, USA) and qRT-PCR. Finally, the libraries were sequenced on the Illumina NovaSeq X Plus platform (Illumina Inc., San Diego, CA, USA) to generate150 bp paired-end reads. Data filtering and transcriptome assembly Raw data in FASTQ format were first processed using Fastp v0.23.1 [ 48 ]. In this step, clean data were obtained by removing reads containing adapter contamination, poly-N stretches, and low-quality reads from the raw data. Simultaneously, the Q20, Q30, and GC content of the clean data were calculated to ensure data quality for downstream analyses. All downstream analyses were based on high-quality clean reads. The clean reads were aligned to the reference genome of IWGSC RefSeq v2.1 using HISAT2 (v2.2.1) with default parameters [ 49 ]. Transcript assembly was performed using StringTie (v2.2.1) [ 50 ], which reconstructs transcripts through a network flow algorithm with an optional de novo assembly step. Reads that mapped to multiple genomic locations or had a mapping quality score below 10 were filtered out using featureCounts (v2.06) to ensure the accuracy of subsequent quantification [ 51 ]. DEGs analysis the expression level for each gene was quantified using the fragments per kilobase of exon model per million mapped fragments (FPKM) method[ 52 ]. Based on the genomic alignment positions, the featureCounts tool from the Subread software package was employed to count the number of reads mapped to the genomic regions for each gene, including newly predicted ones. Reads with low mapping quality (MAPQ < 10), non-paired reads, and reads aligned to multiple genomic locations were filtered out prior to quantification. Following expression quantification, statistical analyses were performed to identify DEGs under different treatment conditions. The differential expression analysis consisted of three main steps. First, raw read counts were normalized to correct for sequencing depth variations. Second, statistical models were applied to calculate p -values, representing the probability of differential expression under the null hypothesis. Finally, multiple hypothesis testing correction was performed to control the false discovery rate (FDR) [ 53 ]. Functional annotation and pathway analysis of DEGs To elucidate the functional implications of the DEGs, we performed GO and KEGG enrichment analyses using the clusterProfiler software (v4.8.1). For GO enrichment, gene length bias was corrected during the analysis [ 54 ]. GO terms with a corrected p-value of less than 0.05 were considered significantly enriched among the DEGs. For pathway analysis, we utilized the KEGG database ( https://www.kegg.jp/ ) to identify statistically enriched metabolic or signaling pathways associated with the DEGs, employing the same software package and significance threshold [ 55 ]. qRT-PCR analysis CWI44398, CWI78968, and CWI44183 were treated using 150 mM NaCI and leaves were sampled at 0, 4, 12, 24, 48, 72, 120 and 168 hpi. Total RNA was isolated from the infected leaves using TRIzol reagent (Invitrogen, Waltham, USA), and approximately 2 µg of RNA was employed for reverse transcription using a FastQuant RT Kit (Tiangen, Beijing, China). The qRT-PCR assays were performed on the Bio-Rad CFX Connect real-time PCR system (BIO-RAD, USA), and relative expression of the selected genes was calculated using the 2 −ΔΔCt method [ 56 – 57 ]. The wheat gene TaActin served as the internal control [ 58 – 59 ]. Abbreviations BCE Before common era HKT High-affinity potassium transporter ROS Reactive oxygen species RNA-seq RNA sequencing DEGs Differentially expressed genes TKW Thousand kernel weight GYPP grain yield per plant GO Gene ontology KEGG Kyoto encyclopedia of genes and genomes MAPK Mitogen-activated protein kinase qRT-PCR Real-time quantitative PCR UBC Ubiquitin-conjugating enzyme OD Optical density RIN RNA integrity number PCA Principal component analysis FPKM Fragments per kilobase of transcript per million mapped reads FDR False discovery rate Declarations Acknowledgments We are grateful to Prof. Hongxing Xu from Henan University for supplying the experimental materials. Author contributions SZ performed the seed germination, salt treatment and sample preparation; SZ, GP, ML, YS and JZ prepared the naked seeds; SZ, YL and DL conducted the qRT-PCR; GH, YQ, DX, NY and SL analyzed the RNA-seq data and prepared the manuscript; ZC, DL and CL were the funding administration. SZ, GH and YJ designed the experiment and revised the manuscript; PM supervised the project. Funding This research was financially supported by Key Research and Development (R&D) plan project of Shandong Province (2023LZGC009-4-4), Science and Technology Demonstration Project of Shandong Province (2024SFGC0402), National Natural Science Foundation of China (32301923), Natural Science Foundation of Shandong Province (ZR2023QC203, ZR2023QC292) and the Graduate Innovation Foundation of Yantai University (GGIFYTU2527). Data availability The RNA-seq data have been deposited with the National Center for Biotechnology Information: Submission ID SRR37547788. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details Yantai Key Laboratory of Characteristic Agricultural Biological Resources Conservation and Germplasm Innovative Utilization, College of Life Sciences, Yantai University, Yantai 264005, China Shengmao Zou, Siqi Li, Yuanwei Sui, Mengyi Liu, Ningning Yu, Dongming Li, Yuting Liang, Guantong Pan, Yuli Jin, Pengtao Ma Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China Guohao Han Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Key Laboratory of Crop Genetic and Breeding, Shijiazhuang 050035, China Yanmin Qie, Lige Geng Crop Research Institute, Shandong Academy of Agricultural Sciences/National Engineering Research Center for Wheat and Maize/National Key Laboratory of Wheat Breeding/Key Laboratory of Wheat Biology and Genetic Improvement in the North Huang-Huai River Valley/Shandong Wheat Technology Innovation Center, Jinan 250100, China Jiadong Zhang, Cheng Liu College of Agronomy, Qingdao Agricultural University, Qingdao, Shandong, 266109, China Jiadong Zhang, Dengan Xu, Cheng Liu National Center of Technology Innovation for Comprehensive Utilization of Saline-Alkali Land, Dongying 257347, China Jiadong Zhang, Cheng Liu Corresponding authors Correspondence to Pengtao Ma, Yuli Jin or Cheng Liu References Kojonna T, Suttiyut T, Khunpolwattana N, Pongpanich M, Suriya-Arunroj D, Comai L, et al. 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Nucleic Acids Res. 2025;53(D1):D672–d677. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2 −ΔΔCT method. Methods. 2001;25(4):402–408. Jin YL, Li WL, Li YX, Li DL, Yan HF, Chen SS, et al. Pm37 as a susceptible Sr22 allele confers resistance to wheat powdery mildew and leaf rust. Nat Commun. Lu P, Guo L, Wang Z, Li B, Li J, Li Y, et al. A rare gain of function mutation in a wheat tandem kinase confers resistance to powdery mildew. Nat Commun. 2020;11(1):680. Zhang JD, Yang H, Han GH, Liu RS, Li YX, Li JT, et al. Fine mapping of Pm71 , a new powdery mildew resistance gene from emmer wheat. Crop J. 2025;13(1):62-68. Additional Declarations No competing interests reported. Supplementary Files TableS1.docx Supplementary table legends Table S1 Phenotypes of 12 salt-tolerant spelt accessions under a preliminary salt stress gradient experiment (0, 50, 100, 150, 200 mM NaCl). TableS2.xlsx Table S2 Differentially expressed genes (DEGs) between the treatment and CK of CWI44398, CWI78968, and CWI44183. TableS3.xlsx Table S3 Detailed information on GO enrichment and KEGG pathway annotations for differentially expressed genes (DEGs) in CWI44398, CWI78968, and CWI44183. TableS4.docx Table S4 Primers for the qRT-PCR of the six selected differentially expressed genes (DEGs). Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Apr, 2026 Reviews received at journal 14 Apr, 2026 Reviews received at journal 13 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviews received at journal 07 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviewers invited by journal 02 Apr, 2026 Editor invited by journal 31 Mar, 2026 Editor assigned by journal 30 Mar, 2026 Submission checks completed at journal 30 Mar, 2026 First submitted to journal 28 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9250361","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618500602,"identity":"bd7fdaa1-539c-4386-8f90-2a72f01fe995","order_by":0,"name":"Shengmao Zou","email":"","orcid":"","institution":"Yantai University","correspondingAuthor":false,"prefix":"","firstName":"Shengmao","middleName":"","lastName":"Zou","suffix":""},{"id":618500604,"identity":"39a02237-752e-4e1f-9b82-ee905dd28772","order_by":1,"name":"Guohao Han","email":"","orcid":"","institution":"Chinese Academy of 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stress).\u003c/p\u003e","description":"","filename":"FIgure.1.png","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/5b320ef0e53d68c1ab7eb3d5.png"},{"id":106455478,"identity":"ec5bf1a3-1588-4797-871d-8041c856311a","added_by":"auto","created_at":"2026-04-08 17:50:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":151875,"visible":true,"origin":"","legend":"\u003cp\u003ePhenotypic differences among three salt-tolerant spelt accessions (CWI44398, CWI78968 and CWI44183) and the salt-tolerant control wheat Jimai 22 (JM 22) under CK and salt stress conditions. (CK: control, Treatment: 150 mM NaCl salt stress, Observed traits were measured in units such as centimeters and grams).\u003c/p\u003e","description":"","filename":"Figure.2.png","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/9fe4bae3b0195ddcd9c5f364.png"},{"id":106455477,"identity":"076f7ece-5000-45d0-b0fd-541cdcc332ef","added_by":"auto","created_at":"2026-04-08 17:50:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":897161,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional principal component analysis (PCA) plot of genome-wide gene expression.\u003c/p\u003e","description":"","filename":"Figure.3.png","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/874bdd249776dddbc3a3efce.png"},{"id":106455472,"identity":"6a49478e-a733-49e4-8921-7ce9279a61a7","added_by":"auto","created_at":"2026-04-08 17:50:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":23628005,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially expressed genes under different conditions. \u003cstrong\u003eA\u003c/strong\u003e Blue dots represent significantly down-regulated genes, and red dots represent significantly up-regulated genes in CWI44398, CWI78968 and CWI44183, respectively. \u003cstrong\u003eB\u003c/strong\u003e Comparison of up-regulated and down-regulated genes in three salt-tolerant spelt accessions (CWI44398, CWI78968 and CWI44183) under salt stress conditions. \u003cstrong\u003eC \u003c/strong\u003eIn the heatmap, red indicates higher expression levels, while blue indicates lower expression levels. Heatmap of DEG expression levels among the three salt-tolerant spelt accessions CWI44398, CWI78968 and CWI44183.\u003c/p\u003e","description":"","filename":"Figure.4.png","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/fcb509254c965cc1d4a67336.png"},{"id":106455474,"identity":"259f1761-f016-4f55-b488-4d40def89719","added_by":"auto","created_at":"2026-04-08 17:50:42","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":18372529,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e Comparison of differentially expressed genes (DEGs) in biological processes among the three salt-tolerant spelt accessions CWI44398, CWI78968 and CWI44183. \u003cstrong\u003eB\u003c/strong\u003e Comparison of DEGs in cellular components among the three salt-tolerant spelt accessions CWI44398, CWI78968 and CWI44183. \u003cstrong\u003eC\u003c/strong\u003e Comparison of DEGs in molecular functions among the three salt-tolerant spelt wheat varieties CWI44398, CWI78968 and CWI44183. \u003cstrong\u003eD\u003c/strong\u003eComparison of KEGG pathways among the three salt-tolerant spelt accessions CWI44398, CWI78968 and CWI44183.\u003c/p\u003e","description":"","filename":"Figure.5.png","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/db2615fff8e9289fdec436a2.png"},{"id":106724143,"identity":"3457dbdf-567e-4ff2-ab1c-48f717e116d9","added_by":"auto","created_at":"2026-04-12 18:26:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1024656,"visible":true,"origin":"","legend":"\u003cp\u003eExpression patterns of \u003cem\u003eTraesCS3A03G0366700\u003c/em\u003e, \u003cem\u003eTraesCS2B03G0234400\u003c/em\u003e, \u003cem\u003eTraesCS3D03G0353700\u003c/em\u003e, \u003cem\u003eTraesCS2A03G0589200\u003c/em\u003e,\u003cem\u003eTraesCS7A03G0921600\u003c/em\u003e and \u003cem\u003eTraesCS2B03G0309400\u003c/em\u003e in CWI44398, CWI78968, and CWI44183 at 0, 4, 12, 24, 48, 72, 120 and 168 hours post-salt stress (CK: control, Treatment: 150mM NaCl). Error bars represent standard deviation (SD) based on three independent repeats. Asterisks indicate significant differences between the Treatment and CK at each time point for the three materials CWI44398, CWI78968, and CWI44183 (\u003cem\u003et\u003c/em\u003e-test). (\u003cem\u003e*P \u003c/em\u003e\u0026lt; 0.05, \u003cem\u003e**P \u003c/em\u003e\u0026lt; 0.01, \u003cem\u003e***P \u003c/em\u003e\u0026lt; 0.001, \u003cem\u003e**** P \u003c/em\u003e\u0026lt; 0.0001 ns: not significant); \u003cem\u003eTaActin\u003c/em\u003ewas used as the internal control.\u003c/p\u003e","description":"","filename":"Figure.6.png","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/682713ff9113b97c6ae88a32.png"},{"id":109295866,"identity":"84dce8b3-a5ce-4a0e-a39a-400041d4432e","added_by":"auto","created_at":"2026-05-15 08:38:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":61227365,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/ace6954e-3b56-4524-9f9e-8d73391f75f6.pdf"},{"id":106455471,"identity":"d83435d4-53ed-4efa-ac3d-4ce173a228d4","added_by":"auto","created_at":"2026-04-08 17:50:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":202957,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table legends\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S1 \u003c/strong\u003ePhenotypes of 12 salt-tolerant spelt accessions under a preliminary salt stress gradient experiment (0, 50, 100, 150, 200 mM NaCl).\u003c/p\u003e","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/c53a7f901f230e58152b3ce5.docx"},{"id":106455479,"identity":"f89a9434-30e9-4283-956f-1dfa50f51f08","added_by":"auto","created_at":"2026-04-08 17:50:43","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3587296,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S2 \u003c/strong\u003eDifferentially expressed genes (DEGs) between the treatment and CK of CWI44398, CWI78968, and CWI44183.\u003c/p\u003e","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/9a1a90a1bb72dc4b9a0135c6.xlsx"},{"id":106724337,"identity":"f6872820-b36d-482e-a68d-a2d3cafd2761","added_by":"auto","created_at":"2026-04-12 18:27:34","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":421186,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S3 \u003c/strong\u003eDetailed information on GO enrichment and KEGG pathway annotations for differentially expressed genes (DEGs) in CWI44398, CWI78968, and CWI44183.\u003c/p\u003e","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/80dfda7983126038dee2f027.xlsx"},{"id":106724359,"identity":"c1f03fa7-5e61-496f-a454-b5f2c5005d62","added_by":"auto","created_at":"2026-04-12 18:27:43","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":15353,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S4 \u003c/strong\u003ePrimers for the qRT-PCR of the six selected differentially expressed genes (DEGs).\u003c/p\u003e","description":"","filename":"TableS4.docx","url":"https://assets-eu.researchsquare.com/files/rs-9250361/v1/21acd91cfb45fa91a8ec9046.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transcriptome-level dissection provides unique insights into the salt tolerance in spelt (Triticum spelta L.)","fulltext":[{"header":"Background","content":"\u003cp\u003eAgricultural output worldwide faces a severe threat from increasing soil salinization [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The problem is widespread, impacting 20% of total arable land and 33% of irrigated areas, and is a key factor in reducing the yield of major food crops by over half [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This challenge is expected to intensify due to climate change [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and its impact is pervasive, disrupting virtually all developmental stages of crops [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Understanding the molecular basis of salt tolerance is therefore essential for breeding stress-resilient cultivars and sustaining global food security.\u003c/p\u003e \u003cp\u003eCommon wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L., AABBDD) is a major staple food crop cultivated globally [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, Among cereal crops, wheat is classified as moderately salt-tolerant, with a higher salinity tolerance than rice, yet lower than that of sorghum and barley [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Spelt (\u003cem\u003eT\u003c/em\u003e. s\u003cem\u003epelta\u003c/em\u003e L.) is an ancient wheat sub-species cultivated as early as 6000\u0026thinsp;\u0026minus;\u0026thinsp;5000 BCE in the Near East and across Europe [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. It is still grown on a small scale in countries, such as Germany, Sweden, and Switzerland. Spelt shares the same genomic constitution (AABBDD) as common wheat but is taxonomically classified as a subspecies of common wheat, distinguished by characteristics such as spike morphology [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Consequently, exploring the unique gene pool and elite traits of spelt could provide novel genetic resources for common wheat breeding. As an ancient wheat germplasm with rich genetic diversity and full cross-compatibility with common wheat, spelt wheat offers a scientifically sound and technically feasible strategy for mining salt tolerance genes, Particularly when combined with contemporary multi-omics analyses and gene editing technologies, this approach offers an effective means of investigating plant responses to abiotic stress [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTranscriptome analysis has been widely employed to identify salt stress-responsive genes in wheat at the genome-wide level, and a considerable number of related studies have been documented to date [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Among the regulatory mechanisms underlying salt tolerance in wheat, the HKT-mediated sodium ion exclusion pathway and the SRO-mediated reactive oxygen species (ROS) homeostasis pathway are two of the most well-established and intensively investigated systems [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Recent efforts have also focused on elucidating salt tolerance mechanisms in landrace wheat germplasms using RNA-seq-based approaches. As an example, a time-course transcriptome analysis was performed on seedlings of the Chinese elite cultivar Xiaoyan 22, resulting in the identification of 11,842 differentially expressed genes (DEGs) across six time points following salt treatment. Functional enrichment analysis revealed that these DEGs were predominantly associated with seven biological processes related to salt adaptation, including hormone signaling, oxidative stress defense, ion homeostasis, osmotic adjustment, water stress response, salt perception and signal transduction, as well as transcription factor-mediated regulatory networks [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These observations underscore the utility of transcriptome profiling in capturing dynamic gene expression changes and pinpointing candidate genes with specific temporal response patterns under salt stress [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This approach provides a robust framework for deciphering the molecular components and regulatory circuits that govern salt tolerance in plants. In wheat, transcriptomic analyses have been applied across different growth stages and tissues, although the majority of studies to date have concentrated on roots, stems, and leaves at the seedling stage [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the progress made in wheat salt tolerance, investigations into the salt tolerance mechanisms of spelt remain limited [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In particular, transcriptome-based studies comparing spelt accessions with contrasting salt tolerance are rarely reported. Therefore, genome-wide identification of salt stress-responsive genes through transcriptome analysis in spelta offers a promising opportunity to elucidate its underlying regulatory mechanisms and holds significant research relevance [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In the present study, we screened a panel of spelt germplasm and identified accessions exhibiting differential salt tolerance at the seedling stage. Subsequently, we conducted a comparative transcriptomic analysis to characterize the early salt stress response in the leaves of spelt accessions with contrasting salinity tolerance, aiming to uncover the transcriptional dynamics and molecular pathways that distinguish their adaptive responses.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and selection of salt-tolerant spelt wheat genotypes\u003c/h2\u003e \u003cp\u003eField evaluation of 22 spelt accessions under saline conditions in Dongying, China, revealed substantial variation in salt tolerance. Based on adult-stage agronomic traits, including plant height, thousand-kernel weight (TKW), and grain yield per plant (GYPP) (Table\u0026nbsp;1), 12 accessions were classified as salt-tolerant. The remaining 10 accessions showed severe salt sensitivity. Among them, CWI17370, CWI17942, CWI18042 and CWI18043 were failed germination. CWI18080, CWI18090, CWI18453, CWI18476, CWI44218 and CWI80462 showed growth arrest, leaf necrosis, or premature senescence before reaching the adult stage, with no effective panicle formation.\u003c/p\u003e \u003cp\u003eTo determine the appropriate salt concentration and identify the most suitable genotypes for subsequent seedling-stage salt tolerance assays and transcriptome sequencing, a preliminary screening was conducted using these 12 salt-tolerant spelt accessions under a NaCl concentration gradient (0, 50, 100, 150 and 200 mM). After seven days of treatment, seedling phenotypes were evaluated. The results showed that under 50 mM NaCl, no significant phenotypic differences were observed among these accessions compared to the control, indicating a mild stress condition insufficient for discriminating salt tolerance levels. At 100 mM level, moderate growth inhibition was observed, but the phenotypic variation among accessions remained limited (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In contrast, under 150 mM level, clear and consistent phenotypic divergence emerged, with three accessions CWI44398, CWI78968, and CWI44183 exhibiting superior growth performance, characterized by higher shoot and root biomass and less severe chlorosis compared to the other nine accessions. Under 200 mM level, severe stress symptoms, including pronounced growth arrest and leaf necrosis, were observed across most accessions, making it difficult to effectively distinguish tolerance levels.\u003c/p\u003e \u003cp\u003eBased on these observations, 150 mM level was selected as the optimal concentration for further experiments, and these three accessions (CWI44398, CWI78968, and CWI44183) showing superior salt tolerance at this concentration were chosen for subsequent transcriptome sequencing analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePhenotypic variation among three spelt accessions under salt stress\u003c/h3\u003e\n\u003cp\u003eUnder 150 mM NaCl treatment, with wheat cultivar Jimai 22 serving as the salt-tolerant control, CWI44398, CWI78968, and CWI44183 exhibited superior salt tolerance, while their root development was more sensitive to salt stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To investigate the phenotypic differences among the genotypes, multiple salt tolerance-related traits were measured. Comparative analysis of phenotypic variations revealed significant differences between salt-treated and control groups in shoot length, primary root length, shoot fresh weight, root fresh weight, total root fresh weight, shoot dry weight, and root dry weight. These findings indicate the sustained effect of salt treatment on the three salt-tolerant spelt genotypes. Notably, under salt stress, the shoot length of the three salt-tolerant spelt wheat genotypes demonstrated superior salt tolerance compared to the Jimai 22. Regarding root dry weight, CWI78968 and CWI44183 exhibited higher salt tolerance than CWI44398, suggesting genotype-specific responses to salt treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTranscriptomic differences between control and salt-treated groups at the seedling stage\u003c/h3\u003e\n\u003cp\u003eGiven that early salt tolerance in wheat is critically influenced by the seedling stage, we profiled the transcriptomes of CWI44398, CWI78968, and CWI44183 under both control and salt-treated conditions to elucidate the biological basis for differential salt tolerance. Principal Component Analysis (PCA) was performed using the first three principal components to distinguish differences among sample groups. The results revealed clear separations between the control and salt-treated groups for the genotypes CWI44398, CWI78968, and CWI44183, indicating substantial genome-wide transcriptional differences across treatment conditions and high reproducibility within each sample group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). DEGs were then obtained for each comparison group (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Subsequently, DEGs under salt stress compared to control conditions were identified for each genotype. In CWI44398 and CWI78968, the numbers of up-regulated DEGs during the seedling stage significantly exceeded those of down-regulated DEGs. In contrast, CWI44183 exhibited a significantly higher number of down-regulated than up-regulated ones, suggesting differential salt tolerance responses among these genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe DEGs were further classified into genotype-specific and shared categories. Under salt stress, CWI44398 displayed 1,005 genotype-specific down-regulated and 2,049 up-regulated genes; CWI78968 exhibited 915 down-regulated and 770 up-regulated genes; and CWI44183 showed 2,441 down-regulated and 547 up-regulated genes. Additionally, 399 genes were commonly down-regulated and 665 genes commonly up-regulated across all the three genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eIt can be observed that under salt stress and control conditions, the highly expressed DEGs were clustered in distinct regions. Moreover, across different wheat varieties subjected to the same treatment, the highly expressed DEGs were mostly concentrated in similar regions. These patterns reveal the differences in DEGs between the salt stress and control groups, and also suggest that the three spelt accessions share a similar salt tolerance mechanism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\n\u003ch3\u003eFunctional categories and pathways associated with seedling-stage salt tolerance\u003c/h3\u003e\n\u003cp\u003eBased on a multi-dimensional transcriptomic analysis, all DEGs were categorized into four groups: common DEGs shared among the three genotypes, and genotype-specific DEGs for CWI44398, CWI78968, and CWI44183, respectively. These distinct categories of DEGs provide complementary insights into the biological basis of salt tolerance in wheat. Specifically, the common DEGs reflect conserved transcriptional responses associated with salt tolerance shared across CWI44398, CWI78968, and CWI44183, whereas the genotype-specific DEGs highlight unique adaptive mechanisms characteristic of each individual genotype.\u003c/p\u003e \u003cp\u003eTo elucidate the functional categories and regulatory pathways associated with salt tolerance during the wheat seedling stage, all DEGs were used for GO and KEGG analyses (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). GO analysis showed that DEGs identified at this stage were predominantly enriched in biological process terms, followed by molecular function terms. Enrichment analysis based on common DEGs shared among CWI44398, CWI78968, and CWI44183 revealed several conserved pathways under salt stress. These included response to abiotic stimulus (GO:0009628), xenobiotic transmembrane transport (GO:0006855), polysaccharide metabolic process (GO:0005976), oxidoreductase activity (GO:0016491), and vitamin binding (GO:0019842). These findings suggest that these biological processes represent common features of the salt stress response in these genotypes. The salt tolerance of CWI44398 was specifically associated with sulfur compound metabolic process (GO:0006790), oligosaccharide metabolic process (GO:0009311), calcium ion binding (GO:0005538), and amylase activity (GO:0004553). For CWI78968, specific associations included small molecule metabolic process (GO:0044281), cellular polysaccharide biosynthetic process (GO:0034637), carboxy-lyase activity (GO:0016831), and primary active transmembrane transporter activity (GO:0015399). In contrast, the salt tolerance of CWI44183 was specifically linked to metal ion transmembrane transporter activity (GO:0046873). In summary, the enriched GO terms derived from the genotype-specific DEGs differed substantially among CWI44398, CWI78968, and CWI44183, highlighting distinct molecular mechanisms underlying their differential salt tolerance (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKEGG enrichment analysis showed that biosynthesis of amino acids (ko01230), starch and sucrose metabolism (ko00500), α-Linolenic acid metabolism (ko00592), and MAPK signaling pathway \u0026ndash; plant (ko04016) were identified as core metabolic pathways commonly associated with salt tolerance across all three wheat genotypes. Arginine biosynthesis (ko00220), Fatty acid metabolism (ko01212), and nitrogen metabolism (ko00910) were specifically enriched in the salt-tolerant genotype CWI44398. Fatty acid elongation (ko00062) was uniquely associated with CWI78968, while glyoxylate and dicarboxylate metabolism (ko00630) was specific to CWI44183 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). These findings further elucidate the distinct molecular mechanisms underlying salt tolerance in these spelta genotypes. .\u003c/p\u003e\n\u003ch3\u003eExpression pattern analysis under salt stress\u003c/h3\u003e\n\u003cp\u003eSix DEGs from the transcriptome analysis, including \u003cem\u003eTraesCS3A03G0366700\u003c/em\u003e, \u003cem\u003eTraesCS2B03G0234400\u003c/em\u003e, \u003cem\u003eTraesCS3D03G0353700\u003c/em\u003e, \u003cem\u003eTraesCS2A03G0589200\u003c/em\u003e, \u003cem\u003eTraesCS7A03G0921600\u003c/em\u003e and \u003cem\u003eTraesCS2B03G0309400\u003c/em\u003e were selected for qRT-PCR validation in CWI44398, CWI78968, and CWI44183 (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). Four genes were identified as positive regulators of salt tolerance in spelt, based on their up-regulation under salt stress. \u003cem\u003eTraesCS3A03G0366700\u003c/em\u003e, another ubiquitin-conjugating enzyme (UBC), and \u003cem\u003eTraesCS2B03G0234400\u003c/em\u003e, encoding a dirigent protein with a jacalin-like lectin domain, were significantly up-regulated, with the latter potentially contributing to cell wall modification and antioxidant defense (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u0026amp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). \u003cem\u003eTraesCS3D03G0353700\u003c/em\u003e, encoding a ubiquitin-conjugating enzyme E2, was up-regulated, suggesting its involvement in protein degradation pathways related to ion homeostasis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). \u003cem\u003eTraesCS2A03G0589200\u003c/em\u003e, encoding a carboxylesterase 15, was also up-regulated, implicating it in membrane stability and Na⁺/K⁺ balance (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). The consistent up-regulation of these four genes in both qRT-PCR and RNA-seq analyses confirms their positive contribution to salt tolerance in the three spelt genotypes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eConversely, two genes exhibited expression patterns inconsistent with a positive role in salt tolerance. \u003cem\u003eTraesCS7A03G0921600\u003c/em\u003e, encoding a polyamine oxidase (PAO), was up-regulated under salt stress. Despite the known roles of PAO enzymes in stress signaling, this expression pattern suggests that the mechanism encoded by this gene is not a major driver of salt tolerance in these genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Similarly, \u003cem\u003eTraesCS2B03G0309400\u003c/em\u003e, encoding a class III peroxidase, was down-regulated under 150 mM NaCl treatment, as confirmed by both qRT-PCR and RNA-seq, indicating that this peroxidase-mediated pathway does not contribute to the observed salt tolerance (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSalt tolerance is a complex trait governed by multiple genes and is closely associated with both environmental and genetic factors [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Wheat responds to salt stress through diverse morphological and physiological pathways, making it difficult to accurately assess salt tolerance using a single criterion [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this study, we integrated field-based phenotypic screening with seedling-stage physiological and transcriptomic analyses to identify and characterize salt-tolerant spelt accessions. Three accessions CWI44398, CWI78968, and CWI44183 were selected for their superior salt tolerance at both adult and seedling stages. Our findings reveal that these accessions exhibit enhanced shoot growth under salt stress compared to the reference cultivar Jimai 22, while showing greater sensitivity in root development with distinct genotype-specific variation. Transcriptomic profiling further uncovered both conserved and genotype-specific molecular pathways underlying their differential salt tolerance, providing valuable insights into the complex regulatory networks governing salt stress responses in spelt.\u003c/p\u003e \u003cp\u003eThe differential responses between shoot and root tissues observed in this study are consistent with previous reports indicating that roots are often more sensitive to salt stress due to direct exposure to the rhizosphere environment [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The superior shoot growth of the three spelt accessions under 150 mM NaCl suggests that these genotypes maintain efficient ion exclusion or compartmentalization mechanisms that protect photosynthetic tissues from salt-induced damage. However, the greater reduction in root biomass, particularly in CWI44398, indicates that root sensitivity may be a trade-off for shoot tolerance. Such genotype-specific root responses have been documented in other wheat relatives, including wild emmer wheat (\u003cem\u003eT. dicoccoides\u003c/em\u003e) and \u003cem\u003eAegilops\u003c/em\u003e species, where root architecture plasticity contributes to overall salt adaptation [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The variation in root dry weight among the three accessions further supports the notion that salt tolerance is a complex trait governed by multiple genetic determinants that may act independently in different tissues.\u003c/p\u003e \u003cp\u003eThe transcriptomic analysis revealed distinct expression patterns among the three accessions, providing molecular evidence for the phenotypic divergence observed. PCA clearly separated control and salt-treated groups, indicating robust transcriptional reprogramming in response to salt stress. Notably, CWI44398 and CWI78968 exhibited more up-regulated than down-regulated DEGs, whereas CWI44183 showed the opposite pattern. This contrasting transcriptional landscape suggests that CWI44183 may rely more on the suppression of growth-related genes or the activation of stress-avoidance strategies, a phenomenon observed in other stress-tolerant plant species [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGO enrichment analysis revealed common biological processes among the three accessions, including response to abiotic stimulus and polysaccharide metabolism, representing core salt stress responses. Genotype-specific GO terms indicated distinct adaptive strategies: CWI44398 was associated with sulfur and oligosaccharide metabolism, suggesting osmotic adjustment; CWI78968 showed enrichment in polysaccharide biosynthesis, implicating cell wall remodeling; and CWI44183 was uniquely enriched in metal ion transport, pointing to ion homeostasis. These divergent enrichments highlight multiple molecular routes to salt tolerance in spelt wheat, consistent with the concept of \u0026lsquo;alternative adaptive pathways\u0026rsquo; proposed in recent plant stress studies [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. KEGG pathway analysis further supported these findings. The plant MAPK signaling pathway, identified as a common pathway across all three accessions, is a well-established regulator of stress responses that mediates signal transduction from stress perception to downstream transcriptional activation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Starch and sucrose metabolism, another common pathway, likely reflects adjustments in carbon partitioning and energy metabolism under stress, as previously reported in salt-tolerant rice and barley genotypes [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The genotype-specific pathways arginine biosynthesis and nitrogen metabolism in CWI44398, fatty acid elongation in CWI78968, and glyoxylate and dicarboxylate metabolism in CWI44183 further underscore the diversity of metabolic adjustments employed by different genotypes to cope with salinity.\u003c/p\u003e \u003cp\u003eFour genes were then identified as positive regulators based on their consistent up-regulation under salt stress. \u003cem\u003eTraesCS3D03G0353700\u003c/em\u003e and \u003cem\u003eTraesCS3A03G0366700\u003c/em\u003e, encoding ubiquitin-conjugating enzymes (E2), are involved in the ubiquitin-26S proteasome pathway, which mediates targeted protein degradation critical for ion homeostasis [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. \u003cem\u003eTraesCS2A03G0589200\u003c/em\u003e, encoding a carboxylesterase, likely contributes to membrane stability and Na⁺/K⁺ balance [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. \u003cem\u003eTraesCS2B03G0234400\u003c/em\u003e, encoding a dirigent protein, is implicated in cell wall reinforcement [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The coordinated up-regulation of these genes across the three accessions suggests they represent core components of salt tolerance in spelt wheat. Conversely, two genes exhibited expression patterns inconsistent with positive regulatory roles. \u003cem\u003eTraesCS2B03G0309400\u003c/em\u003e, encoding a class III peroxidase, was down-regulated under salt stress, despite its typical association with stress responses [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. \u003cem\u003eTraesCS7A03G0921600\u003c/em\u003e, encoding a PAO, was up-regulated, yet this expression pattern may not translate into functional contribution, possibly due to post-transcriptional regulation or tissue-specific expression not captured in whole-seedling RNA-seq analysis [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpelt, as a progenitor of cultivated hexaploid wheat, harbors substantial genetic diversity that can be exploited for introgression breeding [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. These three salt-tolerant spelt accessions identified in this study represent valuable genetic resources for wheat improvement.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, three salt-tolerant spelt accessions CWI44398, CWI78968, and CWI44183 were identified through field screening and seedling-stage evaluation. Under 150 mM NaCl treatment, these accessions exhibited superior shoot growth compared to the salt-tolerant control Jimai 22, while root development was more sensitive with genotype-specific variation. Transcriptomic analysis revealed both conserved pathways and genotype-specific pathways underlying salt tolerance. Quantitative real-time (qRT-PCR) validation confirmed the expression patterns of key genes, identifying four positive regulators and two genes not contributing to tolerance. These findings provide valuable genetic resources and molecular insights for improving salt tolerance in wheat.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePlant materials and salt treatment\u003c/h2\u003e \u003cp\u003eA total of 22 spelt accessions were provided by Prof. Hongxing Xu from Henan University, Kaifeng, China. Wheat cultivar Jimai 22 served as the salt-tolerant control [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. All 22 spelt accessions were firstly evaluated for salt tolerance in a saline-alkali field at Maotuo, Dongying, China [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. At harvest, plant height, grains per spike, the thousand-kernel weight (TKW) and grain yield per plant (GYPP) were recorded for each genotype. Following the screening and identification of salt-tolerant wheat varieties, a preliminary experiment was conducted using a salt stress gradient to evaluate the phenotypes of the selected varieties. Among the salt-tolerant spelt accessions, three ones with superior phenotypic performance were selected for further assessment of seedling-stage salt tolerance.\u003c/p\u003e \u003cp\u003eFor each accession, 100 plump and uniformly sized seeds were selected. The seeds were surface-sterilized with 1.5% sodium hypochlorite for 10 minutes, thoroughly rinsed with distilled water, and then germinated on moistened filter paper in Petri dishes (9 cm diameter) for 2\u0026ndash;3 days at 25℃ [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Uniformly germinated seeds were transferred to hydroponic culture in a greenhouse and grown in half-strength Hoagland\u0026rsquo;s solution. After 7\u0026ndash;10 days, the seedlings were subjected to two treatments for 7 days: (1) Control (Hoagland\u0026rsquo;s solution only) and 150 mM NaCl. The experiment was arranged in a completely randomized design with three biological replicates per treatment. At 7 days post-treatment, leaf samples were collected from the seedlings, immediately frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent RNA-seq analysis. Simultaneously, shoot height, root length, shoot fresh weight, root fresh weight, shoot dry weight, and root dry weight were measured to evaluate salt tolerance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction, library construction, and transcriptome sequencing\u003c/h2\u003e \u003cp\u003e Total RNA was isolated using RNAprep Pure Polysaccharide Polyphenol Plant Total RNA Extraction Kit (Tiangen Biotech, Beijing, China) according to the manufacturer\u0026rsquo;s protocol. The concentration and purity of the extracted RNA were assessed using the Agilent 5400 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA), with the OD260/280 and OD260/230 ratios monitored to ensure protein and polyphenol/polysaccharide contamination were within acceptable limits (OD260/280\u0026thinsp;\u0026ge;\u0026thinsp;1.8, OD260/230\u0026thinsp;\u0026ge;\u0026thinsp;1.5). The integrity of the RNA was evaluated by agarose gel electrophoresis to visualize distinct 28S and 18S ribosomal RNA bands. Furthermore, the RNA integrity number (RIN) was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Only high-quality RNA samples with a RIN value\u0026thinsp;\u0026ge;\u0026thinsp;8.0 were used for subsequent cDNA library construction.\u003c/p\u003e \u003cp\u003eA total of 1 \u0026micro;g of high-quality RNA per sample was used as input material for library preparation. Sequencing libraries were generated using Fast RNA-seq Lib Prep Kit V2 (ABclonal, Wuhan, Hubei, China) following the manufacturer\u0026rsquo;s recommendations. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads and then fragmented. The first-strand cDNA was synthesized using random hexamer primers and reverse transcriptase, followed by second-strand cDNA synthesis. After library construction, the double-stranded cDNA was subjected to end repair, A-tailing, and ligation with Illumina adapters. The library fragments were purified and enriched by PCR amplification to create the final cDNA library. The library quality was assessed on the Agilent 2100 Bioanalyzer to ensure the correct insert size, and the concentration was quantified using Qubit\u0026reg; 2.0 Fluorometer (Invitrogen, CA, USA) and qRT-PCR. Finally, the libraries were sequenced on the Illumina NovaSeq X Plus platform (Illumina Inc., San Diego, CA, USA) to generate150 bp paired-end reads.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData filtering and transcriptome assembly\u003c/h2\u003e \u003cp\u003eRaw data in FASTQ format were first processed using Fastp v0.23.1 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. In this step, clean data were obtained by removing reads containing adapter contamination, poly-N stretches, and low-quality reads from the raw data. Simultaneously, the Q20, Q30, and GC content of the clean data were calculated to ensure data quality for downstream analyses. All downstream analyses were based on high-quality clean reads.\u003c/p\u003e \u003cp\u003eThe clean reads were aligned to the reference genome of IWGSC RefSeq v2.1 using HISAT2 (v2.2.1) with default parameters [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Transcript assembly was performed using StringTie (v2.2.1) [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], which reconstructs transcripts through a network flow algorithm with an optional de novo assembly step. Reads that mapped to multiple genomic locations or had a mapping quality score below 10 were filtered out using featureCounts (v2.06) to ensure the accuracy of subsequent quantification [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDEGs analysis\u003c/h2\u003e \u003cp\u003ethe expression level for each gene was quantified using the fragments per kilobase of exon model per million mapped fragments (FPKM) method[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Based on the genomic alignment positions, the featureCounts tool from the Subread software package was employed to count the number of reads mapped to the genomic regions for each gene, including newly predicted ones. Reads with low mapping quality (MAPQ\u0026thinsp;\u0026lt;\u0026thinsp;10), non-paired reads, and reads aligned to multiple genomic locations were filtered out prior to quantification. Following expression quantification, statistical analyses were performed to identify DEGs under different treatment conditions. The differential expression analysis consisted of three main steps. First, raw read counts were normalized to correct for sequencing depth variations. Second, statistical models were applied to calculate \u003cem\u003ep\u003c/em\u003e-values, representing the probability of differential expression under the null hypothesis. Finally, multiple hypothesis testing correction was performed to control the false discovery rate (FDR) [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFunctional annotation and pathway analysis of DEGs\u003c/h2\u003e \u003cp\u003eTo elucidate the functional implications of the DEGs, we performed GO and KEGG enrichment analyses using the clusterProfiler software (v4.8.1). For GO enrichment, gene length bias was corrected during the analysis [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. GO terms with a corrected p-value of less than 0.05 were considered significantly enriched among the DEGs. For pathway analysis, we utilized the KEGG database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kegg.jp/\u003c/span\u003e\u003cspan address=\"https://www.kegg.jp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to identify statistically enriched metabolic or signaling pathways associated with the DEGs, employing the same software package and significance threshold [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eqRT-PCR analysis\u003c/h2\u003e \u003cp\u003eCWI44398, CWI78968, and CWI44183 were treated using 150 mM NaCI and leaves were sampled at 0, 4, 12, 24, 48, 72, 120 and 168 hpi. Total RNA was isolated from the infected leaves using TRIzol reagent (Invitrogen, Waltham, USA), and approximately 2 \u0026micro;g of RNA was employed for reverse transcription using a FastQuant RT Kit (Tiangen, Beijing, China). The qRT-PCR assays were performed on the Bio-Rad CFX Connect real-time PCR system (BIO-RAD, USA), and relative expression of the selected genes was calculated using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The wheat gene \u003cem\u003eTaActin\u003c/em\u003e served as the internal control [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBCE Before common era\u003c/p\u003e\n\u003cp\u003eHKT High-affinity potassium transporter\u003c/p\u003e\n\u003cp\u003eROS Reactive oxygen species\u003c/p\u003e\n\u003cp\u003eRNA-seq RNA sequencing\u003c/p\u003e\n\u003cp\u003eDEGs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Differentially expressed genes\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTKW\u003c/strong\u003e Thousand kernel weight\u003c/p\u003e\n\u003cp\u003eGYPP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;grain yield per plant\u003c/p\u003e\n\u003cp\u003eGO Gene ontology\u003c/p\u003e\n\u003cp\u003eKEGG Kyoto encyclopedia of genes and genomes\u003c/p\u003e\n\u003cp\u003eMAPK Mitogen-activated protein kinase\u003c/p\u003e\n\u003cp\u003eqRT-PCR Real-time quantitative PCR\u003c/p\u003e\n\u003cp\u003eUBC Ubiquitin-conjugating enzyme\u003c/p\u003e\n\u003cp\u003eOD Optical density\u003c/p\u003e\n\u003cp\u003eRIN\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;RNA integrity number\u003c/p\u003e\n\u003cp\u003ePCA Principal component analysis\u003c/p\u003e\n\u003cp\u003eFPKM Fragments per kilobase of transcript per million mapped reads\u003c/p\u003e\n\u003cp\u003eFDR False discovery rate\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to Prof. Hongxing Xu from Henan University for supplying the experimental materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSZ performed the seed germination, salt treatment and sample preparation; SZ, GP, ML, YS and JZ prepared the naked seeds; SZ, YL and DL conducted the qRT-PCR; GH, YQ, DX, NY and SL analyzed the RNA-seq data and prepared the manuscript; ZC, DL and CL were the funding administration. SZ, GH and YJ designed the experiment and revised the manuscript; PM supervised the project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was financially supported by Key Research and Development (R\u0026amp;D) plan project of Shandong Province (2023LZGC009-4-4), Science and Technology Demonstration Project of Shandong Province (2024SFGC0402), National Natural Science Foundation of China (32301923), Natural Science Foundation of Shandong Province (ZR2023QC203, ZR2023QC292) and the Graduate Innovation Foundation of Yantai University (GGIFYTU2527).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA-seq data have been deposited with the National Center for Biotechnology Information: Submission ID SRR37547788.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYantai Key Laboratory of Characteristic Agricultural Biological Resources Conservation and Germplasm Innovative Utilization, College of Life Sciences, Yantai University, Yantai 264005, China\u003c/p\u003e\n\u003cp\u003eShengmao Zou, Siqi Li, Yuanwei Sui, Mengyi Liu,\u0026nbsp;Ningning Yu, Dongming Li, Yuting Liang, Guantong Pan, Yuli Jin, Pengtao Ma\u003c/p\u003e\n\u003cp\u003eCenter for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China\u003c/p\u003e\n\u003cp\u003eGuohao Han\u003c/p\u003e\n\u003cp\u003eInstitute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences/Hebei Key Laboratory of Crop Genetic and Breeding, Shijiazhuang 050035, China\u003c/p\u003e\n\u003cp\u003eYanmin Qie, Lige Geng\u003c/p\u003e\n\u003cp\u003eCrop Research Institute, Shandong Academy of Agricultural Sciences/National Engineering Research Center for Wheat and Maize/National Key Laboratory of Wheat Breeding/Key Laboratory of Wheat Biology and Genetic Improvement in the North Huang-Huai River Valley/Shandong Wheat Technology Innovation Center, Jinan 250100, China\u003c/p\u003e\n\u003cp\u003eJiadong Zhang, Cheng Liu\u003c/p\u003e\n\u003cp\u003eCollege of Agronomy, Qingdao Agricultural University, Qingdao, Shandong, 266109, China\u003c/p\u003e\n\u003cp\u003eJiadong Zhang, Dengan Xu, Cheng Liu\u003c/p\u003e\n\u003cp\u003eNational Center of Technology Innovation for Comprehensive Utilization of Saline-Alkali Land, Dongying 257347, China\u003c/p\u003e\n\u003cp\u003eJiadong Zhang, Cheng Liu\u003c/p\u003e\n\u003cp\u003eCorresponding authors\u003c/p\u003e\n\u003cp\u003eCorrespondence to Pengtao Ma, Yuli Jin or Cheng Liu\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKojonna T, Suttiyut T, Khunpolwattana N, Pongpanich M, Suriya-Arunroj D, Comai L, et al. 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Crop J. 2025;13(1):62-68.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Spelt, Salt tolerance, RNA-seq, Expression patterns","lastPublishedDoi":"10.21203/rs.3.rs-9250361/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9250361/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSoil salinity severely limits wheat production. Spelt (\u003cem\u003eTriticum spelta\u003c/em\u003e. L.) represents a valuable genetic resource for improving the salt tolerance of common wheat, but its underlying mechanisms remains poorly understood.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eField evaluation of 22 spelt accessions identified 12 salt-tolerant genotypes. Further screening under a NaCl gradient (0\u0026ndash;200 mM) selected three superior accessions CWI44398, CWI78968, and CWI44183. Under 150 mM NaCl, these three accessions exhibited greater shoot growth than the salt-tolerant control Jimai 22, while root development was more sensitive. Transcriptomic analysis revealed distinct expression patterns among genotypes, with common pathways including abiotic stress response and MAPK signaling, alongside genotype-specific pathways such as sulfur metabolism and fatty acid elongation. Expression patterns analysis under salt stress further confirmed the RNA-seq results, identifying four positively regulated genes and two genes not contributing to salt tolerance.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study identified three salt-tolerant spelt accessions and elucidated conserved and genotype-specific molecular mechanisms, providing valuable resources for salt tolerance breeding in wheat.\u003c/p\u003e","manuscriptTitle":"Transcriptome-level dissection provides unique insights into the salt tolerance in spelt (Triticum spelta L.)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 17:50:36","doi":"10.21203/rs.3.rs-9250361/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-15T10:12:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T08:57:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T03:35:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40811241078553444130209727678621261409","date":"2026-04-08T08:10:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318542416330680532437507835164273227301","date":"2026-04-08T01:59:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-07T08:51:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245299083771563043444269701453817181660","date":"2026-04-07T06:16:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T09:14:58+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-31T08:56:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-30T14:03:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-30T14:02:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2026-03-28T06:40:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"005b5999-edbf-4452-8563-cce73cb1eb43","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T17:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 17:50:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9250361","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9250361","identity":"rs-9250361","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}