The PAW was generated using sDBD in gas-tight containers ( Figure 1A ), as previously described (Lee et al., 2020; Ka et al., 2021). The electrodes used consisted of stainless steel (power supply and ground) with an aluminum oxide plate (1 mm thick) between the electrodes. The sDBD reactor used in the experiment has two electrodes at the top, and its input power and driving frequency are 10 W and 17 kHz, respectively. Commercial fans (15-LED 120, Aone, China) were used to dissolve the plasma gas in water. Two liters of deionized water (DW) were treated with sDBD to obtain PAW25 (6 min), PAW50 (12 min), PAW100 (25 min), and PAW400 (90 min). We conducted the experiment under five treatment conditions (DW, PAW25, PAW50, PAW100, and PAW400). The nitrate content in PAW was directly proportional to the plasma exposure times. PAW25, PAW50, PAW100, and PAW400 correspond to exposure times of 6, 12, 25, and 90 minutes, respectively, as shown in Figure 1D . This correlation is based on our previous studies (Lee et al., 2020; Ka et al., 2021), where we systematically analyzed the impact of varying plasma exposure times on the chemical composition of PAW.

The chemical characteristics of PAW were analyzed by measuring the anion content using ion chromatography (ICS-2100, Thermo Dionex, Sunnyvale, CA, USA), which was conducted one day after generating PAW. To quantify the anions, a four-point method was used to measure the standard sample (Dionex Seven Anion Standard II [in DW]) at concentrations of 5, 10, 50, and 100 mg/L, and the pH and conductivity were determined using an Orion Versa Star Pro (Thermo Scientific, Waltham, MA, USA). The pH was adjusted to 5.6-5.8 using 0.1 N and 1 N KOH solution to ensure it is suitable for plant growth. Hydrogen peroxide (H₂O₂) was measured using a Humas HS-H₂ O₂ -L kit (Humas, Daejeon, Republic of Korea). All measurements were performed in triplicates.

In this study, we used the sorghum varieties Sodamchal, Noeulchal, Baremae, and Hichal, obtained from propagation in the field (National Institute of Crop Science, Miryang, Republic of Korea). Seed propagation and all experiments were performed following common agricultural practices and complied with relevant institutional regulations. The experiment was conducted in a growth chamber (GC-S, Jeiotech, Seoul, Rep. of Korea) in light 16 h and dark 8 h conditions with 26 °C at 60-70% humidity. For seedling phenotypes, sorghum seeds were germinated on filter paper under the appropriate treatment conditions (DW, PAW). Seedling phenotypes were measured on the 20th day after sowing.

For the phenotypic comparison, seeds were germinated by laying paper on a plate and adding 5 mL of each solution for each condition; on the 2nd day after germination, the seeds were transplanted into the soil and harvested by growth for 20 days. Throughout the experiment, day and night temperatures and relative humidity were maintained at 26°C and 60%, respectively. Sorghum plants were regularly irrigated with PAW at all growth stages to ensure consistent treatment.

Sorghum leaves were collected from the fourth leaf (or the third leaf if the fourth was less developed) of the plants 20 days after sowing. The leaves were fixed using A4 double-sided tape and scanned with a scanner, and the leaf characteristics (leaf area, length, and width) were measured using ImageJ software version 1.54k (https://imagej.net/ij/).

To measure total chlorophyll content in leaves, the final fully expanded leaves were cut, weighted and ground in tissue homogenizer. The chlorophyll was extracted from leaf by 80% acetone, incubated on dark and repeated until all chlorophyll was dissolved. Total chlorophyll content was measured using a spectrophotometer (Hach DR6000, Loveland, CO, United States), with absorbance readings taken at A665 and A648. Biological replicates consisted of at least five individual plants for each treatment condition (DW, PAW25, PAW50, PAW100, PAW400).

After cutting the stem–root interface of the sorghum seedlings, a portion approximately 4 cm above the bottom of the stem (meristem location) was cut using a razor blade. It was directly stained with 0.05% toluidine blue O for approximately 1 min and then washed 3-4 times with DW. Samples were observed under a Nikon SMZ18 optical microscope (Nikon, Tokyo, Japan) using imaging software (NIS-Elements, Nikon, http://www.microscope.healthcare.nikon.com/). Size and area measurements of the cut biological material were performed using the ImageJ software.

Total RNA was isolated from the shoot apical region of sorghum, specifically from a segment spanning 0.5 cm to 1 cm from the root-shoot junction from 20 days seedlings. The isolation was performed on seedlings cultivated under both DW and PAW100 conditions. Fresh seedlings were immediately frozen and pulverized in liquid nitrogen. Subsequently, RNA was extracted using the TRIzol Plant RNA Extraction Kit, following the manufacturer’s standard protocol.

Library preparation was initiated for RNA sequencing by assessing the quality and quantity of the extracted RNA using Bioanalyzer 2100. High-quality RNA was used to construct sequencing libraries. This process involves RNA fragmentation, synthesis of the first and second cDNA strands, end repair, A-tailing, adapter ligation, and enrichment of the library through PCR. The prepared libraries were quantified and validated for quality before sequencing on an Illumina high-throughput sequencing platform. The RNA-seq reads were deposited in the NCBI Sequence Read Archive under BioProject accession PRJNA1173527.

RNA sequencing was performed to investigate gene expression patterns and identify differentially expressed genes (DEGs) under specific experimental conditions. Raw RNA-Seq reads were aligned to the Sorghum bicolor reference genome, specifically version NCBIv3, using Kallisto, a pseudo-alignment-based tool that efficiently estimates abundance levels and provides counts per million (CPM) and transcripts per million (TPM) values (Bray et al., 2016). The reference sequence, designated as Sorghum_bicolor, Sorghum_bicolor_NCBIv3.dna.toplevel.fa, and the corresponding annotation files Sorghum_bicolor.Sorghum_bicolor_NCBIv3.57. gff3 were accessed and downloaded from the Ensembl Plant database (Cunningham et al., 2022).

Differential expression analysis was subsequently conducted using iDEP version 1.13, installed locally, with Ensembl Release 107 integrated for genomic data annotation (Ge et al., 2018). The iDEP platform facilitated the efficient handling of data preparation, normalization, and statistical analysis using the DEseq2 1.44.0 package in R 4.4.0 (Love et al., 2014). DEGs were defined based on criteria including a 1.5-fold change and a false discovery rate (FDR) threshold of < 0.05. Hierarchical clustering was used to analyze the gene expression patterns, as assessed by log₂TPM, across both groups.

GO analysis was also performed using iDEP, which incorporates ShinyGO (version 0.77) for functional enrichment analysis (Ge et al., 2020). This analysis included both enrichment and GO network analyses, which enabled the identification and visualization of enriched GO terms across biological processes (BPs), cellular components (CCs), and molecular functions (MFs). After identifying the significant GO categories, we isolated and extracted expression values (TPM) using the dplyr package (version 1.1.4). These values were then used to generate heatmaps. Heatmap analysis of the gene expression patterns was performed using the pheatmap package (version 1.0.12) in R in the RStudio environment (version 2024.04.0, Build 735).

To identify conserved motifs among the promoter sequences of highly enriched genes, we collected 2000 base pair sequences upstream of the transcription start site from 285 genes associated with significantly enriched GO categories across BPs, CCs, and MFs. The MEME Suite (version 5.5.5) was used for motif discovery (Bailey et al., 2015). The analysis was performed with the following parameters: the top six motifs were displayed, with a motif length of 20, and all other settings were set to default. For visualization, the identified motifs were further analyzed using TBtools [https://github.com/CJ-Chen/TBtools] (Chen et al., 2020) (Chen et al., 2020). Subsequently, the conserved motifs were subjected to a motif comparison analysis using TomTom (version 5.5.5), a motif comparison tool that aligns and compares discovered motifs against known motif databases. The comparisons were based on the Arabidopsis thaliana DNA Affinity Purification Sequencing (DAP) study, as reported by O’Malley et al. (2016).

GraphPad Prism 9.0 (GraphPad Software, Inc., San Diego, CA, United States) were used for the statistical analysis. Unless described in the figure legends the statistical analysis and comparison among samples were made using one-way ANOVA followed by Tukey’s HSD correction for multiple comparisons. If the P-value was less than 0.05, the different uppercase letters denoted significant differences among samples. The data presented as mean ± SD.

To understand the effects of PAW on early seedlings of the sorghum variety, PAW was produced using an sDBD device with various plasma exposure times ( Figures 1A–C ). The physical and chemical properties of PAW change depending on the plasma treatment time of the sDBD device (Ka et al., 2021). Using sDBD, we previously reported that the main molecular spectra, including the nitrogen primary negative system (N₂ FNS) and nitrogen secondary positive system (N₂ SPS) in the ranges of 280-296 and 390-440 nm, were detected by optical emission spectroscopy (OES) analysis during air discharge (Ka et al., 2021). The standardization of PAW25, PAW50, PAW100, and PAW400 were designated based on their nitrate contents, which were 25, 50, 100, and 400 correspond to exposure times of 6, 12, 25, and 90 minutes, respectively. In detail, the NO₂ ^- and NO₃ ^- contents increased proportionately with the duration of plasma exposure time ( Figures 1D, E , Supplementary Figure 1 ), whereas H₂O₂ was hardly detected regardless of the PAW exposure time ( Figure 1F ). Similar to the nitrite and nitrate contents by PAW concentration, the conductivity was found to increase proportionally with increasing nitrate concentration ( Figure 1G ). Figure 1H shows a schematic diagram of the experimental process. First, PAW was prepared using sDBD on DW by plasma treatment, and IC analysis was performed to confirm the PAW content. After confirming the presence of DW and PAW, irrigated sorghum was grown, and 20-day-old plants were sampled and subjected to microscopic analysis and RNA sequencing.

To evaluate the effect of PAW on sorghum at the seedling stage, various PAW concentrations were tested in a preliminary experiment, including PAW25, PAW50, PAW100, PAW200, PAW300, and PAW400. The results showed that biomass consistently increased with PAW25, PAW50, and PAW100. However, PAW200 and PAW300 resulted in similar or slightly decreased growth compared to PAW100, although both were still greater than DW. A decline in growth relative to DW was observed at PAW400. Based on these findings, we selected PAW25, PAW50, and PAW100 as concentrations that enhance biomass, whereas PAW400 was chosen for its inhibitory effect ( Supplementary Figure 2 ).

To further examine the effect of PAW on different sorghum varieties, we selected five varieties: BTx623, Sodamchal, Noeulchal, Baremae, and Hichal. Plant height, stem thickness, and biomass were measured to assess their sensitivity to PAW treatment ( Figures 2A–D ). Additionally, we analyzed the increase in these phenotypic traits following PAW irrigation compared to DW ( Figures 2E–G ). After 20 days of PAW irrigation, the sorghum varieties exhibited differential growth responses at PAW25, PAW50, PAW100, and PAW400 concentrations ( Figure 2 ).

In terms of plant height, BTx623 showed a proportional increase with PAW25, PAW50, and PAW100, correlating with nitrate concentration. However, the Sodamchal, Baremae, and Hichal varieties showed no response at PAW25, the lowest nitrate condition. In contrast, plant height was significantly inhibited in all varieties under PAW400 ( Figures 2A, B ), with PAW100 producing the tallest plants among the five varieties ( Figures 2A, B ). In addition, stem thickness in BTx623 increased even at the lowest concentration of nitrate, and progressively increased to PAW100, depending on the nitrate concentration. Interestingly, PAW100 exhibited the highest stem thickness across most varieties, whereas PAW400 exhibited the lowest stem growth across all varieties ( Figures 2C, F ).

All sorghum varieties gradually responded to biomass under low nitrate conditions in PAW25 and PAW50 and had a robust reaction in PAW100 ( Figures 2D, G ). They decreased the biomass in PAW400, which had the highest nitration water content. Additionally, leaf phenotypes (leaf area, leaf length, leaf width, and fully expanded leaf number) and chlorophyll content were measured in response to PAW concentrations across all sorghum cultivars ( Supplementary Figure 3 ). In all cultivars, leaf area gradually increased from PAW25 to PAW100, and in four cultivars, except Noeulchal, PAW400 showed a decreased leaf area compared to DW ( Supplementary Figure 3A ). Leaf length slightly increased to nitrate concentration from PAW25 to PAW100, similar to leaf area ( Supplementary Figure 3B ). Leaf width increased gradually from PAW25 to PAW100 in BTx623 and Noeulchal ( Supplementary Figure 3C ). The number of fully expanded leaves followed a similar pattern across all cultivars, with the highest values ​​at PAW50 and PAW100 and the lowest values ​​at DW and PAW400 ( Supplementary Figure 3D ). Chlorophyll content varied across cultivars and nitrate concentrations, and no significant correlation was observed ( Supplementary Figure 3E ). The PAW 100 treatment of young sorghum seedlings served as the optimal PAW condition for the highest plant height, stem thickness, and biomass, indicating that sorghum plants exhibit distinct physiological responses when exposed to varying amounts of PAW. Among the sorghum varieties, the strongest response to PAW in terms of plant biomass was observed in BTx623, whereas the other varieties showed weak phenotypic sensitivity. These results imply that PAW treatment regulates the growth of the BTx623, Sodamchal, Noeulchal, Baremae, and Hichal sorghum varieties, which exhibit variable phenotypic sensitivities to PAW exposure time.

The effect of PAW treatment on specific sorghum tissues was investigated at the cellular level. Phenotypic experimental results from sorghum varieties confirmed the effect of PAW on plant height and stem thickness, resulting in increased biomass in sorghum. We chose stem tissue to further examine the effect of PAW treatment on sorghum tissue and its transcriptome profile because of the strong stem thickness phenotype. Stem tissues included shoot apical meristem (SAM) tissues sampled from the DW and PAW100 treatment groups ( Figure 3A ). Under DW conditions, the three forms of dissected tissues were the leaf sheath (LS), leaf primordia (P), and SAM; the P and SAM tissues were identified as primordial tissues ( Figure 3B ). In the case of DW, the location of the tissue type was organized in the order of SAM, P 1-3, and LS 1-3 from inside to outside. There were no significant differences in the order of tissues or anatomical differences between DW and PAW100. However, the PAW100 condition had an overall larger tissue area, and the primordia tissue, including SAM, P1, P2, P3, and P4, of stem tissue clearly validated that PAW100 had substantially larger stem tissue than DW ( Figures 3B–E ). Specifically, the combination of all tissue areas, primordia tissue, LS1, and LS2 areas was significantly increased in PAW100 condition, 124% in primordia tissue, 27% in LS1, and 42% increment in LS2, respectively ( Figure 3F ). As a result, the overall stem tissue area was enhanced, and sorghum primordia were the most responsive stem tissues to PAW100 treatment. ( Figure 3D ).

To understand the transcriptional regulation underlying plasma-induced sorghum growth enhancement, RNA sequencing was performed on six samples of BTx623 treated with DW and PAW100. As shown in Figures 2 , 3 , the responsiveness to PAW between DW and PAW100 was distinct in the stems of the BTx623 inbred variety, which served as the current reference genome for sorghum ( Figures 2 – 4A ). Total reads mapped to reference with mapping rate at 89-93% ( Supplementary Table 1 ). The total raw read counts for each library of stem samples in DW and PAW100 are displayed in a bar graph, with slight variations in library size ( Supplementary Figure 4A ). To effectively control the mean-dependent variance, we performed a normalized log (rlog) transformation using the DESeq2 package ( Figure 4B ). Principal component analysis (PCA) was performed on the samples to evaluate the sample variability. Principal component (PC1) explained 42.61% of the variance, and the second principal component (PC2) accounted for 15.76%, effectively distinguishing differences between the treatment groups. PCA demonstrated close clustering of the individual samples within triplicates and a distinct separation between DW and PAW100 treatments along two principal axes ( Figure 4C ), indicating repeatability of the RNA-seq data. The 35,567 sorghum genes mapped to the RNA-seq library were normalized using TPM (transcripts per kilobase million). Selection criteria were applied, requiring at least a 1.5-fold change, a P-value of less than 0.05, and a false discovery rate (FDR) < 0.1. Identified 1,650 DEGs between the DW and PAW100 treatment groups, with 1,293 upregulated genes (78.3%) and 357 (21.6%) downregulated genes in PAW100 compared to DW was depicted in volcano plots of Supplementary Figure 4B and the number of DEGs in Figure 4D . The resulting heatmap, shown in Figure 4E , demonstrates the clustering of the samples from individual replicates by the PAW treatment, indicating consistency across replicates and reflecting the response to the PAW100 treatment.

Following the identification of DEGs between DW and PAW100 treatments, GO analysis was performed to elucidate the biological implications of the DEGs ( Supplementary Figure 5 ). The analysis revealed significant enrichment of the top 10 GO terms for BPs, CCs, and MFs ( Figure 5A , Supplementary Figure 5 ). Furthermore, in BPs, transmembrane transport, mRNA transcription, and response to light stimulus were highly enriched ( Figure 5A ); CCs were mainly cell periphery and plasma membrane-related GO was enriched ( Supplementary Figure 6A ); and in MFs, several groups of oxidoreductase activities such as tetrapyrrole binding, monooxygenase activity, heme binding, and iron ion binding were highly enriched. In addition, the DNA-binding transcription factor and transmembrane transporter activity groups were enriched ( Supplementary Figure 6B ).

Additionally, we performed GO network analysis to gain further insight into the overlapping functional relationships and interactions among the enriched gene sets. The enriched network module in the response to the stimulus group was interconnected with other GO terms including responses to radiation, light stimulus, to abiotic stimulus, mRNA transcription, and photosynthesis light harvesting in photosystem I ( Figure 5B ). Similarly, these networks were also detected in CCs and MFs categories, such as the network of cell periphery involved GO module in CCs, and oxidoreductase activity involved module in MFs ( Supplementary Figures 6C, D ). These networks highlight the interplay between different GO terms within the same category of BPs, CCs, and MFs.

Because the upregulation pattern was prominent, we isolated the upregulated genes that were enriched by PAW treatment, especially where the GO-network module showed high interaction among GO-term. As shown in Figure 5C , genes involved in transmembrane transport were strongly upregulated, suggesting an enhanced capability for nutrient and ion transport across cellular membranes, which is a key factor for optimal plant growth and function. Furthermore, genes associated with response to light stimuli showed increased expression, which is likely to facilitate adaptations in photosynthetic efficiency and light absorption, which are essential for energy management and biomass production ( Figure 5D ). In addition, the mRNA transcript levels were enhanced by PAW treatment ( Figure 5E ). In the CCs, the expression levels of genes related to the plasma membrane and cell periphery were significantly increased, indicating cellular modifications aimed at increasing structural integrity and biomass accumulation ( Figures 5F, G ). Moreover, in the GO MFs category, upregulation observed in the transcription regulator activity category underscored the activation of critical gene expression regulatory mechanisms that manage stress responses and developmental processes ( Figure 5H ). Similarly, genes involved in oxidoreductase activity, which is crucial for the oxidative stress response and maintenance of redox homeostasis, also showed marked upregulation, enhancing plant resilience against environmental stressors ( Figure 5I ).

Based on GO analysis, we observed several significantly upregulated GO terms. To further explore the regulatory mechanisms underlying these observations, we performed promoter motif analysis which identified six distinct binding motifs within these promoter regions with varying levels of presence across the gene set ( Figure 6A and Table 1 ). The most prominent motif, AP2/ERBEP (Motif 1), was detected at 234 sites and matched 56 known motifs from the O’Malley et al. (2016) database. This motif was present in 82.11% of the analyzed genes, suggesting its widespread role in regulating gene expression under the influence of PAW. Another significant motif, C2H2 (motif 2), was found in 224 promoter sites with 75 matches and was present in 78.6% of the genes. Other identified motifs, such as C2C2 (motif 3), AP2/ERBEP (motif 4), G2like (motif 5), and C2C2gata (motif 6), were present in 57.54%, 54.74%, 23.86%, and 10.88% of the genes, respectively, highlighting the diverse regulatory elements that may contribute to the observed highly expressed genes.

To examine the regulatory role of PAW in sorghum gene expression, particularly because of the predominant trend of upregulated genes, we focused on the TF family. TFs are crucial for regulating gene expression in various BPs. Using data from the Plant Transcription Factor Database (https://planttfdb.gao-lab.org/index.php?sp=Sbi), which identified 2,654 TFs (1,859 loci) in sorghum, we analyzed their expression under DW and PAW100 treatments. Our findings revealed that 144 of these TF genes significantly exhibited differential expression, 82% upregulated and 18% down-regulated, in response to PAW treatment compared to the control ( Figure 6B ). Among these, TF families, including 19 Ethylene Response Factors (ERF), 15 basic helix–loop–helix (bHLH), and 14 MYB, were notably differentially expressed in the PAW-treated group.