Comparative transcriptome analysis of foxtail millet variety JG21 and resistant mutant unravels the key players associated with downy mildew resistance

Comparative transcriptome analysis of foxtail millet variety JG21 and resistant mutant unravels the key players associated with downy mildew resistance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative transcriptome analysis of foxtail millet variety JG21 and resistant mutant unravels the key players associated with downy mildew resistance Yanqing Han, Anqi Wei, Yongchao Zhang, Hengbo Xiao, Xinyan Liang, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7495945/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Mar, 2026 Read the published version in BMC Plant Biology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Foxtail millet downy mildew, incited by the obligate parasite Sclerospora graminicola , represents a highly devastating disease for foxtail millet. The infection of Sclerospora graminicola frequently causes harm to budlets, leaves, and spikes of foxtail millet, thereby substantially influencing its quality and yield. Nevertheless, disease - resistant varieties can effectively reduce the vulnerability to pathogen attacks. Results In this study, we explored Jingu21 (JG21) and the resistant mutant rdm12, which was generated by ethyl methanesulfonate (EMS) mutagenesis. Phenotypic observations revealed that, in comparison with JG21, rdm12 did not display significant disparities in agronomic and quality characteristics. Significantly, rdm12 manifested disease resistance, accompanied by augmented activities of defense enzymes and elevated levels of osmoregulatory substances. Transcriptome analysis of rdm12 mutants and wild-type plants disclosed that the differentially expressed genes were predominantly enriched in pathways such as plant-pathogen interaction, MAPK signaling, phenylpropanoid biosynthesis, and glutathione metabolism signaling. The differential expression of several critical receptor protein kinase genes, WRKY transcription factors, pathogenesis - related (PR) proteins, calmodulin, glutathione S - transferase, and others endows the mutants with enhanced resistance to downy mildew. In particular, WRKY transcription factor 53 encoded by Seita.3G139400 , pathogenesis-related protein PRMS encoded by Seita.3G175100 and G-type lectin S-receptor-like serine/threonine protein kinase coded by Seita.7G095600 , which have played an essential resistant role during the infection by S. graminicola . Conclusions Through this research, we identified the key genes, important products engaged in the resistance process, and their corresponding metabolic pathways, thus unravelling the resistance mechanism of foxtail millet against S. graminicola infection. These findings lay a theoretical groundwork for resistance screening in foxtail millet and the development of new varieties. Foxtail millet Downy mildew Sclerospora graminicola Transcriptome Differentially expressed genes Resistance mechanism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Foxtail millet [ Setaria italica (L.) P. Beauv.] is one of the important coarse cereals in the north China, and it is with the strongest drought resistance and wide adaptability [ 1 ]. However, with the change of tillage system, there is a risk of being damaged by various pathogens, which not only inhibits the foxtail millet normal growth, but also affects its yield and quality [ 2 , 3 ]. Downy mildew is one of the most important diseases of foxtail millet, which can occur throughout the growth periodand show different symptoms. The pathogen oospores germination began to infect the young buds, resulting in "bud death or bud rot". If the infection is mild, the back of the leaves will show "gray back" symptoms at the seedling stage. A series of symptoms followed, such as "white tip", "gun", "hair" and "hedgehog" etc. The disease can lead to the reduction yield and quality, which brings a great threat to foxtail millet production [ 3 , 4 ]. Given the harm caused by downy mildew, the selection and promotion of varieties resistant is an economical and environmentally friendly way to control downy mildew damage [ 5 , 6 ]. Jingu 21 is an excellent variety, which is famous for its "high yield and high quality" and is widely planted in the main planting areas in Shanxi [ 7 ]. Unfortunately, it has become very susceptible to S. graminicola , causing serious yield losses to farmers. So far, several methods have been used to control downy mildew, including spray chemical fungicides, select coated seeds, application of various agricultural regulation measures [ 8 , 9 ]. However, cultivating and utilizing disease-resistant varieties is the best way and environmental sustainable strategy [ 10 ]. Genetic improvement of excellent varieties and breeding of disease-resistant varieties are particularly urgent. Traditional breeding methods can take seven to eight years or more to screen resistant varieties. Thankfully, FAO and the IAEA have obtained more than 3,200 new crop varieties through mutagenesis, about 80% of which were obtained through physical mutagenesis [ 11 , 12 ]. Mutation breeding is a promising strategy to develop resistant varieties. The resistance mutant WYB-18 obtained by ethyl methylsulfonate (EMS) showed resistance to black spot disease, and provided a theoretical basis for the cultivation of later resistance varieties [ 13 ]. Similarly, embryogenic cell suspension (ECS) were mutagenized by EMS, screened for fusarium wilt resistant mutant in banana, played an important role in fusarium wilt resistance [ 11 ]. The roots of Cuibi-1 (CB-1) and mutant KCB-1 were by metabolome and transcriptome studies, some important metabolites in the phenylpropanoid pathway, and and hormone signals pathway, indole-3-acetic acid (IAA) and abscisic acid (ABA) in CB-1 and KCB-1 were involved in the response to R. solanacearum infection [ 14 ]. Foxtial millet as an important coarse cerea crop, with the improvement of people's quality of life and health awareness in the domestic market demand is also increasing. The disease resistance varieties is the internal factor affecting the occurrence of disease. Therefore, It was devoted to the study of inherent disease resistance of foxtial millet, and applied a relatively common and efficient breeding method-EMS mutagenesis, to obtain the mutant plants. Combined with the field resistance identification, the mutant's phenotype, agronomic traits, quality traits and physiological and biochemical characteristics were compared. At the same time, transcriptome sequencing was used to study the defense mechanism of foxtial millet infected by S. graminicola , in order to obtain the differential genes and the disease resistance or susceptibility mechanism involved. The aim of this study was to lay a theoretical foundation for disease resistance breeding of foxtial millet and provide some reference for breeding of other coarse cereals. Materials and methods Plant materials and growth conditions A stable, downy mildew-resistant mutant designated as rdm12 was isolated from a mutant library of Jingu 21, a foxtail millet variety. The library was constructed via mutagenesis with 1% ethyl methanesulfonate (EMS). Jingu 21 is a widely cultivated foxtail millet variety in northern China, valued for its superior grain quality and high yield. It was originally collected and is preserved by the Coarse Cereal Molecular Breeding Team of Shanxi Agricultural University. To minimize heterozygosity, the rdm12 mutant was subjected to five consecutive generations of forced self-pollination under greenhouse conditions. All plant materials were grown in experimental fields situated in Taigu District (37°25′13″ N, 112°35′26″ E), Shanxi Province, China. Pathogen inoculation and sample preparation In 2021, each foxtail millet material was divided into treatment and control groups, with three biological replicates established for each group. Each plot had an area of 9 m² (3 m × 3 m), with a row spacing of 30 cm, plant spacing of 15 cm, and sowing depth of 3–5 cm. All plots were maintained under consistent cultivation conditions and subjected to conventional field management, including thinning, watering, and weeding. Zoospores used for inoculation were collected from the abaxial surface of fresh diseased leaves. Inoculation was performed during continuous cloudy weather at the heading stage: 1 mL of sporangium suspension (3×10⁵zoospores/mL) was injected into the middle of spikelets. Thirty panicles with uniform growth were selected for inoculation, among which three panicles were harvested for transcriptome sequencing, and the remaining panicles were used for disease incidence. For transcriptome analysis, panicles were collected at 12 h and 24 h post-inoculation. Control plants were inoculated with sterile water, with three replicates per sample. All collected panicles were labeled, immediately frozen in liquid nitrogen, and stored at − 80℃. Fifteen days after inoculation, diseased panicles were surveyed, and resistance levels were classified according to the criteria outlined in Table S1 . Investigation of agronomic traits, yield, and quality At maturity, five plants were randomly selected from each genotype, and the following traits were measured from the base of the plants, with mean values calculated: plant height (PH), number of main stem nodes (NNMS), main panicle length (MPL), main panicle diameter (MPD), main stem diameter (MSD), panicle weight per plant (PWP), grain weight per plant (GWP), and 1000-grain weight (TGW). Data were analyzed for significant differences using Excel and SPSS 26.0 software. Mature grains were collected from three individual plants of each genotype, with three independent biological replicates analyzed. Grains were dried, threshed, and their color was measured using a colorimeter (X-rite VS50, Danaher Corporation, Washington, DC, USA). For each genotype, 5 g of grains from three individual panicles were collected separately, ground in liquid nitrogen, and measured using the colorimeter [ 15 ]. Protein content was determined using the micro-Kjeldahl method with an automatic discrete chemistry analyzer (SmartChem140, AMS-Alliance Co., Paris, France) [ 16 ]. Starch content was measured according to the method of the Association of Official Agricultural Chemists (AOAC) [ 17 ], and gel consistency was determined as described by [ 18 ]. Amino acid content was measured following the method of [ 19 ]. Determination of antioxidant enzyme activities (SOD, POD, CAT), malondialdehyde (MDA), soluble sugar, and proline (Pro) contents Crude enzyme extracts were prepared as follows: approximately 0.1 g of fresh panicle tissue was chopped and ground to a powder in liquid nitrogen, transferred to a 2 mL centrifuge tube, mixed with 1 mL of extraction buffer, and centrifuged at 12,000 rpm at 4℃ for 10 min. The supernatant was collected for subsequent assays, with the entire extraction process performed on ice. Activities of SOD, POD, and CAT, as well as contents of MDA, soluble sugar, and proline in young panicles, were determined using commercial kits (Boxbio, Beijing, China) and a UV-visible spectrophotometer (UV-1200, Mapada Instruments, Shanghai, China). Soluble sugar content was additionally verified by anthrone colorimetry [ 20 ]. Proline content was measured according to the method of with minor modifications [ 21 ]. Statistical analysis was performed using SPSS 16.0 software. Differences between the resistant mutant and susceptible parent were tested by analysis of variance (ANOVA), and significance between genotypes was determined using Fisher’s Least Significant Difference (LSD) test at the 0.05 level. All experiments were conducted independently. RNA extraction, library construction, and sequencing For RNA extraction, over 500 mg of panicle tissue was collected from wild-type JG21 and mutant rdm12. For ease of labeling in transcriptome sequencing, JG21 was designated "S" (susceptible) and rdm12 as "R" (resistant). Total RNA was extracted using a Universal Total RNA Extraction Kit (centrifugal column type, Beijing Newbate Biotechnology Co., Ltd.) following the manufacturer’s protocol. Subsequently, 1 µg of total RNA from each sample was used for library construction with the NEBNext Ultra RNA Library Prep Kit (NEB, MA, USA), and sequencing was performed on an Illumina HiSeq 4000 platform (Novogene, China). Raw sequencing data were filtered, screened, and assembled as described by Zhang et al. to generate contigs [ 22 ], which were then aligned to the foxtail millet genome in GenBank using BLASTx and BLASTn. Sequencing data analysis Raw reads were processed to remove adapters, poly-N sequences, and low-quality reads, yielding clean reads that were mapped to the reference genome (Setaria italica v2.2; https://phytozome.jgi.doe.gov/pz/portal.html#!info?alias=Org_Sitalica ). Gene expression levels were normalized as fragments per kilobase of transcript per million mapped reads (FPKM) for cross-sample comparison [ 23 ]. Differentially expressed genes (DEGs) between S. graminicola -inoculated and mock-inoculated plants were identified using thresholds of absolute log₂(fold change) ≥ 1 and false discovery rate (FDR) < 0.01. DEGs were subjected to Gene Ontology (GO) functional enrichment analysis, with GO terms considered significantly enriched at a P-value < 0.05. Additionally, clusters of orthologous groups (KOG) and pathway analyses were performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database ( http://www.genome.jp/kegg ) [ 24 ] . Real-time quantitative PCR (qRT-PCR) assay Total RNA was extracted using a plant RNA extraction kit (Cowin Biotech, Jiangsu, China), and first-strand cDNA was synthesized using a cDNA Synthesis Kit (Takara, Japan). The foxtail millet Actin gene was used as the internal reference. Primers were designed using Primer Premier 6.0 software, with sequences listed in Table S2 qRT-PCR was performed using the SYBR Green Quantitative RT-qPCR Kit (Takara, Japan) on a CFX96™ Real-Time System (Bio-Rad), with three technical replicates per sample. Results Comparison of resistance differences between JG21 and mutant rdm12 to S.graminicola We compared the resistance of JG21 and the mutant rdm12 to downy mildew. Specifically, the disease incidence of JG21 and rdm12 following inoculation with S. graminicola was recorded under field and greenhouse conditions, respectively. JG21 displayed high susceptibility to downy mildew, with disease incidences of 38.25% (field) and 47.33% (greenhouse). In contrast, the mutant rdm12 exhibited strong re-sistance to the disease, with significantly lower incidences of 0.44% (field) and 2.70% (greenhouse) (Fig. 1 ). These results indicate a marked contrast in the resistance and susceptibility of JG21 and rdm12 after infection with S. graminicola . Characterization of agronomic and grain quality traits in JG21 and its mutant rdm12 In the field, agronomic traits (including plant height, stem diameter, ear length, and ear diameter) were investigated at the heading stage. Additionally, at the heading stage, measurements were taken for plant height, number of internodes, stem diameter, spike length, spike diameter, spike weight, grain weight per spike, and 1000-grain weight. The plant height of JG21 (179.46 ± 4.55 cm) was significantly greater than that of rdm12 (134.52 ± 4.57 cm), with a difference of 44.94 cm; the mutant also had fewer internodes than JG21. The spike length of rdm12 (29.33 ± 2.73 cm) was longer than that of JG21 (23.56 ± 2.73 cm), while its spike diameter (29.93 ± 2.87 cm) was smaller than that of JG21 (34.2 ± 1.88 cm). Determination of three yield-related indices revealed that the spike weight, grain weight per spike, and 1000-grain weight of JG21 were slightly higher than those of rdm12 (Fig. 2 ). To compare differences in nutritional quality between JG21 and rdm12, the protein content, fat content, gel consistency, and amylose content of grains were measured (Fig. 2 ). The protein and fat contents of JG21 were slightly higher than those of rdm12, though the differences were not significant. In contrast, rdm12 exhibited higher gel consistency and amylose content than JG21, with a significant difference in gel consistency between the two (P < 0.05). Amino acid analysis of the two materials showed that among the 17 detected amino acids, glutamic acid had the highest content: 2.56 ± 0.01 in JG21, which was slightly higher than in rdm12 (2.47 ± 0.03). Cysteine had the lowest content, at 0.14 ± 0.01. By comparison, the mutant contained relatively higher levels of 9 amino acids than JG21, while 5 amino acids (Glu, His, Ile, Leu, Pro, Thr) were present at lower levels in rdm12; however, none of these differences in amino acid content were significant (Fig. 2 ). Differences in physiology and biochemistry between JG21 and rdm12 We compared the activities of protective enzymes and contents of osmoregulatory substances in JG21 and rdm12 after infection by S. graminicola . For protective enzymes, both JG21 and the mutant rdm12 showed increased superoxide dismutase (SOD) activity post-infection, with rdm12 exhibiting significantly higher SOD activity than JG21 (Fig. 3 ); in contrast, peroxidase (POD) activity decreased in both genotypes, and the reduction in JG21 reached a significant level compared with its corresponding uninfected control. Regarding catalase (CAT), rdm12 maintained significantly higher activity than JG21 both before and after inoculation JG21 showed a significant decrease in CAT activity after inoculation, while rdm12 exhibited an increase. We also determined the contents of malondialdehyde (MDA), soluble sugars, and proline (Fig. 3 ): uninfected rdm12 had a significantly higher MDA content than uninfected JG21, and after inoculation, MDA content in JG21 increased significantly compared with its control, whereas no significant difference was observed between infected rdm12 and its control. For osmoregulatory substances, JG21 and the mutant showed the same trend in soluble sugar and proline contents after inoculation: both exhibited a decrease in soluble sugar content relative to their respective controls, with JG21 showing a significant reduction, while rdm12 maintained significantly higher soluble sugar and proline contents than JG21 regardless of inoculation status. Sequencing, data processing and differentially expressed genes(DEGs) Sequencing yielded a total of 170.47 Gb of clean data, with each sample generating at least 5.99 GB. Across all 24 samples, the Q30 base percentage exceeded 93%, and the GC content (percentage of guanine and cytosine bases relative to total bases) was over 52% (Table S3). Alignment with the foxtail millet reference genome showed that the total read mapping rate for each sample exceeded 95%, indicating high coverage and good quality of the sequencing data, which was suitable for further analysis. The correlation coefficients between different samples are presented in Fig. 4 A. Using an adjusted P-value < 0.05 as the threshold for screening DEGs, we identified the following expression changes in response to S. graminicola infection at 12 and 24 hours, compared to their respective controls: 2816 (12 h resistant, 12 R), 1139 (24 h resistant, 24 R), 961 (12 h susceptible, 12 S), and 924 (24 h susceptible, 24 S) up-regulated genes, as well as 531 (12 R), 626 (12 S), 49 (24 R), and 25 (24 S) down-regulated genes (Fig. 4 B). A total of 68 genes were differentially expressed between the resistant and susceptible genotypes (Fig. 4 C). After excluding 27 genes without functional zwsannotations, heatmap analysis was performed on the remaining 41 genes(Table S4). Among these, 87.7% (36 genes) were significantly induced and up-regulated at 12 h post-infection, with no significant expression changes observed at 24 h (Fig. 4 D). Notably, the expression patterns of these genes in the susceptible genotype were the reverse of those in the resistant genotype, suggesting that these genes may play a regulatory role in downy mildew resistance in the resistant variety. GO functional enrichment and expression level analysis of DEGs Using a screening threshold of p-value ≤ 0.01, GO enrichment analysis was performed on the differentially expressed genes (DEGs) of JG21 and its disease-resistant mutant rdm12 at 12 h and 24 h post-inoculation. The enrichment results showed that, in terms of GO terms, the DEGs were primarily associated with biological processes including cell surface receptor signaling pathway, defense response to bacteria, protein phosphorylation, glutathione metabolic process, cell wall macromolecule catabolic process, chitin catabolic process, hydrogen peroxide catabolic process, response to oxidative stress (Fig. S1 ). For molecular function, the DEGs were mainly linked to glutathione transferase activity, chitinase activity, calcium ion binding, chitin binding, UDP-glycosyltransferase activity, and peroxidase activity. Notably, the GO term "defense response to oomycetes" was specific to rdm12: 13 DEGs were enriched at 12 h post-inoculation, 9 at 24 h, with 9 DEGs shared between the two time points. All 9 shared genes contain an L-type lectin domain, among which five are receptor kinases with L-type lectin domains; these genes were significantly up-regulated in rdm12 (Fig. 5 ). Notably, the GO term "defense response to oomycetes" was specific to rdm12: 13 DEGs were enriched at 12 h post-inoculation, 9 at 24 h, and 9 DEGs were shared between the two time points. All 9 shared genes contain an L-type lectin domain, among which five are receptor kinases with L-type lectin domains; these genes were significantly up-regulated in rdm12 (Fig. 5 ). KEGG pathway enrichment analysis of DEGs To identify metabolic pathways involved in the response to S. graminicola infection, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on differentially expressed genes (DEGs). As shown in Fig. 6 , our focus was on significantly enriched metabolic pathways in JG21 and its disease-resistant mutant rdm12 at two post-infection time points (12 h and 24 h). The DEGs were significantly enriched in pathways including diterpenoid biosynthesis, phenylpropanoid biosynthesis, MAPK signaling pathway, plant - pathogen interaction, starch and sucrose metabolism, carotenoid biosynthesis, flavone and flavonol biosynthesis, glutathione metabolism, photosynthesis-antenna proteins, zeatin biosynthesis, and alpha-linolenic acid metabolism indicating that these pathways are strongly induced by S. graminicola infection (Fig. 6 ). Notably, in the susceptible genotype JG21, both diterpenoid biosynthesis and plant–pathogen interaction pathways were significantly enriched at 12 h and 24 h post-infection; in rdm12, however, only the plant-pathogen interaction pathway was consistently enriched at both time points. Among these pathways, the plant-pathogen interaction pathway contained the largest number of DEGs (38 genes). Additionally, 31 DEGs were enriched in the MAPK signaling pathway and 10 in diterpenoid biosynthesis, further highlighting their involvement in the host–pathogen interaction. These results suggest that S. graminicola infection activates these pathways to mediate defense responses. We further analyzed the genes within these key pathways. Altered expression of plant-pathogen interaction-related genes in the mutant rdm12 Compared with JG21, in rdm12 at 12 h post-inoculation, the expression of two CDPK genes ( Seita.3G128600 and Seita.9G043400 ) was significantly induced by S. graminicola , with their expression levels being significantly higher than those in JG21. Reactive oxygen species (ROS) act as crucial signaling molecules in plant disease resistance, and Rboh is a key enzyme involved in ROS production. The expression patterns of two Rboh genes in JG21 and rdm12 were opposite: Rboh expression in rdm12 was up-regulated at 12 h but inhibited at 24 h, whereas in JG21, it was inhibited at 12 h followed by significant induction and up-regulation at 24 h (Fig. 7 ). The calmodulin/calmodulin-like (CaM/CML) signaling system plays an important role in plant disease resistance. In rdm12, 8 CaM/CML genes were up-regulated, with expression patterns opposite to those in JG21. As a plant receptor kinase, BAK1 (BRI1-associated kinase 1) perceives extracellular signals to regulate immune responses and disease resistance; in this study, the expression of 6 BAK1-like receptor kinases was significantly up-regulated upon infection (Fig. 7 ). Numerous studies have confirmed that the primary biological function of the plant WRKY gene family is to regulate resistance responses and establish signal transduction pathways. Here, 18 WRKY genes were significantly up-regulated in response to pathogen attack. Additionally, the pathogenesis-related protein gene PR1, mitogen-activated protein kinase Seita.9G444100 (mitogen-activated protein kinase/extracellular signal-regulated kinase 3), and Seita.5G175100 (MEKK3, mitogen-activated protein kinase kinase kinase 3) were significantly up-regulated at 12 h post- S. graminicola infection (Fig. 7 ). Altered expression of MAPK signaling pathway-related genes in the mutant rdm12 The MAPK cascade plays a critical role in PAMP-triggered immunity (PTI), primarily transmitting signals from pattern recognition receptors (PRRs) to downstream transcription factors. We analyzed differentially expressed genes (DEGs) involved in the MAPK signaling pathway and found that in rdm12, several key genes were significantly induced and up-regulated following S. graminicola infection (with the exception of Seita.5g095400 )(Fig. 8 ). These included seven transcription factor genes (four WRKYs, two ERFs, and one other transcription factor), five pathogenesis-related ( PR ) genes ( Seita.2g024600 , Seita.2g024800 , Seita.2g024900 , Seita.9g0435200 , and Seita.5g0175100 ), three calmodulin-like (CML) protein genes (homologous to those in Chinese cabbage), and three rust resistance Lr10 genes. Additionally, several receptor protein kinases were activated in rdm12, such as GsSRK homologs ( Seita.5g016900 , Seita.7g095600 , and Seita.7g045600 ), mitogen-activated protein kinase kinase kinases (MPKKKs), two leucine-rich repeat receptor-like kinases (LRR-RLKs), wall-associated kinase 10 (WAK10; Seita.8g152000 ), and serine/threonine kinase (STK; Seita.8G151600 ) all of which were up-regulated(Fig. 8 ). Altered expression of glutathione metabolism and phenylpropanoid biosynthesis pathways in rdm12 Both the glutathione metabolism and phenylpropanoid biosynthesis pathways were enriched following S. graminicola infection. As shown in Fig. 9 , among the 12 genes involved in glutathione metabolism, glutathione S-transferase (GST) genes were induced and up-regulated at 12 h post-infection but exhibited decreased expression at 24 h in rdm12, whereas their expression patterns were opposite in JG21. Expression of deglutathionylation (DGS) genes remained inhibited and down-regulated throughout, with the exception of Seita.3g0387000 . These results suggest that glutathione S-transferase may promote glutathione synthesis to counteract infection during the early stage. In rdm12, the expression patterns of differentially expressed genes in the phenylpropanoid pathway were opposite to those in JG21 at both infection stages. Compared to JG21, rdm12 showed inhibited and down-regulated expression of 5 cytochrome P450 genes, 3 momilactone A synthase genes, 2 ent-kaurene oxidase 2 genes, 1 terpene synthase (TPS13) gene, and 1 ent-copalyl diphosphate synthase 1 gene at 12 h post-infection, followed by significant up-regulation at 24 h. Validation of transcriptomic data by RT-qPCR To validate the differentially expressed genes (DEGs) identified from RNA-Seq data, 20 DEGs were selected for quantitative real-time PCR (qRT-PCR) analysis. These genes were potentially involved in defense responses against S. graminicola and exhibited distinct expression patterns between the resistant (rdm12) and susceptible (JG21) genotypes. The relative expression levels of all tested genes were normalized using the constitutively expressed Actin gene as an internal reference.The expression profiles of these genes determined by qRT-PCR were consistent with the results from RNA-Seq analysis (Fig. 10 ), confirming the reliability of the transcriptomic data. Discussion Downy mildew is a highly destructive disease that severely impacts foxtail millet production, leading to poor grain development and substantial yield losses. To date, although some studies have initiated the identification of resistance genes or loci, progress in this area remains limited [ 2 , 3 ]. In the present study, we used the elite foxtail millet variety JG21 and its downy mildew-resistant mutant rdm12 generated via ethyl methanesulfonate (EMS) mutagenesis which exhibits developmental abnormalities, most notably stunted growth and shortened internodes (Fig. 2 A). Integrating phenotypic, physiological, and biochemical analyses with transcriptome sequencing, we explored the potential disease resistance regulatory mechanisms associated with the rdm12 mutant phenotype. Genome-wide transcriptomic profiling of rdm12 and wild-type JG21 identified a number of differentially expressed genes (DEGs), which were enriched in pathways such as plant-pathogen interaction, MAPK signaling, phenylpropanoid biosynthesis, and glutathione metabolism. These findings help to clarify the transcriptional regulatory basis underlying the rdm12 mutant phenotype. Plant growth and defense processes are regulated by numerous antagonistic molecular pathways, giving rise to the so-called "growth-defense trade-off": plants transiently suppress growth in response to pest or pathogen attacks. Due to this inherent antagonism, genetic variations enhancing disease tolerance typically reduce growth, while those promoting growth often compromise disease resistance [ 25 ]. Derbyshire et al. (2024) reported an inverse correlation between yield and disease resistance, noting that highly resistant genotypes tend to have lower yields, whereas susceptible genotypes often exhibit higher yields [ 26 ]. Notably, this unfavorable association is disrupted in the rdm12 mutant, suggesting the potential for combining favorable agronomic traits with disease resistance similar to the results of gene-editing techniques that have generated wheat and rice lines with both disease resistance and high-yield potential [ 27 , 28 ]. Thus, Thus, the use of mutants plays a certain role in promoting the genetic improvement of foxtail millet When plants detect pathogens, oxidative stress occurs, leading to the overproduction of reactive oxygen species (ROS). Pathogen-induced ROS act as signaling molecules that actively trigger downstream signaling cascades, thereby activating host basal resistance [ 29 ]. However, cellular ROS levels must be dynamically balanced to avoid excessive oxidative stress. Concurrently with the upregulation of defense-related genes, intrinsic antioxidant pathways are activated to counteract this stress. Increases in enzymes such as polyphenol oxidase (PPO), superoxide dismutase (SOD), and catalase (CAT) are critical for scavenging harmful free radicals and maintaining cellular redox homeostasis [ 30 , 31 ]. In this study, compared with the susceptible genotype JG21, the resistant mutant rdm12 showed significantly higher SOD and CAT activities, indicating that rdm12 can rapidly degrade free radicals generated during pathogen invasion [ 32 , 33 ]. For susceptible varieties, even with host-produced antioxidants, maintaining optimal ROS levels remains challenging: reduced ROS-scavenging capacity leads to marked ROS accumulation, inducing disease susceptibility [ 34 ]. This can damage host DNA and membranes, ultimately resulting in plant death. Similarly, resistant mutants accumulated higher levels of soluble sugars and malondialdehyde (MDA) than susceptible JG21. Soluble sugars have been positively associated with resistance to Bois Noir Phytoplasma in Vitis vinifera cv. Sangiovese [ 35 ] and to fusarium wilt in pigeon pea ( Cajanus cajan ) [ 36 ]. Lectin receptor-like kinases (LecRLKs) form a distinct subfamily of receptor-like kinases, classified into three types (L, G, and C) based on domain differences [ 37 ]. In plants, LecRLKs act as key sentinels of immunity, playing indispensable roles in defense against diverse microorganisms [ 38 , 39 ]. Previous studies have shown that Arabidopsis LecRKs effectively resist Phytophthora infections [ 40 ], while LecRKs in Nicotiana benthamiana and tomato exhibit strong resistance to Phytophthora [ 41 ]. Recent research has further revealed that L-type LecRKs regulate soybean resistance to Phytophthora sojae [ 42 ], and a novel lectin receptor kinase gene, AtG-LecRK-I, enhances Arabidopsis resistance to bacterial pathogens by modulating stomatal immunity [ 43 ]. In the present study, GO enrichment analysis identified "defense response to oomycetes" as a unique term in rdm12, with 9 LecRKs significantly upregulated in the mutant (Fig. 5 ). This suggests that LecRKs are strongly induced in foxtail millet upon S. graminicola infection and likely contribute to downy mildew resistance. During the long-term co-evolutionary interplay between plants and pathogens, a suite of key genes collaborates to form a precise and intricate defense network. In this study, genes such as CDPK , Rboh , CaM/CML , BAK1 , MEKK3 , WRKY , and PR1 played pivotal regulatory roles in the interaction between foxtail millet and downy mildew pathogens(Fig. 7 ). Comprehensive analysis of their regulatory relationships is crucial for deciphering plant immune mechanisms and provides novel insights for foxtail millet disease control and resistance breeding [ 44 ]. Firstly, BAK1 can be considered the "pioneer" of plant immunity initiation. When pathogens invade, their pathogen-associated molecular patterns (PAMPs) are specifically recognized by pattern recognition receptors (PRRs) on the plant cell membrane. At this point, BAK1 acts as a co-receptor, rapidly associating with PRRs to form complexes and initiate immune signal transduction cascades [ 45 ]. This recognition is highly specific and sensitive; once triggered, it rapidly activates downstream defenses, serving as the first critical checkpoint for plants to resist pathogen invasion. For example, when Arabidopsis thaliana encounters Pseudomonas syringae , BAK1 and FLS2 collaborate to activate early immune signals within a short timeframe, facilitating subsequent defense responses [ 46 ]. Secondly, pathogen invasion induces rapid changes in cellular calcium ion concentrations. CaM/CML proteins act as "sensors" that detect this signal; upon binding calcium ions, they undergo conformational changes to activate CDPK [ 47 ]. As a key signaling kinase, CDPK targets multiple substrates, with its regulation of Rboh being particularly significant. Activated CDPK phosphorylates Rboh , significantly enhancing its NADPH oxidase activity and promoting massive ROS production [ 48 ]. ROS not only directly eliminate pathogens but also act as signaling molecules to activate downstream defense-related genes, triggering broader immune responses such as the MAPK cascade [ 49 ]. In the MAPK cascade, MEKK3 serves as a pivotal link between upstream and downstream components. Upstream signals (e.g., ROS) trigger MEKK3 activation, which then sequentially phosphorylates and activates downstream MAPKK and MAPK [ 50 ]. Activated MAPK translocates to the nucleus, where it phosphorylates and activates WRKY transcription factors [ 51 ].The WRKY family comprises numerous members that recognize and bind to W-box elements in target gene promoters, thereby regulating their expression. In plant-pathogen interactions, WRKYs can activate multiple defense genes, including PR1 [ 52 ]. PR1 , often regarded as a "terminal weapon" in plant defense, is highly expressed under WRKY regulation [ 53 ]. The PR1 protein exhibits diverse antimicrobial properties, directly inhibiting pathogen growth, reproduction, and spread, and acts as a key effector of the plant defense response [ 54 ]. High PR1 expression typically indicates successful initiation of the plant immune response and active resistance to pathogen invasion. In summary, these genes form a tightly integrated, interdependent regulatory network during plant-pathogen interactions, with each component being essential and mutually influential [ 55 ]. Glutathione (GSH) is a key plant antioxidant that plays a critical role in resistance to pathogen infections [ 56 ]. It participates in defense responses against various biotic stresses, including fungi, nematodes, viruses, and bacteria [ 57 ]. Overexpression of PdbGSTU10 increases salicylic acid (SA) content and induces SA signaling-related genes, suggesting that PdbGSTU10 enhances poplar resistance to Alternaria by scavenging ROS and modulating the SA pathway [ 58 ]. Glutathione also influences plant resistance to nematodes by precisely regulating the balance between cellular redox status and defense compound production [ 59 ]. Zhu et al. (2021) found that GSH regulates plant immune responses against viruses via SA and ROS signaling pathways [ 60 ]. In this study, 10 differentially expressed glutathione S-transferase genes between wild-type JG21 and rdm12 were identified, suggesting their involvement in host defense against S. graminicola . The phenylpropanoid metabolic pathway has several important biological functions: (1) participating in plant disease resistance and immunity; (2) contributing to cell lignification; and (3) involved in cytochrome synthesis, among others [ 61 ]. On one hand, lignin synthesized via this pathway promotes cell wall lignification and thickening, forming a physical barrier that prevents pathogen invasion [ 62 ]. On the other hand, metabolites such as phenols and isoflavones can be further synthesized into phytoalexins, inhibiting pathogen growth [ 63 ]. Additionally, this pathway is involved in SA synthesis, a key plant defense hormone that activates immune signaling pathways to comprehensively regulate disease resistance [ 64 ]. Our results showed that cytochrome P450, momilactone A synthases, ent-kaurene oxidase 2, terpene synthase TPS13, and ent-copalyl diphosphate synthase are differentially expressed in this pathway and participate in defense against S. graminicola . It is worth noting that in the analysis of transcriptome data, we found that among the co-differentially expressed genes in JG21 and rdm12 at 12 and 24 hours after infection by S. graminicola , 3 genes ( Seita.3G139400 , WRKY transcription factor 53; Seita.3G175100 , pathogenesis-related protein PRMS; Seita.7G095600 , G-type lectin S-receptor-like serine/threonine protein kinase) overlapped with 3 genes in the plant-pathogen interaction pathway of the KEGG metabolic pathway, and they showed significant differential expression. We speculate that these three differentially expressed genes may play important roles in regulating the resistance process against downy mildew, and subsequent studies will conduct more in-depth research focusing on these 3 genes. Conclusions In this study, comparative analysis of the foxtail millet variety JG21 and its EMS-mutagenized downy mildew-resistant mutant rdm12 revealed that rdm12 showed no significant differences in agronomic or quality traits compared to JG21, yet exhibited significantly enhanced resistance to the downy mildew pathogen S. graminicola . This resistance was associated with elevated activities of defense-related enzymes and increased accumulation of osmoregulatory substances. Transcriptome analysis identified differentially expressed genes predominantly enriched in pathways including plant-pathogen interaction, MAPK signaling, phenylpropanoid biosynthesis, and glutathione metabolism. Key genes implicated in the resistance mechanism include WRKY transcription factor 53 ( Seita.3G139400 ), pathogenesis-related protein PRMS ( Seita.3G175100 ), and G-type lectin S-receptor-like serine/threonine-protein kinase ( Seita.7G095600 ). These findings provide valuable insights into the molecular mechanisms governing downy mildew resistance in foxtail millet. In subsequent studies, we will conduct in-depth dissection of gene functions and further decipher the molecular basis of disease resistance. Declarations Acknowledgements The authors would like to thank Yang Yang for discussion of the project and suggestions for the manuscript. Author contributions Conceptualization, Y.H., Y.H.(Yuanhuai Han), and S.H.; data curation, A.W. and Y.Z.; formal analysis, H.X., X.L., and W.Z.; investigation, Z.C. and X.G.; methodology, Y.H.; project administration, Y.H.; resources, L.S., Y.F., and H.H.; software, Y.Z.; supervision, Y.H.; validation, M.J., H.W., and H.W.; visualization, Z.C. X.G., and Z, Z.; writing original draft preparation, Y.H.; writing review and editing, H.W.,and Y.H.. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by grants from the Science and Technology Innovation Enhancement Project of Shanxi Agricultural University (CXGC2025088) ，the Shanxi Houji Laboratory Self-initiated Research Projects (202404010930003-J05)，and Jin Cainong (2025) No. 19 24 Make breakthroughs in key and core agricultural technologies (TK244702085, NYGG19-01-01), and the College Students Innovation Training Program of Shanxi Agricultural University (S202410113010, S202410113007, S202510113005), and the Agricultural Civilization Insect Design Scheme and Teaching Specimen Production Project (20231916330). Data availability The raw sequencing data generated in this study are available in SRA (https://www.ncbi.nlm.nih.gov/sra/PRJNA1299158) of NCBI with the accession numbers PRJNA1276485. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. 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14:38:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7495945/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7495945/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-026-08520-y","type":"published","date":"2026-03-13T16:00:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91641977,"identity":"478584d5-ca4e-401c-b813-a96328977c2a","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5822401,"visible":true,"origin":"","legend":"\u003cp\u003e(A) After being inoculated with \u003cem\u003eS. graminicola\u003c/em\u003e, Jingu 21 showed disease symptoms of \"hair\" and \"hedgehog \", The mutant rdm12 did not produce any disease phenotype. (B) Statistics of downy mildew incidence rate of JG21 and rdm12.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/4b02f987f844c44a2eb36220.png"},{"id":91643245,"identity":"671b0b98-fa8e-4301-9f62-fb1c6957c214","added_by":"auto","created_at":"2025-09-18 15:22:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1251675,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences in agronomic and quality traits between JG21 and mutant rdm12. (A) Comparison of plant height, panicle length, panicle diameter, stem diameter, panicle weight, grain weight per spikelet, and 1000-grain weight. (B) Comparison of protein content, fat content, gel consistency, starch content and the contents of 17 amino acids.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/b98b805f3549f36f764cd01f.png"},{"id":91642913,"identity":"4f14700b-8751-48d7-b951-db3a7c2d8a70","added_by":"auto","created_at":"2025-09-18 15:14:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":914729,"visible":true,"origin":"","legend":"\u003cp\u003eA comparison of the differences in physiological and biochemical characteristics between JG21 and rdm12. (A) Comparison SOD enzyme activity before and after inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e. (B) Comparison POD enzyme activity before and after inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e. (C) Comparison CAT enzyme activity before and after inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e. (D) Comparison of MDA content before and after inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e. (E) Comparison of soluble sugar content before and after inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e. (F) Comparison of Pro content before and after inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/eca4e46f2f6eeed228074881.png"},{"id":91641982,"identity":"13a45df2-12e9-4aae-a87e-f550e99aec8a","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2663483,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation analysis of samples and differentially expressed genes (DEGs) in response to \u003cem\u003eS. graminicola\u003c/em\u003e infection at different time points. (A) Pearson correlation coefficients among samples. (B) Number of DEGs in foxtail millet genotypes JG21 and rdm12 following \u003cem\u003eS. graminicola\u003c/em\u003e infection. (C) Venn diagram analysis of up-regulated and down-regulated DEGs in foxtail millet in response to 12 h and 24 h of \u003cem\u003eS. graminicola\u003c/em\u003e infection. DEGs were screened using the criteria: adjusted P-value (\u0026lt; 0.05 and absolute log₂(fold change) \u0026gt; 0.00. (D) Differentially expressed genes shared between JG21 and rdm12 at 12 h and 24 h post-\u003cem\u003eS. graminicola\u003c/em\u003e infection.\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/fa814927fbf167c50d0eb784.png"},{"id":91642912,"identity":"6b4ea6b3-495e-4ed6-a262-87c8ee419b27","added_by":"auto","created_at":"2025-09-18 15:14:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":42245,"visible":true,"origin":"","legend":"\u003cp\u003eNine genes containing L-type lictin-domain were significantly differentially expressed in JG21 and rdm12.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/4aef9e537b9d68d358e1dcbc.png"},{"id":91641985,"identity":"751b5161-d640-4be5-90b0-4d8427e71d7f","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":12018864,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG pathway enrichment analysis of differentially expressed genes (DEGs) in JG21 and rdm12.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/483a1a08ec6d941fd94c2994.png"},{"id":91642916,"identity":"802d119b-8115-4bb0-b61f-9a28ba3936bb","added_by":"auto","created_at":"2025-09-18 15:14:03","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1196708,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially expressed genes in the plant-pathogen interaction.\u003c/p\u003e","description":"","filename":"Fig.7.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/49471729a712211ad8160342.png"},{"id":91641991,"identity":"1ec7128b-be41-4f42-afb3-37d9b97217db","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2536127,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the MAPK cascade and heatmap of differentially expressed genes (DEGs). Heatmap showing the expression of DEGs in the MAPK cascade signaling pathway. Red indicates up-regulated gene expression, and blue indicates down-regulated expression (expression levels are represented by log₂Fold Change). DEGs were screened using the criteria of adjusted P-value (padj) \u0026lt; 0.05 and absolute log₂(fold change) \u0026gt; 0.\u003c/p\u003e","description":"","filename":"Fig.8.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/c93f041cdac412b62c0eb418.png"},{"id":91641986,"identity":"6351d221-c0af-4787-9b17-e06119395c59","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2025539,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially expressed genes in the glutathion metabolism and phenylpropanoid bi-osynthesis.\u003c/p\u003e","description":"","filename":"Fig.9.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/95f75867778a24b12dc39900.png"},{"id":91641988,"identity":"9a43c397-1512-486c-b9a2-8035481b4aec","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":837362,"visible":true,"origin":"","legend":"\u003cp\u003eqRT-PCR validation genes expression.\u003c/p\u003e","description":"","filename":"Fig.10.png","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/08cc370ff19d785e9af9b864.png"},{"id":104740464,"identity":"81890599-9072-4681-93b3-a1e15e638ed9","added_by":"auto","created_at":"2026-03-16 16:18:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":27860087,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/253b037a-8160-4a15-9028-a22fbbb555c7.pdf"},{"id":91641976,"identity":"b9daff1e-5e28-44f8-b66c-9bd95ac7fa87","added_by":"auto","created_at":"2025-09-18 15:06:03","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":49357,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.zip","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/33df7bba43e4ab3f29e4343e.zip"},{"id":91642914,"identity":"8ff7c28f-a9ba-4548-b37a-2f5db16b0031","added_by":"auto","created_at":"2025-09-18 15:14:03","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":644107,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2.zip","url":"https://assets-eu.researchsquare.com/files/rs-7495945/v1/de3c8eec5846adf9ca6b8551.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative transcriptome analysis of foxtail millet variety JG21 and resistant mutant unravels the key players associated with downy mildew resistance","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFoxtail millet [\u003cem\u003eSetaria italica\u003c/em\u003e (L.) P. Beauv.] is one of the important coarse cereals in the north China, and it is with the strongest drought resistance and wide adaptability [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, with the change of tillage system, there is a risk of being damaged by various pathogens, which not only inhibits the foxtail millet normal growth, but also affects its yield and quality [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Downy mildew is one of the most important diseases of foxtail millet, which can occur throughout the growth periodand show different symptoms. The pathogen oospores germination began to infect the young buds, resulting in \"bud death or bud rot\". If the infection is mild, the back of the leaves will show \"gray back\" symptoms at the seedling stage. A series of symptoms followed, such as \"white tip\", \"gun\", \"hair\" and \"hedgehog\" etc. The disease can lead to the reduction yield and quality, which brings a great threat to foxtail millet production [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Given the harm caused by downy mildew, the selection and promotion of varieties resistant is an economical and environmentally friendly way to control downy mildew damage [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Jingu 21 is an excellent variety, which is famous for its \"high yield and high quality\" and is widely planted in the main planting areas in Shanxi [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Unfortunately, it has become very susceptible to \u003cem\u003eS. graminicola\u003c/em\u003e, causing serious yield losses to farmers. So far, several methods have been used to control downy mildew, including spray chemical fungicides, select coated seeds, application of various agricultural regulation measures [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, cultivating and utilizing disease-resistant varieties is the best way and environmental sustainable strategy [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGenetic improvement of excellent varieties and breeding of disease-resistant varieties are particularly urgent. Traditional breeding methods can take seven to eight years or more to screen resistant varieties. Thankfully, FAO and the IAEA have obtained more than 3,200 new crop varieties through mutagenesis, about 80% of which were obtained through physical mutagenesis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Mutation breeding is a promising strategy to develop resistant varieties. The resistance mutant WYB-18 obtained by ethyl methylsulfonate (EMS) showed resistance to black spot disease, and provided a theoretical basis for the cultivation of later resistance varieties [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Similarly, embryogenic cell suspension (ECS) were mutagenized by EMS, screened for fusarium wilt resistant mutant in banana, played an important role in fusarium wilt resistance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The roots of Cuibi-1 (CB-1) and mutant KCB-1 were by metabolome and transcriptome studies, some important metabolites in the phenylpropanoid pathway, and and hormone signals pathway, indole-3-acetic acid (IAA) and abscisic acid (ABA) in CB-1 and KCB-1 were involved in the response to \u003cem\u003eR. solanacearum\u003c/em\u003e infection [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFoxtial millet as an important coarse cerea crop, with the improvement of people's quality of life and health awareness in the domestic market demand is also increasing. The disease resistance varieties is the internal factor affecting the occurrence of disease. Therefore, It was devoted to the study of inherent disease resistance of foxtial millet, and applied a relatively common and efficient breeding method-EMS mutagenesis, to obtain the mutant plants. Combined with the field resistance identification, the mutant's phenotype, agronomic traits, quality traits and physiological and biochemical characteristics were compared. At the same time, transcriptome sequencing was used to study the defense mechanism of foxtial millet infected by \u003cem\u003eS. graminicola\u003c/em\u003e, in order to obtain the differential genes and the disease resistance or susceptibility mechanism involved. The aim of this study was to lay a theoretical foundation for disease resistance breeding of foxtial millet and provide some reference for breeding of other coarse cereals.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePlant materials and growth conditions\u003c/h2\u003e\u003cp\u003eA stable, downy mildew-resistant mutant designated as rdm12 was isolated from a mutant library of Jingu 21, a foxtail millet variety. The library was constructed via mutagenesis with 1% ethyl methanesulfonate (EMS). Jingu 21 is a widely cultivated foxtail millet variety in northern China, valued for its superior grain quality and high yield. It was originally collected and is preserved by the Coarse Cereal Molecular Breeding Team of Shanxi Agricultural University. To minimize heterozygosity, the rdm12 mutant was subjected to five consecutive generations of forced self-pollination under greenhouse conditions. All plant materials were grown in experimental fields situated in Taigu District (37\u0026deg;25\u0026prime;13\u0026Prime; N, 112\u0026deg;35\u0026prime;26\u0026Prime; E), Shanxi Province, China.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePathogen inoculation and sample preparation\u003c/h3\u003e\n\u003cp\u003eIn 2021, each foxtail millet material was divided into treatment and control groups, with three biological replicates established for each group. Each plot had an area of 9 m\u0026sup2; (3 m \u0026times; 3 m), with a row spacing of 30 cm, plant spacing of 15 cm, and sowing depth of 3\u0026ndash;5 cm. All plots were maintained under consistent cultivation conditions and subjected to conventional field management, including thinning, watering, and weeding.\u003c/p\u003e\u003cp\u003eZoospores used for inoculation were collected from the abaxial surface of fresh diseased leaves. Inoculation was performed during continuous cloudy weather at the heading stage: 1 mL of sporangium suspension (3\u0026times;10⁵zoospores/mL) was injected into the middle of spikelets. Thirty panicles with uniform growth were selected for inoculation, among which three panicles were harvested for transcriptome sequencing, and the remaining panicles were used for disease incidence.\u003c/p\u003e\u003cp\u003eFor transcriptome analysis, panicles were collected at 12 h and 24 h post-inoculation. Control plants were inoculated with sterile water, with three replicates per sample. All collected panicles were labeled, immediately frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80℃. Fifteen days after inoculation, diseased panicles were surveyed, and resistance levels were classified according to the criteria outlined in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eInvestigation of agronomic traits, yield, and quality\u003c/h3\u003e\n\u003cp\u003eAt maturity, five plants were randomly selected from each genotype, and the following traits were measured from the base of the plants, with mean values calculated: plant height (PH), number of main stem nodes (NNMS), main panicle length (MPL), main panicle diameter (MPD), main stem diameter (MSD), panicle weight per plant (PWP), grain weight per plant (GWP), and 1000-grain weight (TGW). Data were analyzed for significant differences using Excel and SPSS 26.0 software.\u003c/p\u003e\u003cp\u003eMature grains were collected from three individual plants of each genotype, with three independent biological replicates analyzed. Grains were dried, threshed, and their color was measured using a colorimeter (X-rite VS50, Danaher Corporation, Washington, DC, USA). For each genotype, 5 g of grains from three individual panicles were collected separately, ground in liquid nitrogen, and measured using the colorimeter [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eProtein content was determined using the micro-Kjeldahl method with an automatic discrete chemistry analyzer (SmartChem140, AMS-Alliance Co., Paris, France) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Starch content was measured according to the method of the Association of Official Agricultural Chemists (AOAC) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and gel consistency was determined as described by [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Amino acid content was measured following the method of [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eDetermination of antioxidant enzyme activities (SOD, POD, CAT), malondialdehyde (MDA), soluble sugar, and proline (Pro) contents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCrude enzyme extracts were prepared as follows: approximately 0.1 g of fresh panicle tissue was chopped and ground to a powder in liquid nitrogen, transferred to a 2 mL centrifuge tube, mixed with 1 mL of extraction buffer, and centrifuged at 12,000 rpm at 4℃ for 10 min. The supernatant was collected for subsequent assays, with the entire extraction process performed on ice. Activities of SOD, POD, and CAT, as well as contents of MDA, soluble sugar, and proline in young panicles, were determined using commercial kits (Boxbio, Beijing, China) and a UV-visible spectrophotometer (UV-1200, Mapada Instruments, Shanghai, China). Soluble sugar content was additionally verified by anthrone colorimetry [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Proline content was measured according to the method of with minor modifications [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eStatistical analysis was performed using SPSS 16.0 software. Differences between the resistant mutant and susceptible parent were tested by analysis of variance (ANOVA), and significance between genotypes was determined using Fisher\u0026rsquo;s Least Significant Difference (LSD) test at the 0.05 level. All experiments were conducted independently.\u003c/p\u003e\n\u003ch3\u003eRNA extraction, library construction, and sequencing\u003c/h3\u003e\n\u003cp\u003eFor RNA extraction, over 500 mg of panicle tissue was collected from wild-type JG21 and mutant rdm12. For ease of labeling in transcriptome sequencing, JG21 was designated \"S\" (susceptible) and rdm12 as \"R\" (resistant). Total RNA was extracted using a Universal Total RNA Extraction Kit (centrifugal column type, Beijing Newbate Biotechnology Co., Ltd.) following the manufacturer\u0026rsquo;s protocol. Subsequently, 1 \u0026micro;g of total RNA from each sample was used for library construction with the NEBNext Ultra RNA Library Prep Kit (NEB, MA, USA), and sequencing was performed on an Illumina HiSeq 4000 platform (Novogene, China). Raw sequencing data were filtered, screened, and assembled as described by Zhang et al. to generate contigs [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which were then aligned to the foxtail millet genome in GenBank using BLASTx and BLASTn.\u003c/p\u003e\n\u003ch3\u003eSequencing data analysis\u003c/h3\u003e\n\u003cp\u003eRaw reads were processed to remove adapters, poly-N sequences, and low-quality reads, yielding clean reads that were mapped to the reference genome (Setaria italica v2.2; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://phytozome.jgi.doe.gov/pz/portal.html#!info?alias=Org_Sitalica\u003c/span\u003e\u003cspan address=\"https://phytozome.jgi.doe.gov/pz/portal.html#!info?alias=Org_Sitalica\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Gene expression levels were normalized as fragments per kilobase of transcript per million mapped reads (FPKM) for cross-sample comparison [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Differentially expressed genes (DEGs) between \u003cem\u003eS. graminicola\u003c/em\u003e-inoculated and mock-inoculated plants were identified using thresholds of absolute log₂(fold change)\u0026thinsp;\u0026ge;\u0026thinsp;1 and false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.01. DEGs were subjected to Gene Ontology (GO) functional enrichment analysis, with GO terms considered significantly enriched at a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Additionally, clusters of orthologous groups (KOG) and pathway analyses were performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.genome.jp/kegg\u003c/span\u003e\u003cspan address=\"http://www.genome.jp/kegg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] .\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eReal-time quantitative PCR (qRT-PCR) assay\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted using a plant RNA extraction kit (Cowin Biotech, Jiangsu, China), and first-strand cDNA was synthesized using a cDNA Synthesis Kit (Takara, Japan). The foxtail millet Actin gene was used as the internal reference. Primers were designed using Primer Premier 6.0 software, with sequences listed in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e qRT-PCR was performed using the SYBR Green Quantitative RT-qPCR Kit (Takara, Japan) on a CFX96\u0026trade; Real-Time System (Bio-Rad), with three technical replicates per sample.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eComparison of resistance differences between JG21 and mutant rdm12 to\u003c/b\u003e \u003cb\u003eS.graminicola\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe compared the resistance of JG21 and the mutant rdm12 to downy mildew. Specifically, the disease incidence of JG21 and rdm12 following inoculation with \u003cem\u003eS. graminicola\u003c/em\u003e was recorded under field and greenhouse conditions, respectively. JG21 displayed high susceptibility to downy mildew, with disease incidences of 38.25% (field) and 47.33% (greenhouse). In contrast, the mutant rdm12 exhibited strong re-sistance to the disease, with significantly lower incidences of 0.44% (field) and 2.70% (greenhouse) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These results indicate a marked contrast in the resistance and susceptibility of JG21 and rdm12 after infection with \u003cem\u003eS. graminicola\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eCharacterization of agronomic and grain quality traits in JG21 and its mutant rdm12\u003c/h3\u003e\n\u003cp\u003eIn the field, agronomic traits (including plant height, stem diameter, ear length, and ear diameter) were investigated at the heading stage. Additionally, at the heading stage, measurements were taken for plant height, number of internodes, stem diameter, spike length, spike diameter, spike weight, grain weight per spike, and 1000-grain weight. The plant height of JG21 (179.46\u0026thinsp;\u0026plusmn;\u0026thinsp;4.55 cm) was significantly greater than that of rdm12 (134.52\u0026thinsp;\u0026plusmn;\u0026thinsp;4.57 cm), with a difference of 44.94 cm; the mutant also had fewer internodes than JG21. The spike length of rdm12 (29.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73 cm) was longer than that of JG21 (23.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73 cm), while its spike diameter (29.93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87 cm) was smaller than that of JG21 (34.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88 cm). Determination of three yield-related indices revealed that the spike weight, grain weight per spike, and 1000-grain weight of JG21 were slightly higher than those of rdm12 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo compare differences in nutritional quality between JG21 and rdm12, the protein content, fat content, gel consistency, and amylose content of grains were measured (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The protein and fat contents of JG21 were slightly higher than those of rdm12, though the differences were not significant. In contrast, rdm12 exhibited higher gel consistency and amylose content than JG21, with a significant difference in gel consistency between the two (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Amino acid analysis of the two materials showed that among the 17 detected amino acids, glutamic acid had the highest content: 2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 in JG21, which was slightly higher than in rdm12 (2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03). Cysteine had the lowest content, at 0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01. By comparison, the mutant contained relatively higher levels of 9 amino acids than JG21, while 5 amino acids (Glu, His, Ile, Leu, Pro, Thr) were present at lower levels in rdm12; however, none of these differences in amino acid content were significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDifferences in physiology and biochemistry between JG21 and rdm12\u003c/h2\u003e\u003cp\u003eWe compared the activities of protective enzymes and contents of osmoregulatory substances in JG21 and rdm12 after infection by \u003cem\u003eS. graminicola\u003c/em\u003e. For protective enzymes, both JG21 and the mutant rdm12 showed increased superoxide dismutase (SOD) activity post-infection, with rdm12 exhibiting significantly higher SOD activity than JG21 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e); in contrast, peroxidase (POD) activity decreased in both genotypes, and the reduction in JG21 reached a significant level compared with its corresponding uninfected control. Regarding catalase (CAT), rdm12 maintained significantly higher activity than JG21 both before and after inoculation JG21 showed a significant decrease in CAT activity after inoculation, while rdm12 exhibited an increase. We also determined the contents of malondialdehyde (MDA), soluble sugars, and proline (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e): uninfected rdm12 had a significantly higher MDA content than uninfected JG21, and after inoculation, MDA content in JG21 increased significantly compared with its control, whereas no significant difference was observed between infected rdm12 and its control. For osmoregulatory substances, JG21 and the mutant showed the same trend in soluble sugar and proline contents after inoculation: both exhibited a decrease in soluble sugar content relative to their respective controls, with JG21 showing a significant reduction, while rdm12 maintained significantly higher soluble sugar and proline contents than JG21 regardless of inoculation status.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSequencing, data processing and differentially expressed genes(DEGs)\u003c/h2\u003e\u003cp\u003eSequencing yielded a total of 170.47 Gb of clean data, with each sample generating at least 5.99 GB. Across all 24 samples, the Q30 base percentage exceeded 93%, and the GC content (percentage of guanine and cytosine bases relative to total bases) was over 52% (Table S3). Alignment with the foxtail millet reference genome showed that the total read mapping rate for each sample exceeded 95%, indicating high coverage and good quality of the sequencing data, which was suitable for further analysis. The correlation coefficients between different samples are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eUsing an adjusted P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the threshold for screening DEGs, we identified the following expression changes in response to \u003cem\u003eS. graminicola\u003c/em\u003e infection at 12 and 24 hours, compared to their respective controls: 2816 (12 h resistant, 12 R), 1139 (24 h resistant, 24 R), 961 (12 h susceptible, 12 S), and 924 (24 h susceptible, 24 S) up-regulated genes, as well as 531 (12 R), 626 (12 S), 49 (24 R), and 25 (24 S) down-regulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eA total of 68 genes were differentially expressed between the resistant and susceptible genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). After excluding 27 genes without functional zwsannotations, heatmap analysis was performed on the remaining 41 genes(Table S4). Among these, 87.7% (36 genes) were significantly induced and up-regulated at 12 h post-infection, with no significant expression changes observed at 24 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Notably, the expression patterns of these genes in the susceptible genotype were the reverse of those in the resistant genotype, suggesting that these genes may play a regulatory role in downy mildew resistance in the resistant variety.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eGO functional enrichment and expression level analysis of DEGs\u003c/h2\u003e\u003cp\u003eUsing a screening threshold of p-value\u0026thinsp;\u0026le;\u0026thinsp;0.01, GO enrichment analysis was performed on the differentially expressed genes (DEGs) of JG21 and its disease-resistant mutant rdm12 at 12 h and 24 h post-inoculation. The enrichment results showed that, in terms of GO terms, the DEGs were primarily associated with biological processes including cell surface receptor signaling pathway, defense response to bacteria, protein phosphorylation, glutathione metabolic process, cell wall macromolecule catabolic process, chitin catabolic process, hydrogen peroxide catabolic process, response to oxidative stress (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). For molecular function, the DEGs were mainly linked to glutathione transferase activity, chitinase activity, calcium ion binding, chitin binding, UDP-glycosyltransferase activity, and peroxidase activity.\u003c/p\u003e\u003cp\u003eNotably, the GO term \"defense response to oomycetes\" was specific to rdm12: 13 DEGs were enriched at 12 h post-inoculation, 9 at 24 h, with 9 DEGs shared between the two time points. All 9 shared genes contain an L-type lectin domain, among which five are receptor kinases with L-type lectin domains; these genes were significantly up-regulated in rdm12 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Notably, the GO term \"defense response to oomycetes\" was specific to rdm12: 13 DEGs were enriched at 12 h post-inoculation, 9 at 24 h, and 9 DEGs were shared between the two time points. All 9 shared genes contain an L-type lectin domain, among which five are receptor kinases with L-type lectin domains; these genes were significantly up-regulated in rdm12 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eKEGG pathway enrichment analysis of DEGs\u003c/h2\u003e\u003cp\u003eTo identify metabolic pathways involved in the response to \u003cem\u003eS. graminicola\u003c/em\u003e infection, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on differentially expressed genes (DEGs). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, our focus was on significantly enriched metabolic pathways in JG21 and its disease-resistant mutant rdm12 at two post-infection time points (12 h and 24 h). The DEGs were significantly enriched in pathways including diterpenoid biosynthesis, phenylpropanoid biosynthesis, MAPK signaling pathway, plant - pathogen interaction, starch and sucrose metabolism, carotenoid biosynthesis, flavone and flavonol biosynthesis, glutathione metabolism, photosynthesis-antenna proteins, zeatin biosynthesis, and alpha-linolenic acid metabolism indicating that these pathways are strongly induced by \u003cem\u003eS. graminicola\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNotably, in the susceptible genotype JG21, both diterpenoid biosynthesis and plant\u0026ndash;pathogen interaction pathways were significantly enriched at 12 h and 24 h post-infection; in rdm12, however, only the plant-pathogen interaction pathway was consistently enriched at both time points. Among these pathways, the plant-pathogen interaction pathway contained the largest number of DEGs (38 genes). Additionally, 31 DEGs were enriched in the MAPK signaling pathway and 10 in diterpenoid biosynthesis, further highlighting their involvement in the host\u0026ndash;pathogen interaction. These results suggest that \u003cem\u003eS. graminicola\u003c/em\u003e infection activates these pathways to mediate defense responses. We further analyzed the genes within these key pathways.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAltered expression of plant-pathogen interaction-related genes in the mutant rdm12\u003c/h2\u003e\u003cp\u003eCompared with JG21, in rdm12 at 12 h post-inoculation, the expression of two CDPK genes (\u003cem\u003eSeita.3G128600\u003c/em\u003e and \u003cem\u003eSeita.9G043400\u003c/em\u003e) was significantly induced by \u003cem\u003eS. graminicola\u003c/em\u003e, with their expression levels being significantly higher than those in JG21. Reactive oxygen species (ROS) act as crucial signaling molecules in plant disease resistance, and Rboh is a key enzyme involved in ROS production. The expression patterns of two Rboh genes in JG21 and rdm12 were opposite: Rboh expression in rdm12 was up-regulated at 12 h but inhibited at 24 h, whereas in JG21, it was inhibited at 12 h followed by significant induction and up-regulation at 24 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The calmodulin/calmodulin-like (CaM/CML) signaling system plays an important role in plant disease resistance. In rdm12, 8 CaM/CML genes were up-regulated, with expression patterns opposite to those in JG21. As a plant receptor kinase, BAK1 (BRI1-associated kinase 1) perceives extracellular signals to regulate immune responses and disease resistance; in this study, the expression of 6 BAK1-like receptor kinases was significantly up-regulated upon infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Numerous studies have confirmed that the primary biological function of the plant WRKY gene family is to regulate resistance responses and establish signal transduction pathways. Here, 18 WRKY genes were significantly up-regulated in response to pathogen attack. Additionally, the pathogenesis-related protein gene PR1, mitogen-activated protein kinase \u003cem\u003eSeita.9G444100\u003c/em\u003e (mitogen-activated protein kinase/extracellular signal-regulated kinase 3), and \u003cem\u003eSeita.5G175100\u003c/em\u003e (MEKK3, mitogen-activated protein kinase kinase kinase 3) were significantly up-regulated at 12 h post-\u003cem\u003eS. graminicola\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAltered expression of MAPK signaling pathway-related genes in the mutant rdm12\u003c/h2\u003e\u003cp\u003eThe MAPK cascade plays a critical role in PAMP-triggered immunity (PTI), primarily transmitting signals from pattern recognition receptors (PRRs) to downstream transcription factors. We analyzed differentially expressed genes (DEGs) involved in the MAPK signaling pathway and found that in rdm12, several key genes were significantly induced and up-regulated following \u003cem\u003eS. graminicola\u003c/em\u003e infection (with the exception of \u003cem\u003eSeita.5g095400\u003c/em\u003e)(Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These included seven transcription factor genes (four WRKYs, two ERFs, and one other transcription factor), five pathogenesis-related (\u003cem\u003ePR\u003c/em\u003e) genes (\u003cem\u003eSeita.2g024600\u003c/em\u003e, \u003cem\u003eSeita.2g024800\u003c/em\u003e, \u003cem\u003eSeita.2g024900\u003c/em\u003e, \u003cem\u003eSeita.9g0435200\u003c/em\u003e, and \u003cem\u003eSeita.5g0175100\u003c/em\u003e), three calmodulin-like (CML) protein genes (homologous to those in Chinese cabbage), and three rust resistance \u003cem\u003eLr10\u003c/em\u003e genes. Additionally, several receptor protein kinases were activated in rdm12, such as GsSRK homologs (\u003cem\u003eSeita.5g016900\u003c/em\u003e, \u003cem\u003eSeita.7g095600\u003c/em\u003e, and \u003cem\u003eSeita.7g045600\u003c/em\u003e), mitogen-activated protein kinase kinase kinases (MPKKKs), two leucine-rich repeat receptor-like kinases (LRR-RLKs), wall-associated kinase 10 (WAK10; \u003cem\u003eSeita.8g152000\u003c/em\u003e), and serine/threonine kinase (STK; \u003cem\u003eSeita.8G151600\u003c/em\u003e) all of which were up-regulated(Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eAltered expression of glutathione metabolism and phenylpropanoid biosynthesis pathways in rdm12\u003c/h2\u003e\u003cp\u003eBoth the glutathione metabolism and phenylpropanoid biosynthesis pathways were enriched following \u003cem\u003eS. graminicola\u003c/em\u003e infection. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, among the 12 genes involved in glutathione metabolism, glutathione S-transferase (GST) genes were induced and up-regulated at 12 h post-infection but exhibited decreased expression at 24 h in rdm12, whereas their expression patterns were opposite in JG21. Expression of deglutathionylation (DGS) genes remained inhibited and down-regulated throughout, with the exception of \u003cem\u003eSeita.3g0387000\u003c/em\u003e. These results suggest that glutathione S-transferase may promote glutathione synthesis to counteract infection during the early stage. In rdm12, the expression patterns of differentially expressed genes in the phenylpropanoid pathway were opposite to those in JG21 at both infection stages. Compared to JG21, rdm12 showed inhibited and down-regulated expression of 5 cytochrome P450 genes, 3 momilactone A synthase genes, 2 ent-kaurene oxidase 2 genes, 1 terpene synthase (TPS13) gene, and 1 ent-copalyl diphosphate synthase 1 gene at 12 h post-infection, followed by significant up-regulation at 24 h.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eValidation of transcriptomic data by RT-qPCR\u003c/h2\u003e\u003cp\u003eTo validate the differentially expressed genes (DEGs) identified from RNA-Seq data, 20 DEGs were selected for quantitative real-time PCR (qRT-PCR) analysis. These genes were potentially involved in defense responses against \u003cem\u003eS. graminicola\u003c/em\u003e and exhibited distinct expression patterns between the resistant (rdm12) and susceptible (JG21) genotypes. The relative expression levels of all tested genes were normalized using the constitutively expressed Actin gene as an internal reference.The expression profiles of these genes determined by qRT-PCR were consistent with the results from RNA-Seq analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e), confirming the reliability of the transcriptomic data.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDowny mildew is a highly destructive disease that severely impacts foxtail millet production, leading to poor grain development and substantial yield losses. To date, although some studies have initiated the identification of resistance genes or loci, progress in this area remains limited [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In the present study, we used the elite foxtail millet variety JG21 and its downy mildew-resistant mutant rdm12 generated via ethyl methanesulfonate (EMS) mutagenesis which exhibits developmental abnormalities, most notably stunted growth and shortened internodes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Integrating phenotypic, physiological, and biochemical analyses with transcriptome sequencing, we explored the potential disease resistance regulatory mechanisms associated with the rdm12 mutant phenotype. Genome-wide transcriptomic profiling of rdm12 and wild-type JG21 identified a number of differentially expressed genes (DEGs), which were enriched in pathways such as plant-pathogen interaction, MAPK signaling, phenylpropanoid biosynthesis, and glutathione metabolism. These findings help to clarify the transcriptional regulatory basis underlying the rdm12 mutant phenotype.\u003c/p\u003e\u003cp\u003ePlant growth and defense processes are regulated by numerous antagonistic molecular pathways, giving rise to the so-called \"growth-defense trade-off\": plants transiently suppress growth in response to pest or pathogen attacks. Due to this inherent antagonism, genetic variations enhancing disease tolerance typically reduce growth, while those promoting growth often compromise disease resistance [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Derbyshire et al. (2024) reported an inverse correlation between yield and disease resistance, noting that highly resistant genotypes tend to have lower yields, whereas susceptible genotypes often exhibit higher yields [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Notably, this unfavorable association is disrupted in the rdm12 mutant, suggesting the potential for combining favorable agronomic traits with disease resistance similar to the results of gene-editing techniques that have generated wheat and rice lines with both disease resistance and high-yield potential [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Thus, Thus, the use of mutants plays a certain role in promoting the genetic improvement of foxtail millet\u003c/p\u003e\u003cp\u003eWhen plants detect pathogens, oxidative stress occurs, leading to the overproduction of reactive oxygen species (ROS). Pathogen-induced ROS act as signaling molecules that actively trigger downstream signaling cascades, thereby activating host basal resistance [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, cellular ROS levels must be dynamically balanced to avoid excessive oxidative stress. Concurrently with the upregulation of defense-related genes, intrinsic antioxidant pathways are activated to counteract this stress. Increases in enzymes such as polyphenol oxidase (PPO), superoxide dismutase (SOD), and catalase (CAT) are critical for scavenging harmful free radicals and maintaining cellular redox homeostasis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this study, compared with the susceptible genotype JG21, the resistant mutant rdm12 showed significantly higher SOD and CAT activities, indicating that rdm12 can rapidly degrade free radicals generated during pathogen invasion [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. For susceptible varieties, even with host-produced antioxidants, maintaining optimal ROS levels remains challenging: reduced ROS-scavenging capacity leads to marked ROS accumulation, inducing disease susceptibility [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This can damage host DNA and membranes, ultimately resulting in plant death. Similarly, resistant mutants accumulated higher levels of soluble sugars and malondialdehyde (MDA) than susceptible JG21. Soluble sugars have been positively associated with resistance to Bois Noir Phytoplasma in \u003cem\u003eVitis vinifera\u003c/em\u003e cv. Sangiovese [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and to fusarium wilt in pigeon pea (\u003cem\u003eCajanus cajan\u003c/em\u003e) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLectin receptor-like kinases (LecRLKs) form a distinct subfamily of receptor-like kinases, classified into three types (L, G, and C) based on domain differences [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In plants, LecRLKs act as key sentinels of immunity, playing indispensable roles in defense against diverse microorganisms [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Previous studies have shown that \u003cem\u003eArabidopsis\u003c/em\u003e LecRKs effectively resist \u003cem\u003ePhytophthora\u003c/em\u003e infections [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], while LecRKs in \u003cem\u003eNicotiana benthamiana\u003c/em\u003e and tomato exhibit strong resistance to \u003cem\u003ePhytophthora\u003c/em\u003e [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Recent research has further revealed that L-type LecRKs regulate soybean resistance to \u003cem\u003ePhytophthora sojae\u003c/em\u003e [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], and a novel lectin receptor kinase gene, AtG-LecRK-I, enhances \u003cem\u003eArabidopsis\u003c/em\u003e resistance to bacterial pathogens by modulating stomatal immunity [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In the present study, GO enrichment analysis identified \"defense response to oomycetes\" as a unique term in rdm12, with 9 LecRKs significantly upregulated in the mutant (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This suggests that LecRKs are strongly induced in foxtail millet upon \u003cem\u003eS. graminicola\u003c/em\u003e infection and likely contribute to downy mildew resistance.\u003c/p\u003e\u003cp\u003eDuring the long-term co-evolutionary interplay between plants and pathogens, a suite of key genes collaborates to form a precise and intricate defense network. In this study, genes such as \u003cem\u003eCDPK\u003c/em\u003e, \u003cem\u003eRboh\u003c/em\u003e, \u003cem\u003eCaM/CML\u003c/em\u003e, \u003cem\u003eBAK1\u003c/em\u003e, \u003cem\u003eMEKK3\u003c/em\u003e, \u003cem\u003eWRKY\u003c/em\u003e, and \u003cem\u003ePR1\u003c/em\u003e played pivotal regulatory roles in the interaction between foxtail millet and downy mildew pathogens(Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Comprehensive analysis of their regulatory relationships is crucial for deciphering plant immune mechanisms and provides novel insights for foxtail millet disease control and resistance breeding [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Firstly, \u003cem\u003eBAK1\u003c/em\u003e can be considered the \"pioneer\" of plant immunity initiation. When pathogens invade, their pathogen-associated molecular patterns (PAMPs) are specifically recognized by pattern recognition receptors (PRRs) on the plant cell membrane. At this point, \u003cem\u003eBAK1\u003c/em\u003e acts as a co-receptor, rapidly associating with PRRs to form complexes and initiate immune signal transduction cascades [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This recognition is highly specific and sensitive; once triggered, it rapidly activates downstream defenses, serving as the first critical checkpoint for plants to resist pathogen invasion. For example, when \u003cem\u003eArabidopsis thaliana\u003c/em\u003e encounters \u003cem\u003ePseudomonas syringae\u003c/em\u003e, \u003cem\u003eBAK1\u003c/em\u003e and \u003cem\u003eFLS2\u003c/em\u003e collaborate to activate early immune signals within a short timeframe, facilitating subsequent defense responses [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Secondly, pathogen invasion induces rapid changes in cellular calcium ion concentrations. CaM/CML proteins act as \"sensors\" that detect this signal; upon binding calcium ions, they undergo conformational changes to activate \u003cem\u003eCDPK\u003c/em\u003e [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. As a key signaling kinase, \u003cem\u003eCDPK\u003c/em\u003e targets multiple substrates, with its regulation of Rboh being particularly significant. Activated \u003cem\u003eCDPK\u003c/em\u003e phosphorylates \u003cem\u003eRboh\u003c/em\u003e, significantly enhancing its NADPH oxidase activity and promoting massive ROS production [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. ROS not only directly eliminate pathogens but also act as signaling molecules to activate downstream defense-related genes, triggering broader immune responses such as the \u003cem\u003eMAPK\u003c/em\u003e cascade [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In the \u003cem\u003eMAPK\u003c/em\u003e cascade, \u003cem\u003eMEKK3\u003c/em\u003e serves as a pivotal link between upstream and downstream components. Upstream signals (e.g., ROS) trigger \u003cem\u003eMEKK3\u003c/em\u003e activation, which then sequentially phosphorylates and activates downstream \u003cem\u003eMAPKK\u003c/em\u003e and \u003cem\u003eMAPK\u003c/em\u003e [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Activated \u003cem\u003eMAPK\u003c/em\u003e translocates to the nucleus, where it phosphorylates and activates \u003cem\u003eWRKY\u003c/em\u003e transcription factors [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].The \u003cem\u003eWRKY\u003c/em\u003e family comprises numerous members that recognize and bind to W-box elements in target gene promoters, thereby regulating their expression. In plant-pathogen interactions, \u003cem\u003eWRKYs\u003c/em\u003e can activate multiple defense genes, including \u003cem\u003ePR1\u003c/em\u003e [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. \u003cem\u003ePR1\u003c/em\u003e, often regarded as a \"terminal weapon\" in plant defense, is highly expressed under \u003cem\u003eWRKY\u003c/em\u003e regulation [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The PR1 protein exhibits diverse antimicrobial properties, directly inhibiting pathogen growth, reproduction, and spread, and acts as a key effector of the plant defense response [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. High \u003cem\u003ePR1\u003c/em\u003e expression typically indicates successful initiation of the plant immune response and active resistance to pathogen invasion. In summary, these genes form a tightly integrated, interdependent regulatory network during plant-pathogen interactions, with each component being essential and mutually influential [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGlutathione (GSH) is a key plant antioxidant that plays a critical role in resistance to pathogen infections [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. It participates in defense responses against various biotic stresses, including fungi, nematodes, viruses, and bacteria [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Overexpression of \u003cem\u003ePdbGSTU10\u003c/em\u003e increases salicylic acid (SA) content and induces SA signaling-related genes, suggesting that \u003cem\u003ePdbGSTU10\u003c/em\u003e enhances poplar resistance to \u003cem\u003eAlternaria\u003c/em\u003e by scavenging ROS and modulating the SA pathway [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Glutathione also influences plant resistance to nematodes by precisely regulating the balance between cellular redox status and defense compound production [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Zhu et al. (2021) found that GSH regulates plant immune responses against viruses via SA and ROS signaling pathways [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In this study, 10 differentially expressed glutathione S-transferase genes between wild-type JG21 and rdm12 were identified, suggesting their involvement in host defense against \u003cem\u003eS. graminicola\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe phenylpropanoid metabolic pathway has several important biological functions: (1) participating in plant disease resistance and immunity; (2) contributing to cell lignification; and (3) involved in cytochrome synthesis, among others [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. On one hand, lignin synthesized via this pathway promotes cell wall lignification and thickening, forming a physical barrier that prevents pathogen invasion [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. On the other hand, metabolites such as phenols and isoflavones can be further synthesized into phytoalexins, inhibiting pathogen growth [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Additionally, this pathway is involved in SA synthesis, a key plant defense hormone that activates immune signaling pathways to comprehensively regulate disease resistance [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Our results showed that cytochrome P450, momilactone A synthases, ent-kaurene oxidase 2, terpene synthase TPS13, and ent-copalyl diphosphate synthase are differentially expressed in this pathway and participate in defense against \u003cem\u003eS. graminicola\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eIt is worth noting that in the analysis of transcriptome data, we found that among the co-differentially expressed genes in JG21 and rdm12 at 12 and 24 hours after infection by \u003cem\u003eS. graminicola\u003c/em\u003e, 3 genes (\u003cem\u003eSeita.3G139400\u003c/em\u003e, WRKY transcription factor 53; \u003cem\u003eSeita.3G175100\u003c/em\u003e, pathogenesis-related protein PRMS; \u003cem\u003eSeita.7G095600\u003c/em\u003e, G-type lectin S-receptor-like serine/threonine protein kinase) overlapped with 3 genes in the plant-pathogen interaction pathway of the KEGG metabolic pathway, and they showed significant differential expression. We speculate that these three differentially expressed genes may play important roles in regulating the resistance process against downy mildew, and subsequent studies will conduct more in-depth research focusing on these 3 genes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, comparative analysis of the foxtail millet variety JG21 and its EMS-mutagenized downy mildew-resistant mutant rdm12 revealed that rdm12 showed no significant differences in agronomic or quality traits compared to JG21, yet exhibited significantly enhanced resistance to the downy mildew pathogen \u003cem\u003eS. graminicola\u003c/em\u003e. This resistance was associated with elevated activities of defense-related enzymes and increased accumulation of osmoregulatory substances. Transcriptome analysis identified differentially expressed genes predominantly enriched in pathways including plant-pathogen interaction, MAPK signaling, phenylpropanoid biosynthesis, and glutathione metabolism. Key genes implicated in the resistance mechanism include WRKY transcription factor 53 (\u003cem\u003eSeita.3G139400\u003c/em\u003e), pathogenesis-related protein PRMS (\u003cem\u003eSeita.3G175100\u003c/em\u003e), and G-type lectin S-receptor-like serine/threonine-protein kinase (\u003cem\u003eSeita.7G095600\u003c/em\u003e). These findings provide valuable insights into the molecular mechanisms governing downy mildew resistance in foxtail millet. In subsequent studies, we will conduct in-depth dissection of gene functions and further decipher the molecular basis of disease resistance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Yang Yang for discussion of the project and suggestions for the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Y.H., Y.H.(Yuanhuai Han), and S.H.; data curation, A.W. and Y.Z.; formal analysis, H.X., X.L., and W.Z.; investigation, Z.C. and X.G.; methodology, Y.H.; project administration, Y.H.; resources, L.S., Y.F., and H.H.; software, Y.Z.; supervision, Y.H.; validation, M.J., H.W., and H.W.; visualization, Z.C. X.G., and Z, Z.; writing original draft preparation, Y.H.; writing review and editing, H.W.,and Y.H.. All authors have read and agreed to the published version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by grants from the Science and Technology Innovation Enhancement Project of Shanxi Agricultural University (CXGC2025088) ，the Shanxi Houji Laboratory Self-initiated Research Projects (202404010930003-J05)，and Jin Cainong (2025) No. 19 24 Make breakthroughs in key and core agricultural technologies (TK244702085, NYGG19-01-01), and the College Students Innovation Training Program of Shanxi Agricultural University (S202410113010, S202410113007, S202510113005), and the Agricultural Civilization Insect Design Scheme and Teaching Specimen Production Project (20231916330).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequencing data generated in this study are available in SRA (https://www.ncbi.nlm.nih.gov/sra/PRJNA1299158) of NCBI with the accession numbers PRJNA1276485.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSachdev N, Goomer S, Singh LR. 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Plant J. 2025;121:e17226.\u003c/span\u003e\u003c/li\u003e\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":"Foxtail millet, Downy mildew, Sclerospora graminicola, Transcriptome, Differentially expressed genes, Resistance mechanism","lastPublishedDoi":"10.21203/rs.3.rs-7495945/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7495945/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eFoxtail millet downy mildew, incited by the obligate parasite \u003cem\u003eSclerospora graminicola\u003c/em\u003e, represents a highly devastating disease for foxtail millet. The infection of \u003cem\u003eSclerospora graminicola\u003c/em\u003e frequently causes harm to budlets, leaves, and spikes of foxtail millet, thereby substantially influencing its quality and yield. Nevertheless, disease - resistant varieties can effectively reduce the vulnerability to pathogen attacks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e In this study, we explored Jingu21 (JG21) and the resistant mutant rdm12, which was generated by ethyl methanesulfonate (EMS) mutagenesis. Phenotypic observations revealed that, in comparison with JG21, rdm12 did not display significant disparities in agronomic and quality characteristics. Significantly, rdm12 manifested disease resistance, accompanied by augmented activities of defense enzymes and elevated levels of osmoregulatory substances. Transcriptome analysis of rdm12 mutants and wild-type plants disclosed that the differentially expressed genes were predominantly enriched in pathways such as plant-pathogen interaction, MAPK signaling, phenylpropanoid biosynthesis, and glutathione metabolism signaling. The differential expression of several critical receptor protein kinase genes, WRKY transcription factors, pathogenesis - related (PR) proteins, calmodulin, glutathione S - transferase, and others endows the mutants with enhanced resistance to downy mildew. In particular, WRKY transcription factor 53 encoded by \u003cem\u003eSeita.3G139400\u003c/em\u003e, pathogenesis-related protein PRMS encoded by \u003cem\u003eSeita.3G175100\u003c/em\u003eand G-type lectin S-receptor-like serine/threonine protein kinase coded by \u003cem\u003eSeita.7G095600\u003c/em\u003e, which have played an essential resistant role during the infection by \u003cem\u003eS. graminicola\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eThrough this research, we identified the key genes, important products engaged in the resistance process, and their corresponding metabolic pathways, thus unravelling the resistance mechanism of foxtail millet against \u003cem\u003eS. graminicola\u003c/em\u003e infection. These findings lay a theoretical groundwork for resistance screening in foxtail millet and the development of new varieties.\u003c/p\u003e","manuscriptTitle":"Comparative transcriptome analysis of foxtail millet variety JG21 and resistant mutant unravels the key players associated with downy mildew resistance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-18 15:05:58","doi":"10.21203/rs.3.rs-7495945/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-20T10:35:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-19T09:30:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-19T06:11:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238024917326474300298514045884645585541","date":"2025-11-09T10:43:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105207362571109357179508067746036296447","date":"2025-11-05T13:00:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-11T10:41:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-11T10:34:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-11T10:12:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-11T02:01:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-09-11T01:57:23+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":"b4a255a3-e854-4d5a-8c02-b953b1313566","owner":[],"postedDate":"September 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:14:03+00:00","versionOfRecord":{"articleIdentity":"rs-7495945","link":"https://doi.org/10.1186/s12870-026-08520-y","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2026-03-13 16:00:34","publishedOnDateReadable":"March 13th, 2026"},"versionCreatedAt":"2025-09-18 15:05:58","video":"","vorDoi":"10.1186/s12870-026-08520-y","vorDoiUrl":"https://doi.org/10.1186/s12870-026-08520-y","workflowStages":[]},"version":"v1","identity":"rs-7495945","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7495945","identity":"rs-7495945","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}