Identification and characterization of the powdery mildew resistance in a spelt accession Lsy-93

Abstract

Background

Powdery mildew, a widespread fungal disease caused by Blumeria graminis f. sp. tritici (Bgt), seriously threatens the yield and quality of wheat. The most effective and sustainable approach to control this disease is utilizing resistance genes and unraveling their underlying molecular mechanisms. Spelt (Triticum aestivum ssp. Spelta, 2n = 6x = 42, AABBDD), an ancient hexaploid wheat subspecies, has emerged as a valuable genetic resource for enhancing powdery mildew resistance in modern wheat breeding programs.

Results

Spelt accession lsy-93 demonstrated resistance against powdery mildew at the whole-growth stage. Genetic analysis revealed that the seedling resistance is conferred by a single dominant gene, tentatively designated as PmLsy-93. Bulked segregant RNA sequencing (BSR-seq) and molecular markers positioned PmLsy-93 within a 1.5 cM (genetic) and 10.34 Mb (physical) interval on chromosome 2BL. Six genes were directly associated with disease resistance in this interval and hence were considered as the candidate genes for PmLsy-93. Furthermore, a total of 3,140 differentially expressed genes (DEGs) were identified between the two bulks, with 2,214 down-regulated and 916 up-regulated ones relative to the susceptible bulk. The integration of gene ontology and kyoto encyclopedia of genes and genomes pathway analysis underscores the multifaceted roles of these DEGs in plant defense, stress response, and metabolic regulation. Then, expression pattern of six genes, encoding disease resistance protein, serine threonine-protein kinase, or protein kinase domain, were profiled with Bgt invasion, and analyzed their potential roles in immune pathway. Three closely linked or co-segregated markers were confirmed to be available for marker-assisted selection of PmLsy-93 in breeding programs.

Conclusions

This study successfully pinpointed critical genetic loci and candidate genes associated with powdery mildew resistance in the spelt wheat accession Lsy-93. The results provide valuable insights into plant-pathogen defense mechanisms and lay an foundation for subsequent molecular breeding efforts to enhance crop disease resistance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-025-07040-5.

Introduction

Common wheat (Triticum aestivum L.) is the world’s second most widely cultivated crop, serves as a staple food for 35% of the global population and contributes 20% of the calories and protein [1]. However, diseases such as powdery mildew, wheat rust, and fusarium head blight threaten wheat yield and quality. Wheat powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a globally devastating disease prevalent in major wheat-growing countries, severely reducing wheat yield and quality [2]. Host resistance remains the most effective strategy to reduce yield losses caused by this disease. However, variations in toxicity of the pathogen populations often render existing resistance (R) genes ineffective [3]. Therefore, identification and exploitation of resistance genes represent the cornerstone of developing crop varieties with durable resistance [4].

Up to now, over 100 powdery mildew resistance (Pm) genes/alleles (Pm1 - Pm71) have been identified from wheat and its wild relatives. Although many of them have been cloned, clear and in-depth mechanisms remains limited due to the complex mechanism in plant immunity [5]. The majority of the cloned Pm genes encode nucleotide-binding site leucine-rich repeat (NBS-LRR) proteins, with a smaller number coding for kinases and other protein types [6]. Among them, Pm1, Pm2, Pm3, Pm8, Pm17, Pm5, Pm12, Pm21, Pm41, Pm60 and Pm69 have been experimentally verified to encode NBS-LRR proteins, while Pm24 (WTK3) and WTK4 encode tandem kinase proteins [7]. Other rare protein structures were also reported, such as Pm4 encoding a chimeric protein of a serine/threonine kinase and multiple C2 domains and transmembrane regions, Pm38/Yr18/Lr34/Sr57 encoding a putative ATP-binding cassette transporter and Pm46/Yr46/Lr67/Sr55 encoding hexose transporter [8–10].

Common wheat, as a polyploid species, contains three analogous genomes (97% identical among homoeologous genes). This characteristic severely hampers the gene cloning and mining of the resistance genes [11]. To deal with this issue, bulked segregant RNA sequencing (BSR-Seq) was developed and proven to be an effective method to rapidly identify the target genes underlying elite traits [12]. As a verification, BSR-Seq have been widely used to identify candidate resistance genes against diseases and study overall transcriptome profiles. For example, the Pm gene PmSGD was predicted to reside in the 240–250 Mb interval of chromosome 7B Based on the distribution characteristics of putative single nucleotide polymorphism (SNP) across 21 wheat chromosomes via BSR-Seq [13]; 3,653 differentially expressed genes (DEGs) between the resistant and susceptible bulks were identified throughout the entire genome range via Gene Ontology (GO) analysis of BSR-Seq [14]; six disease-related genes as critical candidates were captured to unravel the molecular mechanisms of resistance by GO, clusters of orthologous group (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis [15]. These reports verified the effectiveness of BSR-Seq on rapid gene identification of analysis of their regulatory and/or candidate genes.

Spelt (T. aestivum ssp. Spelta, 2n = 6x = 42, AABBDD), a hexaploid wheat (2n = 6x = 42, AABBDD) widely cultivated in Europe until the early 20th century, remains a critical genetic reservoir for enhancing key traits in modern wheat cultivars [16]. Many disease resistance genes have been identified in Spelt, such as Pm1d, MlHubel, Yr5, Yr10, Lr65 and Lr71 [17]. In this study, a Spelt accession Lsy-93 demonstrated resistance against powdery mildew at the whole-growth stage. To identify the seeding resistance to powdery mildew and preliminary analyze potential resistance mechanism, our study aimed to (i) assess the resistance to powdery mildew; (ii) map the target Pm gene and explore its key candidate gene(s); (iii) analyze the potential regulatory genes use BSR-Seq combined with expression pattern analysis.

Results

Evaluation and genetic inheritance of powdery mildew resistance in Lsy-93

Upon inoculation with the Bgt isolate E09, Lsy-93 did not produce any visible symptoms, scoring an infection type (IT) 0, while Tainong 18 (TN18) exhibited abundant sporulation, and hence scoring an IT 4 (Fig. 1a and b). Additional five Bgt isolates F07, F09, F10, F23, F28 were further employed to assess the seedling resistance of Lsy-93. The results showed that Lsy-93 exhibited resistance to F07, F09 and F23, while was susceptible to F10 and F28. Ten F₁ plants of Lsy-93 × TN18 showed similar symptoms as Lsy-93, suggesting dominant inheritance pattern for the seedling resistance to the Bgt isolate E09. Among 253 inoculated F₂ plants, 188 ones were resistant and 65 ones were susceptible, fitting a ratio of 3:1 for Mendel monogenic segregation (χ² = 0.06, P = 0.79). To confirm the genotype of the resistant F₂ plants and also re-validate the phenotype of the F₂ plants, the 253 F₂ plants were transplanted in the field after scoring to produce the corresponding F_2:3 families. The harvested F_2:3 families segregated with 61 (homozygous resistant) : 124 (segregating) : and 65 (homozygous susceptible), also fitting a ratio of 1:2:1 for monogenic inheritance (χ² = 0.14, P = 0.93) (Fig. 1a; Table 1). In conclusion, the resistance to Bgt isolate E09 was conferred by single dominant resistance gene, tentatively designated PmLsy-93.

Fig. 1.

a Responses of resistant parent Lsy-93, susceptible parent Tainong 18 (TN18), and part of F_2:3 plants at 14 days post inoculation (dpi) with Blumeria graminis f. sp. tritici (Bgt) isolate E09; b Infection process of Bgt isolate E09 on leaves of Lsy-93 and TN18. Wheat leaf samples were taken at different times post inoculation (hpi) for Coomassie blue staining. Scale bar, 100 μm

Table 1.

Genetic analysis of resistance to the Blumeria Graminis f. Sp. tritici (Bgt) isolate E09 based on the cross of Lsy-93 × Tainong 18

Parent and Cross	Generation	Observed ratio	Expected ratio	χ2	P
Lsy-93	RP	R : S = 10 : 0
Tainong 18	SP	R : S = 0 : 10
Lsy-93 × Tainong 18 F1	F1	R : S = 10 : 0
Lsy-93 × Tainong 18 F2	F2	R : S = 188 : 65	3 : 1	0.06	0.79
Lsy-93 × Tainong 18 F2:3	F2:3	HR : Seg : HS = 61 : 124 : 65	1 : 2 : 1	0.14	0.93

R_P Resistant parent, S_P Susceptible parent, HR Homozygous resistant, Seg Segregating, HS Homozygous susceptible

SNP calling and screening of candidate intervals

High-quality sequencing data were obtained by performing BSR-Seq analysis on the resistant and susceptible bulks.The resistant bulk generated 20.513 Gb of clean reads with a Q30 score > 93% and GC content of 43-73%. The susceptible bulk produced 27.825 Gb of clean data, showing a Q30 score > 94% and GC content of 41-72%. Alignment results indicated 137,400,008 and 186,646,126 reads from the resistant and susceptible bulks successfully mapped to the reference genome of Chinese Spring (IWGSC RefSeq v2.1), respectively. These high-quality sequences were deemed suitable for subsequent analyses. To reduce background noise, original euclidean distance (ED) values were quartic-transformed and used as correlation values, with a Loess curve applied for fitting. The threshold was determined using the quantile method, which entails arranging all fitted values in ascending order and designating the ED values of SNP markers exceeding the 99% as the threshold during the screening process. Using this threshold, the ED algorithm identified only one estimated candidate region situated at the terminal end of chromosome arm 2BL (Fig. 2a and b; Table S1). This result shows that PmLsy-93 resides on chromosome arm 2BL.

Fig. 2.

Candidate interval analysis of PmLsy-93. a SNPs distribution on 21 wheat chromosomes between resistant and susceptible bulks of Lsy-93 and Tainong 18 (TN18); b Euclidean distance (ED) analysis of the candidate region on 21wheat chromosomes

Molecular mapping of PmLsy-93 and prediction of candidate genes

Based on the BSR-Seq results, we further validated the candidate interval by screening 12 known markers surrounding the region of interest on chromosome arm 2BL and developing eight simple sequence repeat marker (SSR) and insertion-deletion polymorphism primer (Indel) markers derived from the BSR-Seq data. Eleven markers, including L43177, L11500, L93-293, CIT02g-20, S93-2, S93-46, L93-277, CIT02g-4, L93-21, CINAU140 and L93-260 (Table S2), showed polymorphism between resistant and susceptible parents as well as two bulks. Subsequently, based on the genotyping results of these markers on the 250 F_2:3 families, a genetic linkage map for PmLsy-93 was constructed (Fig. 3a). PmLsy-93 was mapped to a 1.5 cM interval flanked by markers S93-2 and S93-46, corresponding to a 10.34-Mb physical interval (710.73-721.07 Mb) based on the IWGSC RefSeq v2.1 (Fig. 3a and b).

Fig. 3.

Molecular mapping of PmLsy-93. a Genetic linkage map of PmLsy-93; b Amplification patterns of PmLsy-93-linked markers S93-2 and S93-46 in genotyping the resistant parent Lsy-93, susceptible parent Tainong 18, and randomly selected F_2:3 families of Lsy-93×Tainong 18. Lane M: pUC19/MspI; 1: Lsy-93; 2: Tainong 18; 3–7: homozygous resistant F_2:3 families; 8–12: heterozygous F_2:3 families; 13–17: homozygous susceptible F_2:3 families. The white arrows were used to indicate the polymorphic bands linked to PmLsy-93

Discovery and analysis of DEGs

After BSR-Seq analysis, 3,140 DEGs were identified between the two bulks, including 2,214 down-regulated and 926 up-regulated genes compared with the susceptible bulk (Fig. 4a). GO analysis indicated that these DEGs were mainly related to three functional domains. In molecular function, key activities included manganese ion binding, oxidoreductase activity, heme binding, and hydrolase activity acting on glycosyl bonds, which are critical for enzymatic reactions and metabolic regulation. In cellular component, enriched terms such as extracellular region and cell wall macromolecule catabolic process highlighted the involvement of DEGs in extracellular interactions and cell wall remodeling, which are vital for pathogen defense and structural integrity. In biological process, DEGs were linked to processes like response to water, response to biotic stimulus, and chitin catabolic process, indicating their roles in stress adaptation and pathogen resistance (Fig. 4b; Table S3). Using KEGG pathway enrichment analysis, the DEGs were significantly enriched in metabolic and signaling pathways associated with plant defense and stress tolerance. The MAPK signaling pathway-plant and plant-pathogen interaction pathways were enriched, highlighting their pivotal roles in defense mechanisms against pathogens. Additionally, glutathione metabolism and photosynthesis-antenna proteins were identified, emphasizing DEGs involved in mitigating oxidative damage during infection and involvement in energy production and light harvesting, respectively (Fig. 4c; Table S4). The integration of GO and KEGG analyses underscores the multifaceted roles of these DEGs in plant defense, stress response, and metabolic regulation.

Fig. 4.

The distribution and functional classification of differentially expressed genes (DEGs) based on the bulked segregant RNA sequencing (BSR-Seq) of the resistant and susceptible bulks of Lsy-93 × Tainong 18. a The distribution of the DEGs using a volcano plot; b A Gene Ontology (GO) analysis of the DEGs; c A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs

Expression patterns of the disease resistance-related genes in the candidate interval

To further identify candidate genes, DEGs within the candidate interval (710.73-721.07 Mb) were analyzed. A total of 123 highly confidence DEGs were found in this interval, and they were considered the essential candidates for powdery mildew resistance. Among these 123 DEGs, six ones were associated with disease resistance, and the expression patterns of these six DEGs between Lsy-93 and TN18 were analyzed at different hours post inoculation (hpi) with Bgt isolate E09. All genes were found to be induced by Bgt invasion. The transcription levels of TraesCS2B0361276100 (encoding disease resistance protein) and TraesCS2B0361276200 (encoding disease resistance protein) reached peak transcript levels at 0.5 hpi in resistant parent Lsy-93. The remaining four genes TraesCS2B03G1285300 (encoding serine threonine-protein kinase), TraesCS2B0361283800 (encoding serine threonine-protein kinase), TraesCS2B0361284900 (encoding serine threonine-protein kinase) and TraesCS2B0361290400 (encoding protein kinase domain) reached their peak transcript levels at 24 hpi or even later. Additionally, most of these genes displayed significantly higher expression in the early stage of inoculation in Lsy-93 compared to TN18 (Fig. 5; Table S2), suggesting potential regulatory mechanisms at the early stage of pathogen infection.

Fig. 5.

Expression patterns of TraesCS2B03G1285300, TraesCS2B0361276100, TraesCS2B0361276200, TraesCS2B0361283800, TraesCS2B0361284900 and TraesCS2B0361290400 in Lsy-93 and Tainong 18 (TN18) at 0, 0.5, 2, 4, 12, 24, 48 and 72 hours post inoculation (hpi) following the invasion of Blumeria graminis f. sp. tritici (Bgt) isolate E09. Error bars represent standard deviation (SD) based on three independent repeats. Asterisks indicate significant differences (t tests) between Lsy-93 and Tainong 18 at each time point (* P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001, ns: not significant); the sphemplasts indicate biological replicates; TaActin was used as the internal control

Screening of molecular markers for marker assisted selection (MAS)

To assess the potential of the linked markers in MAS, 46 susceptible wheat cultivars/lines were tested with markers L93-293, CIT02g-20 and L93-277. All these markers amplified polymorphic bands between Lsy-93 and most of wheat accessions, displaying their widely effective potential in different wheat backgrounds (Fig. 6; Table S5). Hence, when the PmLsy-93 was transferred into these genotypes, the corresponding markers could be employed to accelerate the transfer of PmLsy-93 in wheat breeding practices.

Fig. 6.

Amplification patterns of PmLsy-93-linked markers L93-293 and CIT02g-20 in Lsy-93 and 14 susceptible wheat cultivars/lines to powdery mildew. M: pUC19/MspI; 1: Lsy-93; 2: Yannong 15; 3: Yannong 17; 4: Yannong 30; 5: Yannong 161; 6: Yannong 191; 7: Yannong 836; 8: Yannong 5158; 9: Saidemai 16; 10: Shengmai 116; 11: Luomai 013; 12: Taishan 6039; 13: Xumai 1108; 14: Henong 974; The white arrows indicate the polymorphic bands in Lsy-93

Discussion

Spelt, an ancient hexaploid wheat subspecies, has emerged as a valuable genetic resource for enhancing powdery mildew resistance in modern wheat breeding programs. As a crop historically cultivated in Europe, spelt possesses a rich reservoir of disease resistance genes that have been largely lost in elite wheat cultivars due to intense selection for agronomic traits [18]. Of particular interest is its potential contribution to combating powdery mildew. Spelt accession Lsy-93 showed resistance against powdery mildew across all growth stages. Through genetic mapping in this study, a dominant Pm gene, provisionally designated PmLsy-93, was identified to confer this resistance. Using BSR-Seq and genetic markers, PmLsy-93 was mapped to a 10.34 Mb physical interval (710.73-721.07 Mb) on chromosome arm 2BL referred to IWGSC RefSeq v2.1. Six formally designated Pm genes, including Pm6 from T. timopheevii, have been reported to be located on chromosome arm 2BL, with diverse gene donors contributing to this locus [19], Pm33 from T. persicum Vav. [20], Pm51 from a Thinopyrum ponticum introgression line [21], Pm52 from Chinese wheat cultivar Liangxing 99 [22], Pm63 from Iranian wheat landrace PI 628,024 [23] and Pm64 from wild emmer [24]. Additionally, several temporarily named genes were also identified in this chromosome arm, such as PmQ, MlZec1, MlAB10, PmKN0816, PmJM809. Compared with those documented genes, PmLsy-93 (710.73-721.07 Mb) was derived from spelt, which has a unique source. Furthermore, PmLsy-93 could be clearly distinguished from four of them based on mapping interval: Pm6 (698.3-699.2 Mb), Pm33 (773.2-784.3 Mb), Pm52 (581.0-585.0 Mb) and Pm64 (699.2-710.3 Mb). It overlapped with Pm51 (709.8-739.4 Mb) and Pm63 (710.3-723.4 Mb). But even so, clarifying their allelism relationships through allelism tests and cloning these genes is also necessary in the future.

As for the gene donor spelt, several Pm genes and quantitative trait loci (QTLs) have been identified, such as Pm54 and PmTm4 [25, 26]. These genetic elements often trigger defense mechanisms like cell wall reinforcement and hypersensitive responses, providing multiple layers of protection against pathogen invasion [27].In this study, a total of 3,140 DEGs were detected between the two bulks. Compared with the susceptible bulk, 2,214 genes were down-regulated and 926 ones were up-regulated. The GO and KEGG enrichment analyses further provided comprehensive insights into the functional roles and metabolic pathways associated with the DEGs in response to biotic stress. The GO analysis revealed that DEGs were predominantly involved in molecular functions, which were critical for enzymatic reactions and stress responses. Additionally, cellular components like the extracellular region and cell wall-related processes suggested active remodeling during pathogen defense. Biological processes, including response to biotic stimuli and chitin catabolism, further emphasized the activation of defense mechanisms against pathogens [28]. The KEGG analysis highlighted key pathways linked to plant immunity. The enrichment of MAPK signaling and plant-pathogen interaction pathways underscored the importance of signal transduction in defense responses [29]. Furthermore, glutathione metabolism indicated a role in mitigating oxidative stress, while photosynthesis-related pathways suggested a balance between defense and energy metabolism [30]. These findings were consistent with previously studies, including PmW762, PmJM23 and PmL709 [31–33].

Looking forward, spelt accessions will continue to play a critical role in sustainable wheat disease management systems. Spelt have evolved into abundant genetic variations during the long process of domestication and adaptation to the environment. Numerous excellent traits could be used in modern wheat improvement, including yield, quality, disease resistance, and stress tolerance [16]. The ultimate goal of mining disease-resistant genes is to apply them in wheat breeding and production. In this study, PmLsy-93 is derived from spelt, which shares the A, B and D genomes with common wheat. Spelt has maintained greater allelic diversity in resistance-related genes due to its adaptation to diverse environments and high selection pressure. Compared with the alien species of wheat without any of A, B, D genomes, it can be easily integrated in wheat genome without linkage drags [34]. Therefore, PmLsy-93 has high potential in wheat breeding to combat powdery mildew. MAS now enables more precise transfer of the target genes while minimizing linkage drag. To promote the transfer of PmLsy-93 by means of MAS, three PCR-based and co-dominant markers were screened to be available for efficiently tracing PmLsy-93 once it has been introduced into those cultivars/breeding lines. Furthermore, the strategic integration of spelt genetic resources with resistance loci from wild relatives may offer a robust, multi-layered defense system against rapidly evolving pathogen populations. With the climate change and intensive agricultural practices, the conservation and exploitation of genetic diversity in ancient wheat varieties such as spelt is emerging as a critical component of global food security strategies.

Conclusion

In this study, a single dominant Pm gene PmLsy-93 was identified in the spelt accession Lsy-93. The results provide valuable insights into plant-pathogen defense mechanisms and lay an foundation for subsequent molecular breeding efforts to enhance crop disease resistance.

Materials and methods

Plant materials

Spelt wheat Lsy-93 sourced from Prof. Hongxing Xu, Henan University, Kaifeng, China. The Bgt isolate E09 is prevalent in northern regions of China, which was sourced from Prof. Yilin Zhou, State Key Laboratory for Biology of Plant Disease and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China. Because Lsy-93 displayed continuous resistance to powdery mildew across all growth stages, it was selected as the resistant parent for hybridization with the susceptible parent TN 18. F₁, F₂ and F_2:3 progenies were produced for genetic and BSR-Seq analysis. The susceptible wheat cultivar TN18 was also planted as a susceptible control.

Phenotypic evaluation

The F₁, F₂, and F_2:3 progenies of Lsy-93 × TN18 was planted in the 128-cell rectangular trays, and 5–8 seeds were sown in each cell, which were inoculated with the Bgt isolates for genetic analysis and resistance assessment. The incubator was set at 20℃ for 14 h daily and 18℃ for 10 h nightly. Upon reaching the two-leaf stage, seedlings underwent phenotypic observations. ITs were scored on a 0–4 scale. Plants with 0–2 were categorized as resistant, while those with ITs 3 and 4 were considered susceptible [35]. As for the phenotypic evaluation using different Bgt isolates, each isolate was put in independent airtight space to avoid cross infection. Evaluation procedure was repeated three times to guarantee the reliability of the results. For F_2:3 families, at least 20 seeds per family were planted and assessed. At the same time, TN18 were randomly distributed and planted in each tray.

Genetic analysis

For genetic analysis, 10 F₁, 253 F₂, and 252 F₂:₃ families (approximately 20 seedlings per family) were planted and inoculated with Bgt isolate E09 for resistance phenotyping. The Chi-squared test (χ²) was used to check goodness-of-fit to expected the Mendelian segregation ratio for monogenic inheritance.

Microscopic evaluation of powdery mildew resistance responses

To additionally analyze hyphal morphology post-invasion by Bgt isolate E09, 10 seedlings Lsy-93 and 10 seedlings TN18 were planted separately. At 0, 0.5, 2, 4, 12, 24, 48, and 72 h post inoculation (hpi) after Bgt invasion, 2 cm seedling leaf samples were collected from Lsy-93 and TN 18. Samples were fixed using Carnoy’s fixative (anhydrous alcohol-glacial acetic acid, 3:1, v/v) immediately and remained at an environmental temperature of 37℃ for 24 h. Before observation under the microscope, the samples were stained in 5 mL of 0.6% (w/v) Coomassie blue solution for 5 min and then wash the leaves with distilled water to remove the reagent residue [36]. Finally, an Axioscope 5 microscope (ZEISS, Oberkochen, Germany) was used for sample analysis.

RNA extraction and BSR-Seq library preparation

At 10 days post inoculation (dpi), leaf tissues were sampled (10 plants per family) from 30 homozygous resistant and 30 homozygous susceptible F_2:3 lines. Equal amount of these samples were mixed to generate resistant (R) and susceptible (S) bulks, from which total RNA was extracted using the RNA Simple Total RNA Kit (Tiangen, Beijing, China). To purify mRNA from total RNA samples, oligo(dT) beads were added to the mixture, leveraging the specific binding between the poly-A tails of mRNA and the beads. The mixture was then gently shaken and incubated at 18–20 °C for 15–30 min. Subsequently, the beads were washed with a washing solution to remove non-mRNA components such as rRNA and tRNA. Before this purification step, RNA quality was initially evaluated by agarose gel electrophoresis, spectrophotometry, and other methods. Following successful mRNA purification, fragmentation was achieved using either chemical reagents or enzymatic digestion. After fragmentation, cDNA synthesis was carried out using reverse transcriptase in conjunction with random primers. The obtained cDNA was subjected to end repair and adapter ligation, after which the ligation products were amplified by PCR to generate the final sequencing library. Subsequently, the library was quantified and its quality was assessed to ensure it met the requirements for sequencing [37].

Sequencing and data analysis

The sequencing was carried out on the Illumina HiSeq4000 platform (Illumina HiSeq4000) at Tcuni Bioscience (Chengdu, China). At Tcuni Bioscience, large quantities of sequencing data were produced as short-read sequences. The raw data pre-processing steps included read quality score assessment, low-quality reads elimination, and adapter sequence trimming. Subsequently, the cleaned data were aligned to IWGSC RefSeq v2.1 to prepare for subsequent analysis using the STAR software [38].

Determination of the candidate interval and genetic mapping of the target Pm gene

To identify the target interval, the following procedures were implemented. Initially, SNP calling for the resistant and susceptible bulks was carried out using the software packages GATK v4.2.3.0 and SAMtools v1.17 [39]. This was followed by the quantification of allele frequencies for each SNP across the two bulks. Following the calculation of SNP index values using MutMap, the ΔSNP index for each SNP was defined as: ΔSNP index = SNP index (resistant) – SNP index (susceptible) [40, 41]. Subsequently, the linkage between SNPs and the target gene(s) was determined using Bayesian analysis integrated with the Euclidean distance (ED) algorithm. Potential candidate intervals were then identified according to previously reported procedures [37].

Following the identification of the candidate interval, molecular markers within it were developed to map the target Pm gene. Polymorphic genetic markers were applied to genotype the F_2:3 families from the Lsy-93 and TN18 cross for mapping. Subsequently, phenotypic and genotypic data were collected, followed by linkage analysis using Mapmaker 3.0b [42]. A LOD score threshold of 3.0 was applied. And the genetic map of the Pm gene in Lsy-93 was constructed using Mapdraw v2.1 [43].

DEGs analysis associated with the powdery mildew resistance in Lsy-93

After BSR-Seq, software like HTSeq v2.0.3 or featureCounts v2.0.1 estimated transcript abundances mapped to each gene to quantify candidate gene expression levels. Statistical comparisons between experimental groups were made using EBSeq v3.5 to identify DEGs with a fold change ≥ 2 and FDR (false discovery rate) < 0.01. For functional characterization of the identified DEGs, annotation was conducted using GO and KEGG databases, combined with an R package specifically designed for analyzing DEGs [44]. Finally, an enrichment analysis of DEGs in terms of defined pathways, cell structures, or molecular activities provided insights into the role of candidate genes. After locking the candidate interval, high confidence DEGs related to disease resistance were selected for subsequent expression analysis.

qRT-PCR

qRT-PCR was performed to validate the expression pattern of the DEGs potential linked to disease resistance within the target interval. At 0, 0.5, 2, 4, 12, 24, 48, and 72 hpi, leaves with a length of 3–5 cm of Lsy-93 and TN 18 were collected, respectively. Total RNA was isolated from samples using the RNAsimple Total RNA Kit (Tiangen, Beijing, China). Primers were designed using Primer5 software. Approximately 2 µg of RNA was reverse transcribed into cDNA by employing a FastQuant RT Kit (Tiangen, Beijing, China). qRT-PCR reactions were prepared with SYBR Premix Ex Taq (Takara, China) and conducted on a Bio-Rad CFX Connect real-time PCR system (BIO-RAD, Hercules, USA) following standard protocols. The TaActin gene was chosen as the reference gene. Gene expression levels were finally calculated using the 2^−∆∆Ct method [45]. Each sample underwent triplicate testing.

Evaluation of linked markers available for MAS

Markers that amplify polymorphic bands between the 46 wheat genotypes collected from major wheat-producing areas in China and Lsy-93 can be identified as suitable for MAS in corresponding genetic background.

Abbreviations

Bgt

Blumeria graminis f. sp. Tritici

NBS-LRR

Nucleotide-binding site leucine-rich repeat

BSR-Seq

Bulked segregant RNA sequencing

SNP

Single nucleotide polymorphism

DEGs

Differentially expressed genes

GO

Gene ontology

COG

Clusters of orthologous groups

KEGG

Kyoto encyclopedia of genes and genomes

IT

Infection type

ED

Euclidean distance

SSR

Simple sequence repeat marker

Indel

Insertion-deletion polymorphism primer

hpi

Hours post-inoculation

TN18

Tainong 18

MAS

Marker-assisted selection

QTL

Quantitative trait loci

dpi

Days post inoculation

FDR

False discovery rate

qRT-PCR

Real-time quantitative PCR

Authors’ contributions

PM, YJ and HZ conceived the research. HZ, YJ, JL, JL, NY, HX, QS, TY, JZ, LL performed the experiments and collected data. NS, JL and JL performed data analyses. NY developed the experimental materials. HZ, YJ and PM wrote and revised the manuscript. All authors read and approved the final manuscript.

Funding

This research was financially supported by Key R&D Program of Shandong Province (2024LZGC001), National Modern Wheat Industry Technology System, Yantai Comprehensive Experimental Station project (CARS-03-62), National Natural Science Foundation of China (32301923), Natural Science Foundation of Shandong Province, China (ZR2023QC203) and Henan Province Natural Science Foundation (232300420003).

Data availability

The datasets generated and analysed during the current study are available in the National Center for Biotechnology Information repository, SRA: SUB15322822.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.