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Article

Transcriptomic Analysis Reveals the Molecular Defense Mechanisms of Poa pratensis Against Powdery Mildew Fungus Blumeria graminis f. sp. Poae

by
Zhiyu Xu
1,
Zhanchao Guo
1,
Fan Wu
1,
Yining Zhang
1,
Yumin Zhao
1,
Lingjuan Han
1,2,
Peng Gao
1,2,
Huisen Zhu
1,2,
Qingfang Xu
1,2,
Xiang Zhao
1,2 and
Yinping Liang
1,2,*
1
College of Grassland Science, Shanxi Agricultural University, Jinzhong 030801, China
2
Shanxi Key Laboratory of Grassland Ecological Protection and Native Grass Germplasm Innovation, Jinzhong 030801, China
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(11), 2543; https://doi.org/10.3390/agronomy14112543
Submission received: 1 October 2024 / Revised: 25 October 2024 / Accepted: 26 October 2024 / Published: 29 October 2024
(This article belongs to the Special Issue Research Progress on Pathogenicity of Fungi in Crops—2nd Edition)
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Versions Notes

Abstract

:
Kentucky bluegrass (Poa pratensis L.) is a valuable cool-season turfgrass widely utilized for forage, turf, and ecological purposes; however, its productivity and ornamental value are significantly compromised by powdery mildew, caused by Blumeria graminis f. sp. Poae, which negatively affects turf quality. In the present study, we examined the interactions between P. pratensis varieties and B. graminis, focusing on primary haustorium formation at 24 h post-inoculation and the formation of germ tubes at 48 h post-inoculation. We explored the molecular mechanisms underlying the response of different P. pratensis varieties at 48 h post-inoculation via transcriptomic techniques. Our results revealed that the primary haustorium formation rate in ‘Taihang’ at 24 h after B. graminis inoculation was significantly lower than that in ‘Explorer’ and ‘Black Jack’. The conidia of B. graminis could form two to five germ tubes, and the proportion of conidia that formed five germ tubes in ‘Taihang‘ at 48 h post-inoculation was significantly lower than that in the other two varieties. Transcriptome analysis revealed 680,765 transcripts as unigenes. A total of 9983 unigenes were identified as differentially expressed genes in one or more varieties of P. pratensis after inoculation with powdery mildew compared with the control. In total, 6284 differentially expressed genes were upregulated in ‘Taihang’, which was substantially greater than those in ‘Black Jack’ (4530) and ‘Explorer’ (4666). Moreover, 2843 differentially expressed genes were specific to ‘Taihang’, whereas 1644 and 1590 unique differentially expressed genes were specific to ‘Explorer’ and ‘Black Jack’, respectively. The specifically expressed genes play crucial roles in determining the disease resistance of powdery mildew. Notably, the expression of genes encoding chitinase, gamma-glutamyltranspeptidase 1, UDP-arabinopyranose mutase 1, oxalate oxidase 2, mitogen-activated protein kinase kinase 1-like, tryptophan decarboxylase, and aromatic L-amino acid decarboxylase was closely related to powdery mildew resistance in ‘Taihang’, making them promising candidate genes for studying resistance to powdery mildew in P. pratensis. This study identified critical genes involved in powdery mildew resistance in P. pratensis, providing a basis for future gene mining and molecular breeding to increase disease resistance in P. pratensis.

1. Introduction

Kentucky bluegrass (Poa pratensis L.) is a rhizomatous perennial grass that is excellent forage and turf grass [1,2,3,4]. It makes beautiful, lush and finely textured lawns on golf courses and in squares and parks because of its high adaptability [5], including infrequent mowing, trampling tolerance, cold resistance and versatility [6]. Additionally, Kentucky bluegrass has important ecological applications [7]. However, the susceptibility of this species to diseases and pests and its sensitivity to heat, drought and salt limit its wide cultivation [6,8].
Blumeria graminis (DC.) Speer is an obligate fungal pathogen that causes powdery mildew in most Poaceae crops and grasses [9,10]. The species B. graminis contains eight formae speciales (ff. spp.), defined by their host specificity, such as B. graminis f. sp. secalis, hordei, tritici, avenae, poae, bromi, agropyri and dactylidis [9]. B. graminis f. sp. tritici can lead to estimated annual yield losses of 7.6–19.9% in wheat [11]. P. pratensis powdery mildew, caused by B. graminis f. sp. Poae (Bgp), poses a great threat to Kentucky bluegrass. Kentucky bluegrass is commonly used in seed and sod production for turfgrass establishment [12]. Powdery mildew outbreaks can reduce seed quality and yield, affect sod production and diminish the market value of turfgrass products, impacting the profitability of seed and sod producers [13]. Bgp has been reported to occur on P. pratensis in Poland, Switzerland, Japan and China [9,10,14,15]. Powdery mildew negatively affects the yield and quality of grasses, reduces their ornamental value and shortens their life. In addition, P. pratensis may serve as a primary inoculum reservoir from which B. graminis can attack other species, including cereal crops, because the hybridization of B. graminis ff. spp. allows pathogens to adapt to new hosts [16,17]. Therefore, controlling the occurrence of P. pratensis powdery mildew in Kentucky bluegrass is important.
Fungicides can be sprayed on host leaves to control the disease, but powdery mildew fungi are able to develop fungicide resistance because of the frequent application of commercial fungicides, pathogens with a shorter life cycle, an abundance of sporulation and the ability of spores to spread [18,19]. To avoid fungicide resistance and the environmental problems caused by fungicide residues, new control strategies that are independent of chemical methods are needed to control powdery mildew [20]. The use of an integrated pest management (IPM) programme is highly recommended for sustainable agriculture. An IPM programme includes the combination of chemical control, the use of resistant varieties, the use of biological control agents and appropriate cultural practices [18]. However, P. pratensis varieties resistant to powdery mildew are scarce, and the resistance mechanism of P. pratensis powdery mildew is still unclear. Plants resist pathogens via a two-branch immune system, including a general response triggered by pathogen-associated molecular patterns (PAMPs) and a specific response triggered by effectors [21,22]. PAMP-triggered immunity (PTI) is initiated by cell surface-localized pattern-recognition receptors (PRRs), and effector-triggered immunity (ETI) is initiated by intracellular nucleotide-binding domain leucine-rich repeat-containing receptors (NLRs) [21,22]. Recently, important components in PTI and ETI were shown to be needed for both PTI and ETI; in addition, PTI and ETI potentiate each other to achieve stronger plant defenses [23]. Therefore, the model of plant immunity does not involve two independent branches but rather one integrated pathway that needs all of its components to be fully functional [23]. The expression of the light-harvesting antenna protein genes LHCA and LHCB, and the photosynthetic electron transport genes petE and petH, EDS, RPS and WRKY decreased significantly in P. pratensis leaves inoculated with Bgp after 14 days [10]. Furthermore, the expression of genes involved in plant–pathogen interactions, such as HSP90, RBOH and RPM, was upregulated in infected leaves [10]. Glutamine synthetase gene PpGS1.1 negatively regulates the powdery mildew resistance in Kentucky bluegrass [24].
Recently, transcriptome analysis has been widely used in P. pratensis to reveal abundant variation in response to biotic and abiotic stresses, such as drought [25,26,27,28], salt [29,30], cold [31], heat [32], cadmium [33,34,35] and copper [36], as well as other traits, such as plant height [37], inflorescence development [38] and wax deposition [39], at the transcriptional level. For example, differential transcriptomics revealed that the ‘starch and sucrose metabolism’, ‘photosynthesis’ and ‘fatty acid metabolism’ pathways were the key metabolic pathways of a P. pratensis variety with high resistance to powdery mildew infection [40]. B. graminis infection led to a reduction in the sclerenchyma area, the expansion of vesicular cells and the movement of chloroplasts in P. pratensis [10]. B. graminis conidia germinate in a special manner, producing two types of germ tubes: primary germ tubes, which never penetrate the host cells, and longer and thicker secondary germ tubes, which produce penetrating hyphae. The pathogen of plant powdery mildew delivers the effector via the haustorium, so the haustorium-forming stage is important for the initiation of plant ETI, which affects the plant immune system [41,42].
In this study, comparative transcriptomic techniques were applied to the leaves of P. pratensis at 48 h post-inoculation (hpi) with Bgp, which is when mature haustoria are formed. Elucidating the interaction mechanism between P. pratensis and Bgp will enrich the knowledge of plant resistance mechanisms against Bgp and will be helpful for the breeding and application of resistant varieties. Insights gained from transcriptomic analysis will help in the development of targeted and precise treatment protocols for managing powdery mildew infections in Kentucky bluegrass. This will lead to more efficient use of resources, reduced application of chemical inputs and improved disease control, thereby positively impacting the economic sustainability of the turfgrass industry.

2. Materials and Methods

2.1. Plant and Pathogen Materials

In the present study, the Bgp BGP(TG) strain was isolated from the leaves of diseased P. pratensis plants in a greenhouse at the College of Grassland Science of Shanxi Agricultural University (37°25′ N, 112°35′ E) and purified via the single-spore heap purification method and conidium shaking method. The BGP(TG) isolate was propagated and preserved in 30-day-old P. pratensis ‘Explorer’ plants [43]. Three varieties of P. pratensis (‘Explorer’, extremely susceptible to BGP(TG); ‘Black Jack’, moderately susceptible to BGP(TG); and ‘Taihang’, moderately resistant to BGP(TG)) were used in the experiment [43]. The seeds of P. pratensis ‘Explorer’ and ‘Black Jack’ were provided by Beijing Rytway Seed Co., Ltd. (Beijing, China) and Beijing Clover Seed and Turf Co. (Beijing, China). The seeds of P. pratensis ‘Taihang’, which were selected and bred by Professor Zhu Huisen of Shanxi Agricultural University, were preserved at the College of Grass Science of Shanxi Agricultural University.

2.2. Cytological Observation of the Interaction Between Kentucky Bluegrass and Bgp

‘Explorer’, ‘Black Jack’ and ‘Taihang’ seeds of the same size and full grains were selected. The seeds were first soaked in 75% alcohol for 1 min and then washed with sterile water 3–5 times until no alcohol odor was present. Finally, the seeds were evenly sown in a pot containing sterile substrate (seedling substrate–sand = 2:1, volume ratio) with a sowing amount of 10 g/m2 and covered with 2–3 mm of vermiculite. Three P. pratensis varieties were planted in 16 seedling pots each, and the 48 seedling pots were placed in an artificial climate incubator with a random group arrangement (temperature, 20 °C; 16/8 h light–dark cycle; relative humidity, 60 ± 2%). Distilled water was sprayed every day before emergence to maintain adequate moisture, and the plants were watered every 5 days after emergence. The intensive shaking inoculation method was used to inoculate P. pratensis with Bgp after sowing for 1 month, with a density of 100–200 spores/mm2 [44]. After inoculation, P. pratensis plants were cultured in an artificial climate incubator. Samples were taken at 24 and 48 hpi, with 3 replicates per time point, and 5–10 segments of leaves were taken for each replicate. The leaves were decolorized immediately after sampling via an AA solution (ethanol–acetic acid = 1:1, volume ratio) [45]. The decolorized leaves were stained with Coomassie bright blue staining solution (0.15% trichloroacetic acid aqueous solution–0.6% Coomassie bright blue R-250 methanol solution = 1:1, volume ratio) for 4 h, rinsed with distilled water and stored in a glacial acetic acid–glycerin–water mixture (1:4:15, volume ratio) [45,46]. Leaf staining was observed under a microscope, and haustorium formation at 50–100 interaction sites at 24 hpi after inoculation with Bgp and the number of germ tubes at 50–100 interaction sites at 48 hpi after inoculation with Bgp were examined.

2.3. RNA Extraction

Leaves from the treatment group and control group were randomly collected from ‘Taihang’, ‘Black Jack’ and ‘Explorer’ plants at 48 hpi, as each sample comprised three biological replicates. A total of 18 leaf samples were frozen in liquid nitrogen and submitted to a commercial service (Wekemo Tech Group Co., Ltd., Shenzhen, China) for RNA-seq. Briefly, total RNA was extracted from P. pratensis plants via the TRIzol reagent method (Invitrogen Life Technologies, Carlsbad, CA, USA) [47].

2.4. cDNA Library Construction

After the integrity and purity of the RNA were checked via an Agilent 2100 Bioanalyzer (Agilent Technologies Co., Ltd., Santa Clara, CA, USA) [48] and a NanoDrop ND-2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA), a cDNA library was constructed via the NEBNext Ultra RNA Library Prep Kit for Illumina (NEB, San Diego, CA, USA) following the manufacturer’s recommendations.

2.5. RNA-Seq

Finally, RNA-seq was performed on an Illumina Novaseq 6000 platform (Illumina, San Diego, CA, USA) in accordance with the 150 bp paired-end sequencing strategy [49]. All the raw sequencing data have been submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA), and the accession number is PRJNA1032119.

2.6. Alignment of RNA-Seq Reads and Differential Gene Expression Analysis

The sequencing data were filtered via Trimmomatic v0.39 software [50], and reads that contained sequencing connectors or those that were of low quality were removed from the raw reads. The filtered high-quality clean reads were spliced via Trinity v2.1.1 software to obtain a reference sequence for subsequent analysis [51]. On the basis of Trinity concatenation, Corset aggregated transcripts into clusters according to shared reads among transcripts [52]. Then, by combining the expression levels of transcripts among different samples and the H-cluster algorithm, transcripts with differential expression between samples were separated from the original cluster. New clusters were created, and each cluster was eventually defined as a “Gene”. All identified genes were functionally annotated via BLASTX against the NCBI nonredundant (NR), NCBI nucleotide sequence (Nt), euKaryotic orthologous (KOG), Swiss-Prot protein, UniProt, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. The expression levels of the transcripts were subsequently calculated and normalized to transcripts per million reads (TPM) values via RNA-Seq by Expectation-Maximization (RSEM) v.1.2.28 software [53]. Furthermore, DEseq2 was applied to detect differentially expressed genes (DEGs) in pairwise comparisons with thresholds of a false discovery rate (FDR) < 0.05 and |log2(fold change) > 1.

2.7. Reliability Analysis by qRT-PCR

To confirm the reliability of the RNA-seq data, we randomly chose 5 expressed genes for qRT-PCR experiments. A PrimeScriptTM 1st Strand cDNA Synthesis Kit (Takara Bio, Beijing, China) was used to synthesize cDNA for qRT-PCR. The sequences of the primers used were designed via NCBI Primer-BLAST and are listed in Table 1. The reactions were conducted on a LightCycler® 480 real-time PCR system (Roche, Basel, Switzerland) together with AceQ® qPCR SYBR® Green Master Mix (Vazyme, Nanjing, China). The relative expression levels of the abovementioned 5 genes were calculated according to the 2−△△Ct method [54], with Actin used as a reference gene [55]. The experiments were performed with three biological replicates, and each biological replicate involved three technical repeats.

2.8. Statistical Analysis

Statistical analysis was conducted with SPSS 26.0 statistical software (SPSS Inc., Chicago, IL, USA), and one-way ANOVA and Duncan’s test were used to analyze significant differences in cytological parameters. Origin 2021 software (OriginLab., Northampton, MA, USA) was used for drawing.

3. Results

3.1. Phenotypic Differences in Leaves Affected by Bgp

Nine days after inoculation with Bgp, the leaf surface of ‘Explorer’ was covered by a white powder layer, and the leaf areas of ‘Taihang’ and ‘Black Jack’ were much lower than that of ‘Explorer’ (Figure 1).

3.2. Estimation of P. pratensis–Bgp Interactions

There was a great difference in the haustorium formation rate during infection with powdery mildew among the different P. pratensis varieties. In this study, haustorium formation from conidia of Bgp was statistically analyzed at 24 hpi (Figure 2). There was no significant difference in the abundance of conidia with haustoria between ‘Explorer’ and ‘Black Jack’ (p > 0.05), but the values for both were significantly greater than that for ‘Taihang’. In addition, the abundance of conidia without haustoria was significantly greater than that of conidia with haustoria in ‘Taihang’. In this study, during the process of Bgp infection on the leaves of P. pratensis, the number of conidial bud tubes of Bgp changed with infection time, with primary and appressorium germ tubes giving rise to grades 3, 4 and 5 germ tubes (Figure 3).
At 48 h after inoculation with Bgp, the proportion of conidia with 4 germ tubes was the highest in all the three varieties of P. pratensis. The percentage of conidia with 2 germ tubes on ‘Black Jack’ and ‘Taihang’ was significantly greater than that on ‘Explorer’ (<0.05), and the percentage of conidia with 3 germ tubes on ‘Taihang’ was significantly greater than that on ‘Explorer’ and ‘Black Jack’ (<0.05). However, the percentage of conidia with 5 germ tubes on ‘Taihang’ was significantly lower than that on ‘Explorer’ and ‘Black Jack’ (<0.05) (Figure 4).

3.3. Statistics of Transcriptome Sequencing and Assembly

All the samples were sequenced to produce 40.38 million raw sequences, and the length of the original sequences was greater than 6.06 Gbp. Among them, the length of the clean sequences was greater than 5.68 G. In addition, the base error rate was low at 0.03%, the Q20 value was 100% and the Q30 value was greater than 99.89%. The GC content was between 52% and 57%. Clean data were de novo assembled via Trinity software, and the results were evaluated. There were 680,765 unigenes obtained from 18 samples. The average length of the unigenes was 3137.5 bp, and the N50 length was 4436 bp.

3.4. Functional Annotation and Classification of Unigenes

To obtain the functional information of genes, the unigenes were annotated with gene function via transcriptome assembly via BLAST and seven databases (Nr, Nt, KOG, Swiss-Prot, UniProt, KEGG and GO). The results revealed that 444,748 (65.33%) of the 680,765 unigenes had significant matches in at least one of the seven databases. Among them, 398,725 (58.57%), 337,657 (49.6%), 277,595 (40.78%), 253,347 (37.22%), 252,892 (37.15%), 168,931 (24.81%) and 149,755 (22%) unigenes had significant matches in the NR, NT, KOG, Swiss-Prot, UniProt, KEGG and GO databases, respectively.
The results of unigene functional annotation in the NR database revealed that the species that could be compared with P. pratensis were primarily Triticum aestivum (26.54%), Brachypodium distachyon (16.94%), Aegilops tauschii subsp. Strangulate (16.14%), Hordeum vulgare (16.30%), Triticum urartu (4.35%), Oryza sativa Japonica Group (2.54%), B. graminis f. sp. hordei DH14 (2.38%), Panicum virgatum (1.90%), Zea mays (1.87%) and Oryza brachyantha (1.17%). They noted that the species closely related to P. pratensis were Brachypodium, wheat and other Triticeae species.
GO annotation analysis was performed to classify the predicted functions of the P. pratensis unigenes. A total of 149,755 unigenes were successfully annotated and classified into three main categories: molecular functions, cellular components and biological processes. The top three terms in the biological process category were cellular process (42,133), metabolic process (34,646) and cellular metabolic process (30,992); those in the cellular component category were obsolete cell (54,330), obsolete cell part (54,323) and intracellular anatomical structure (48,928); and those in the molecular function category were catalytic activity (29,148), binding MF (21,575) and transferase activity (12,485).
KOG annotation analysis was performed to classify the predicted functions of P. pratensis unigenes. A total of 277,595 unigenes were successfully annotated and classified into 25 metabolic pathways. The top three terms were general function prediction only (34,278); signal transduction mechanisms (20,092); and post-translational modification, protein turnover and chaperones (19,849).
After KO annotation, the genes were classified according to the KEGG metabolic pathway in which they participated. A total of 168,931 unigenes were successfully annotated and classified into 755 functional categories, including 5 primary pathways: environmental information processing (9.04%), organismal systems (10.42%), cellular processes (6.45%), metabolism (27.5%) and genetic information processing (10.2%). The top five secondary pathways were general function prediction only (34,278), metabolic pathways (10.19%), biosynthesis of secondary metabolites (5.85%), microbial metabolism in diverse environments (2.28%), carbon metabolism (1.42%) and the MAPK signaling pathway (1.4%).

3.5. Statistics and Analysis of DEGs

Compared with those of the control, the gene expression levels of the three P. pratensis varieties changed considerably after inoculation with powdery mildew, with |log2(fold change)| > 1 and FDR < 0.05 used as the standards. However, the number of modified genes differed among the varieties; ‘Taihang’ contained 6284 upregulated DEGs and 309 downregulated DEGs, whereas ‘Black Jack’ contained 4530 upregulated DEGs and 492 downregulated DEGs, and ‘Explorer’ contained 4666 upregulated DEGs and 437 downregulated DEGs (Figure 5, Table S1). The number of DEGs in the three varieties were compared, and a Venn diagram was generated to visualize the unique and common DEGs of each variety. The results revealed that there were 9983 DEGs in one or more varieties of P. pratensis after inoculation with Bgp compared with the control; 2829 DEGs were shared by the three varieties, 2843 DEGs were unique to ‘Taihang’, 1590 DEGs were unique to ‘Black Jack’ and 1644 DEGs were unique to ‘Explorer’ (Figure 6).

3.6. GO Functional Enrichment Analysis of Differentially Expressed Genes

There were 1415, 1291 and 1422 enriched GO terms in ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively (Figure 7 and Table S2). Among them, 34 molecular functions, 88 biological processes and 14 cellular components were enriched with the DEGs specific to ‘Taihang’. For example, the molecular functions included endochitinase activity, with 4 genes; the biological processes included glutathione transport, regulation of the salicylic acid biosynthetic process, response to the host immune response and the pentose biosynthetic process, with 6, 4, 6 and 4 genes, respectively; and the cellular components included the superoxide dismutase complex, with 4 genes (Figure 8).

3.7. KEGG Functional Enrichment Analysis of Differentially Expressed Genes

The KEGG pathway terms enriched with the DEGs of the three varieties inoculated with Bgp differed. Nine, 11 and 8 KEGG pathways were enriched in ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively (Table S3). Among them, 8 KEGG pathways were enriched with the DEGs in all three varieties. A total of 55 DEGs were enriched in the KEGG pathways in the three varieties, and 6, 11 and 5 DEGs were enriched in only the KEGG pathways ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively (Figure 9).

3.8. Verification of DEGs by qRT-PCR

To verify the reliability of the transcriptome data, five DEGs in ‘Taihang’ were randomly selected, and the genes significantly expressed in the other two varieties were subjected to qRT-PCR. The qRT-PCR results were essentially consistent with the RNA-seq data, and the correlation coefficient reached 0.800 (Figure 10), indicating that the sequencing results were real and reliable.

4. Discussion

4.1. Germ Tubes

It is generally believed that only primary germ tubes and appressorium germ tubes are formed during the germination of Blumeria graminis conidia; occasionally, several secondary germ tubes without appressoria are formed, but these secondary germ tubes do not have the characteristics needed for infection [44,45]. However, the results showed that the conidia of Bgp could not only form primary germ tubes and appressorium germ tubes but also form third- to fifth-level germ tubes in P. pratensis, which is a feature of Bgp distinct from that of other B. graminis. In addition, the proportion of Bgp conidia with five germ tubes in ‘Taihang’ at 48 hpi was significantly lower than that in the other two varieties, so the infection process was slower in ‘Taihang’ than in other two varieties. The number of conidial germ tubes indirectly reflects the ability of Bgp to infect P. pratensis.

4.2. Genes Related to Resistance to Bgp in ‘Taihang’

4.2.1. Chitinases

Chitin is a natural biopolymer composed of N-acetyl-D-glucosamine units linked with β-1,4-glycosidic bonds. Chitinase (EC 3.2.1.14) is a hydrolytic enzyme that can cleave the β-1,4-glycosidic bonds in chitin. Chitin is a major cuticle element of the peritrophic membrane (the protective lining of the gut of many insects), the cell walls of fungi and the skeletons of many crustacean animals [56]. Plant chitinases are pathogenesis-related proteins. When plant cells are under pathogen stress, plant chitinases are strongly expressed; hence, plant chitinases play a critical role in the defense against fungal pathogens [57]. The genes Cluster-62878.135468, Cluster-62878.156398, Cluster-62878.82261 and Cluster-62878.98168 were identified as encoding a class I chitinase, basic endochitinase A, basic endochitinase A and chitinase, and their expression was increased 11.96-, 14.52-, 121.94- and 300.25-fold, respectively, in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp. Chitinases can bolster the plant defense system as they act on chitin, a major component of the cell wall of pathogenic fungi, and render the fungi inactive without any negative impact on the plants [58].

4.2.2. Gamma-Glutamyl Transpeptidase

Numerous gamma-glutamyl transpeptidases have been reported in plants [59]. Gamma-glutamyl transpeptidases participate in the degradation of glutathione and translocate extracellular amino acids via a transpeptidation reaction involving intracellular glutathione [60,61]. Genome annotation of Bacillus subtilis Dcl1 revealed its potential to synthesize catalase, superoxide dismutase, peroxidases, gamma-glutamyltranspeptidase, glutathione and glycolate oxidase to confer oxidative stress protection to plants under changing environmental conditions [62]. The gene Cluster-62878.153396 was identified as encoding a gamma-glutamyltranspeptidase, and its expression was increased 149.09-fold in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

4.2.3. SAR Deficient 1

Plants possess a unique form of broad-spectrum long-distance immunity termed systemic acquired resistance (SAR). SAR involves the rapid generation of mobile signals in response to localized microbial infection; these signals are transported to distal tissues and ‘prime’ the tissue against future infection by related and unrelated pathogens [63]. The gene Cluster-62878.448722 was identified as encoding the protein SAR DEFICIENT 1 isoform X1, and its expression was increased to 165.42-fold in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

4.2.4. DnaJ Protein ERDJ3B

Eukaryotic cells possess an endoplasmic reticulum quality control (ERQC) system, and the stromal cell-derived factor 2 (SDF2)-endoplasmic reticulum-localized DnaJ family 3 (ERDJ3)-binding immunoglobulin protein (BiP) chaperone complex plays a crucial role in protein folding, maturation, translocation, and degradation in ERQC [64,65]. Studies have highlighted the dynamics of ERDJ3B in plants under pathogen, high-temperature and cadmium stress challenge conditions [66,67,68]. The genes Cluster-62878.206400 and Cluster-62878.215694 were identified as encoding the dnaJ protein ERDJ3B, and their expression was increased to 5.74- and 3.58-fold, respectively, in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

4.2.5. UDP-Arabinopyranose

All plant cells are surrounded by a cell wall consisting of polysaccharides as the most abundant component, as well as proteins and occasionally lignin [69]. The cell walls of land plants form arabinofuranosyl residues from uridine diphosphate (UDP)-L-arabinofuranosyl (UDP-Araf), and UDP-Araf is formed from UDP-L-arabinopyranose (UDP-Arap) by UDP-L-arabinopyranose mutase (UAM) [70,71]. The cell walls have several very important functions in plants: they allow the plant to stand upright, they provide the cell structure, they mediate interactions between cells, and they provide a barrier against attack from herbivores and disease agents [69]. The genes Cluster-62878.169468 and Cluster-62878.169470 were identified as encoding UDP-arabinopyranose mutase 1, and their expression was increased to 6.36- and 5.21-fold, respectively, in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

4.2.6. Oxalate Oxidase

The relationships with oxalate oxidase suggest that HvOxOLP (for Hordeum vulgare oxalate oxidase-like protein) may be involved in hydrogen peroxide (H2O2) generation, which is essential, for example, for the cross-linking of cell wall components during the formation of papillae [72]. The genes Cluster-62878.374736, Cluster-62878.37656, Cluster-62878.390359 and Cluster-62878.479117 were identified as encoding oxalate oxidase 2, and their expression was increased to 12.30-, 6.19-, 22.16- and 6.15-fold, respectively, in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp. The level of PR15 (pathogenesis-related protein 15–oxalate oxidase) expression slightly increased at 24 hpi and further increased at 48 hpi (3-fold) in wheat leaves [73]. Oxalate oxidase (OxO) can metabolize oxalic acid (OA) to carbon dioxide (CO2) and H2O2. The degradation of OA during the early phase of fungal–host interactions can interfere with fungal infection and establishment processes [74]. The heterologous expression of wheat oxalate oxidase (WOxO) in various oilseed crops, such as soybean [75], sunflower [76] and rapeseed [77], has been reported to increase resistance to S. sclerotiorum [78]. A study demonstrated the potential ability of the barley oxalate oxidase (BOxO) gene to confer stable resistance against stem rot in the productive and highly susceptible Brassica juncea cv. Varuna under field conditions [74].

4.2.7. Mitogen-Activated Protein Kinase Kinase 1-like

Mitogen-activated protein kinase (MAPK) cascades play pivotal roles in signal transduction during adaptation to biotic and abiotic stresses in all eukaryotes. The genome of Arabidopsis encodes 20 MAPKs, 10 MAPK kinases (MAPKKs) and 60–80 MAPKK kinases (MAPKKKs) [79]. Several Arabidopsis MAPKs, MAPKKs and MAPKKKs are known to regulate disease resistance against phytopathogens via the production and signaling pathways of salicylic acid (SA), jasmonic acid (JA) and ethylene (ET), the three major plant hormones [80]. The gene Cluster-62878.170489 was identified as encoding mitogen-activated protein kinase kinase 1-like, and its expression increased to 157.59-fold in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

4.2.8. Tryptophan Decarboxylase

Tryptophan decarboxylase genes from Aegilops variabilis No. 1 (AeVTDC1 and AeVTDC2) were both induced by cereal cyst nematode juveniles at the early stage of the resistance response (30 h post-inoculation) [81]. Plant tryptophan decarboxylase (TDC, 4.1.1.28) catalyzes the formation of tryptamine from tryptophan (Trp). Tryptamine is a precursor for the biosynthesis of serotonin, indole alkaloids and indole acetic acid (IAA). The biological functions of TDCs have been documented in several plant–pathogen interactions. The TDC gene has been implicated in the red-light-induced resistance of rice to Bipolaris oryzae [82]. The gene Cluster-62878.256368 was identified as encoding a tryptophan decarboxylase, and its expression increased to 171.25-fold in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

4.2.9. Aromatic L-Amino Acid Decarboxylase

Aromatic L-amino acid decarboxylases (AADCs) catalyze the pyridoxal 5′-phosphate-dependent decarboxylation of select aromatic L-amino acids in plants, mammals and insects. Two plant AADCs, L-tryptophan decarboxylase (TDC) and L-tyrosine decarboxylase (TYDC), have attracted considerable attention because of their roles in the biosynthesis of pharmaceutically important monoterpenoid indole alkaloids and benzylisoquinoline alkaloids, respectively [83]. In plants, AADCs are involved in the biosynthesis of several types of secondary metabolites, which are defined as compounds that are not essential for normal growth and development but are often involved in key interactions between plants and their biotic and abiotic environments [83]. The gene Cluster-62878.389251 was identified as encoding a tryptophan decarboxylase, and its expression was increased to 154.34-fold in ‘Taihang’ leaves at 48 hpi after inoculation with Bgp.

5. Conclusions

In this study, we investigated the resistance mechanisms of different Poa pratensis varieties against powdery mildew caused by Bgp via transcriptomic analysis. Our results revealed that ‘Taihang’, a moderately resistant variety, presented significantly lower primary haustorium formation and a lower proportion of conidia with five germ tubes than the more susceptible varieties ‘Black Jack’ and ‘Explorer’. Furthermore, differential gene expression analysis revealed a significantly greater number of upregulated DEGs in ‘Taihang’, with 2843 specific DEGs playing a crucial role in disease resistance. Key resistance-related genes encoding chitinase, gamma-glutamyltranspeptidase 1, protein SAR DEFICIENT 1 isoform X1, dnaJ protein ERDJ3B, UDP-arabinopyranose mutase 1, oxalate oxidase 2, mitogen-activated protein kinase kinase 1-like, tryptophan decarboxylase and aromatic L-amino acid decarboxylase were proposed as candidate genes for resistance to Bgp in ‘Taihang’, and they could be studied as candidate genes for resistance to powdery mildew in P. pratensis. This research provides important insights into the molecular mechanisms of powdery mildew resistance in P. pratensis and provides a basis for future gene mining and molecular breeding aimed at improving disease resistance in this important turfgrass species.

Supplementary Materials

The following supporting information can be downloaded from https://www.mdpi.com/article/10.3390/agronomy14112543/s1, Table S1: Differentially expressed genes calculated via DESeq2; Table S2: Significantly enriched GO (Gene Ontology) categories; Table S3: Significantly enriched KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways.

Author Contributions

Y.L., Q.X., X.Z. and Z.X. designed the research. Z.X., Y.L., F.W., Y.Z. (Yumin Zhao) and H.Z. performed the research. Z.X., Y.L., P.G., L.H., Z.G., F.W., Y.Z. (Yining Zhang), Q.X. and X.Z. analyzed the data. Z.X., Y.L., Z.G., F.W. and Y.Z. (Yining Zhang) wrote the paper. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Doctoral Scientific Foundation of Shanxi Agricultural University (2020BQ74), the Scientific and Technological Innovation Program of Higher Education Institutions in Shanxi Province (2021L166), the Doctoral Scientific Foundation for Returned Scholars in Shanxi Province (SXBYKY2021023), the Research Project Supported by Shanxi Scholarship Council of China (No. 2022-097), the Shanxi Province Central Guide Local Science and Technology Development Fund (YDZJSX2022B006) and the Key Research and Development Program of Shanxi Province (202102140601006).

Data Availability Statement

Data is contained within the article or supplementary material.

Acknowledgments

We thank Beijing Rytway Seed Co., Ltd. and Beijing Clover Seed and Turf Co. for providing the seeds of the P. pratensis cultivars ‘Explorer’ and ‘Black Jack’.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agronomy 14 02543 g001
Figure 1. Symptoms of P. pratensis varieties with different degrees of resistance to powdery mildew for 9 days after Bgp inoculation. (a–c) Symptoms of powdery mildew after inoculation for 9 days in ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively.
Figure 1. Symptoms of P. pratensis varieties with different degrees of resistance to powdery mildew for 9 days after Bgp inoculation. (a–c) Symptoms of powdery mildew after inoculation for 9 days in ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively.
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Figure 2. The formation of haustoria at 24 hpi with Bgp in three P. pratensis varieties. Different lowercase letters indicate that there were significant differences among the proportions of conidia with haustoria or without haustoria in different varieties at the 0.05 significance level.
Figure 2. The formation of haustoria at 24 hpi with Bgp in three P. pratensis varieties. Different lowercase letters indicate that there were significant differences among the proportions of conidia with haustoria or without haustoria in different varieties at the 0.05 significance level.
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Figure 3. Representative graph of conidia with different germ tubes in P. pratensis at 48 hpi with Bgp. (a) There were only primary and appressorium germ tubes on the conidia. (b) In addition to the primary and secondary germ tubes, there was a third-level germ tube on the conidia. (c) In addition to the primary-, secondary- and third-level germ tubes, there was a fourth-level germ tube on the conidia. (d) In addition to the primary-, secondary-, third- and fourth-level germ tubes, there was a fifth-level germ tube on the conidia. PGT: primary germ tube; AGT: appressorium germ tube; GT: germ tube.
Figure 3. Representative graph of conidia with different germ tubes in P. pratensis at 48 hpi with Bgp. (a) There were only primary and appressorium germ tubes on the conidia. (b) In addition to the primary and secondary germ tubes, there was a third-level germ tube on the conidia. (c) In addition to the primary-, secondary- and third-level germ tubes, there was a fourth-level germ tube on the conidia. (d) In addition to the primary-, secondary-, third- and fourth-level germ tubes, there was a fifth-level germ tube on the conidia. PGT: primary germ tube; AGT: appressorium germ tube; GT: germ tube.
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Figure 4. The percentage of conidia with different germ tubes in P. pratensis at 48 hpi with Bgp. Different lowercase letters indicate that there were significant differences among the proportions of different formation conditions in different species at the 0.05 significance level.
Figure 4. The percentage of conidia with different germ tubes in P. pratensis at 48 hpi with Bgp. Different lowercase letters indicate that there were significant differences among the proportions of different formation conditions in different species at the 0.05 significance level.
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Figure 5. Volcano plots summarizing differentially expressed genes in the three P. pratensis varieties after inoculation with powdery mildew compared with the control. (a–c) Volcano plots 9 days after inoculation for ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively. Each red dot represents a gene.
Figure 5. Volcano plots summarizing differentially expressed genes in the three P. pratensis varieties after inoculation with powdery mildew compared with the control. (a–c) Volcano plots 9 days after inoculation for ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively. Each red dot represents a gene.
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Figure 6. Venn diagram of differentially expressed genes (DEGs) in the three P. pratensis varieties after inoculation with powdery mildew compared with the control.
Figure 6. Venn diagram of differentially expressed genes (DEGs) in the three P. pratensis varieties after inoculation with powdery mildew compared with the control.
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Figure 7. Overview of the functional enrichment of P. pratensis leaves in response to powdery mildew infection. Functional enrichment analysis was performed via clusterProfiler. (a–c) Significantly induced GO (gene ontology) categories (top 20 GOs) in ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively.
Figure 7. Overview of the functional enrichment of P. pratensis leaves in response to powdery mildew infection. Functional enrichment analysis was performed via clusterProfiler. (a–c) Significantly induced GO (gene ontology) categories (top 20 GOs) in ‘Explorer’, ‘Black Jack’ and ‘Taihang’, respectively.
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Figure 8. Differential expression of genes related to endochitinase activity, the regulation of the salicylic acid biosynthetic process, the pentose biosynthetic process, the response to the host immune response, the superoxide dismutase complex and glutathione transport. Heatmap depicting DEGs related to endochitinase activity (a), the regulation of the salicylic acid biosynthetic process (b), the pentose biosynthetic process (c), the response to the host immune response (d), the superoxide dismutase complex (e), and glutathione transport (f) in ‘Explorer’, ‘Black Jack’ and ‘Taihang’ after inoculation with powdery mildew compared with the control. Differentially expressed genes were annotated via the NR database. The expression values are presented as log2(fold change) values.
Figure 8. Differential expression of genes related to endochitinase activity, the regulation of the salicylic acid biosynthetic process, the pentose biosynthetic process, the response to the host immune response, the superoxide dismutase complex and glutathione transport. Heatmap depicting DEGs related to endochitinase activity (a), the regulation of the salicylic acid biosynthetic process (b), the pentose biosynthetic process (c), the response to the host immune response (d), the superoxide dismutase complex (e), and glutathione transport (f) in ‘Explorer’, ‘Black Jack’ and ‘Taihang’ after inoculation with powdery mildew compared with the control. Differentially expressed genes were annotated via the NR database. The expression values are presented as log2(fold change) values.
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Figure 9. Information on differentially expressed genes (DEGs) enriched in KEGG functions in the three P. pratensis varieties after inoculation with powdery mildew compared with the control.
Figure 9. Information on differentially expressed genes (DEGs) enriched in KEGG functions in the three P. pratensis varieties after inoculation with powdery mildew compared with the control.
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Figure 10. Correlation of RNA-seq and qRT-PCR data.
Figure 10. Correlation of RNA-seq and qRT-PCR data.
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Table 1. Primer sequence information for qRT-PCR.
Table 1. Primer sequence information for qRT-PCR.
Gene IDPrimers’ Sequence (5′ → 3′)
ActinTGTTGGATTCTGGTGATGGTGTC/AGGATGGCGTGCGGAAGG
Cluster-62878.283639TACTGCGACACCCGATACC/GCCGCTCCGTAGTTGTAGTT
Cluster-62878.257472CGAACACCTTGGCTACGATG/CAACCTTGCCACCTATGTCG
Cluster-62878.105450CAGATGATGAAGACGCCGC/TTCTACGACCATGGCAGCAA
Cluster-62878.209345GATTTTCGATAGGCTTGCGG/GCCCAGGACTTCTACGACA
Cluster-62878.304093CTGGACGAGGGCTACCTGA/CCGAGACGAGGAAGTGGAA
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MDPI and ACS Style

Xu, Z.; Guo, Z.; Wu, F.; Zhang, Y.; Zhao, Y.; Han, L.; Gao, P.; Zhu, H.; Xu, Q.; Zhao, X.; et al. Transcriptomic Analysis Reveals the Molecular Defense Mechanisms of Poa pratensis Against Powdery Mildew Fungus Blumeria graminis f. sp. Poae. Agronomy 2024, 14, 2543. https://doi.org/10.3390/agronomy14112543

AMA Style

Xu Z, Guo Z, Wu F, Zhang Y, Zhao Y, Han L, Gao P, Zhu H, Xu Q, Zhao X, et al. Transcriptomic Analysis Reveals the Molecular Defense Mechanisms of Poa pratensis Against Powdery Mildew Fungus Blumeria graminis f. sp. Poae. Agronomy. 2024; 14(11):2543. https://doi.org/10.3390/agronomy14112543

Chicago/Turabian Style

Xu, Zhiyu, Zhanchao Guo, Fan Wu, Yining Zhang, Yumin Zhao, Lingjuan Han, Peng Gao, Huisen Zhu, Qingfang Xu, Xiang Zhao, and et al. 2024. "Transcriptomic Analysis Reveals the Molecular Defense Mechanisms of Poa pratensis Against Powdery Mildew Fungus Blumeria graminis f. sp. Poae" Agronomy 14, no. 11: 2543. https://doi.org/10.3390/agronomy14112543

APA Style

Xu, Z., Guo, Z., Wu, F., Zhang, Y., Zhao, Y., Han, L., Gao, P., Zhu, H., Xu, Q., Zhao, X., & Liang, Y. (2024). Transcriptomic Analysis Reveals the Molecular Defense Mechanisms of Poa pratensis Against Powdery Mildew Fungus Blumeria graminis f. sp. Poae. Agronomy, 14(11), 2543. https://doi.org/10.3390/agronomy14112543

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