{"paper_id":"4d157d7f-3370-41ae-a58a-b2c5a5dc59fa","body_text":"Genome-wide identification of phospholipase D gene family in wheat reveals miRNA-regulated module underlying FHB 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 Genome-wide identification of phospholipase D gene family in wheat reveals miRNA-regulated module underlying FHB resistance Lalit Laxman Kharbikar, Arti Shanware, Piyush Ghoshe, Shweta Kishor Nandanwar, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7877570/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Phospholipase D (PLD)-mediated lipid signalling is a crucial component of plant defence responses. However, the PLD gene family remains poorly characterised in hexaploid wheat ( Triticum aestivum L.), particularly regarding its role in resistance to Fusarium head blight (FHB), a devastating fungal disease. This study identified 178 non-redundant PLD genes in the wheat genome and comprehensively analysed their phylogenetic relationships, conserved domains, chromosomal distribution, promoter cis-elements, and expression profiles under Fusarium graminearum infection. These PLDs were classified into C2-dependent, PX–PH, and uncharacterised types. Promoter analysis revealed stress- and hormone-responsive cis-elements, while expression profiling demonstrated genotype-dependent induction patterns, with several PLDs strongly upregulated in the resistant genotype. We experimentally validated that tae-miR160 targets specific TaPLD transcripts, revealing a post-transcriptional regulatory layer. Furthermore, polymorphic SSR markers were developed from PLD loci for potential use in marker-assisted breeding. This study provides the first evidence of a miRNA–PLD regulatory network in wheat defence and highlights PLDs as critical mediators of FHB resistance. Wheat phospholipase D Fusarium head blight miRNA lipid signalling SSR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Key Message PLD gene family analysis in wheat uncovers a miRNA–PLD regulatory module that modulates Fusarium head blight resistance, providing molecular tools for breeding resistant cultivars. Introduction Wheat ( Triticum aestivum L.) is one of the most important staple crops worldwide, providing nearly 20% of the global caloric intake and sustaining billions of people as a primary food source (Dweba et al. 2017). However, wheat production faces growing challenges from both abiotic and biotic stresses, which collectively undermine yield, quality, and food security. Among these threats, Fusarium head blight (FHB), caused predominantly by Fusarium graminearum , remains one of the most destructive fungal diseases of wheat. FHB epidemics reduce grain yield and quality while contaminating harvested kernels with mycotoxins such as deoxynivalenol (DON), which pose serious risks to human and animal health (Alisaac and Mahlein 2023; Giedrojć et al. 2025). The global burden of FHB has intensified in recent decades, with climate change further exacerbating its incidence by creating favourable conditions of humidity and warmth for pathogen proliferation (González-Mendoza et al. 2021). Traditional breeding efforts have introduced moderate resistance in some wheat cultivars, but resistance is quantitative and polygenic, with no single source providing complete protection (Canonne et al. 2011). Therefore, an improved understanding of the molecular and regulatory mechanisms underlying wheat immunity is essential for developing novel genetic and biotechnological strategies to combat FHB. Lipids and their metabolites play pivotal roles in plant growth, development, and responses to environmental stresses. Phospholipases, enzymes that hydrolyse membrane phospholipids, have emerged as central players in stress signalling, as they generate lipid-derived second messengers that activate downstream defence pathways (Deepika and Singh 2022). In particular, phospholipase D (PLD; EC 3.1.4.4) catalyses the hydrolysis of structural phospholipids to produce phosphatidic acid (PA), a versatile signalling molecule involved in membrane dynamics, vesicle trafficking, cytoskeletal organisation, programmed cell death, and hormone responses (Zhang et al. 2004; Testerink and Munnik 2005; Wang et al. 2006). PA also acts as a docking site for protein kinases and phosphatases, thereby integrating lipid metabolism with cellular signalling networks (Li et al. 2009). Functional studies in Arabidopsis and rice have demonstrated the roles of PLDs in drought tolerance, salt stress adaptation, and pathogen defence. For example, PLDα1 and PLDδ in Arabidopsis regulate abscisic acid (ABA) signalling, stomatal closure, and reactive oxygen species generation (Qin and Wang 2002a; Zhang et al. 2004). In rice, PLDs have been implicated in the regulation of blast resistance and drought stress adaptation (Zhao et al. 2010a). Tomato PLDs modulate lipid signalling during fruit development and pathogen challenge (Guo et al. 2024). These studies highlight the importance of PLDs as molecular switches that coordinate developmental and defence processes. Despite this knowledge, the PLD gene family remains poorly characterised in wheat, a hexaploid species with a large, complex genome. Previous genome-wide studies have catalogued PLDs in model plants and some crops, but no systematic analysis has addressed their roles in wheat, especially in relation to FHB. The integration of PLDs into stress-responsive transcriptional networks, their regulation by transcription factors (TFs), and their post-transcriptional modulation by microRNAs (miRNAs) are virtually unexplored in wheat. miRNAs are short, non-coding RNAs that fine-tune gene expression through sequence-specific cleavage or translational repression (Duan et al. 2015). Several studies have reported the involvement of miRNAs in wheat responses to drought, salinity, and pathogen attack (Hao et al. 2022), but their regulation of PLDs remains to be demonstrated. Given the central role of PLDs in lipid-mediated stress signalling and the urgent need to understand molecular mechanisms of FHB defence, we undertook a comprehensive genome-wide characterisation of the PLD gene family in wheat. We identified 178 non-redundant PLDs and classified them based on their domain organisation, phylogenetic relationships, and structural features. We analysed their physicochemical properties, chromosomal distribution, exon–intron structures, conserved motifs, cis-regulatory elements, and predicted TF regulators. We also examined their post-transcriptional regulation by wheat miRNAs, validated miRNA–PLD interactions experimentally using multiplex PCR and semi-quantitative RT-PCR, and profiled their expression in resistant and susceptible genotypes under FHB infection using RNA-seq. Finally, we mined simple sequence repeat (SSR) markers from PLD loci, providing tools for genetic mapping and breeding. This integrative study represents the first systematic attempt to link wheat PLDs to FHB defence. By combining computational, transcriptomic, and experimental approaches, we reveal the structural, regulatory, and functional complexity of wheat PLDs, and establish a miRNA–TF–PLD signalling axis that underpins resistance. Our findings not only expand fundamental understanding of lipid-mediated defence signalling in cereals but also provide practical molecular tools for breeding FHB-resistant wheat cultivars. Materials and Methods Identification of PLD genes in wheat Protein sequences of wheat ( Triticum aestivum L.) were retrieved from the Phytozome v13 and NCBI databases. To ensure comprehensive coverage, both annotated and uncharacterised proteins were included. Initial filtering for PLD domains was performed using Pfam ( http://pfam.xfam.org ) and the Conserved Domain Database (CDD; https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml ). A total of 331 candidate PLDs were identified. Redundant sequences were removed by aligning proteins with Jalview v2.11.2.6 at a 95% identity threshold, resulting in 178 non-redundant PLDs for downstream analysis. Physicochemical properties and subcellular localisation The amino acid length, molecular weight, theoretical isoelectric point (pI), instability index, aliphatic index, and grand average of hydropathicity (GRAVY) were calculated using ProtParam ( https://web.expasy.org/protparam/ ). Subcellular localisation was predicted using Plant-mPLoc ( http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/ ), which integrates sequence-based and annotation-based prediction. Domain, motif, and secondary structure analysis Conserved domains were confirmed using Pfam and CDD. Motifs were predicted with MEME Suite v5.4.1 ( http://meme-suite.org ), with maximum motifs set to 15. Specific motif scans for HKD (HxKxxxxD) and IYIENQFF were conducted using FIMO. Secondary structures were predicted using SOPMA ( https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html ), with parameters set at 70% window size and default thresholds. Homology modelling and structural evaluation (dup: abstract ?) Representative PLDs from PI-independent, PIP2-dependent, and PIP2-independent subgroups were modelled using SWISS-MODEL ( https://swissmodel.expasy.org ). Structural quality was assessed using Global Model Quality Estimation (GMQE), QMEANDisCo scores, and Ramachandran plots (PROCHECK). Structural visualisation was performed using PyMOL v2.5. Phylogenetic and gene structure analysis Multiple sequence alignment of wheat PLDs was conducted using MUSCLE in ETE3. Phylogenetic trees were constructed with the neighbour-joining method and 1,000 bootstrap replicates, and visualised with iTOL v6. Gene structures, including exon–intron organisation, were analysed with GSDS v2.0 ( http://gsds.cbi.pku.edu.cn ). Chromosomal distribution Chromosomal mapping of PLD genes was performed using the IWGSC RefSeq v1.1 wheat genome assembly available at Wheatomics ( http://202.194.139.32/wheatomics/ ). Gene coordinates were extracted, and physical locations visualised with TBtools v2.003. Cis-regulatory element and transcription factor prediction Promoter sequences (2 kb upstream of the start codon) were retrieved from the wheat genome and analysed for cis-regulatory elements using PlantCARE ( http://bioinformatics.psb.ugent.be/webtools/plantcare/ ). Putative transcription factors (TFs) associated with PLDs were predicted using PlantTFDB v5.0 ( http://planttfdb.gao-lab.org ). Tandem repeat and SSR marker analysis Tandem repeats within PLDs were detected using Tandem Repeats Finder ( https://tandem.bu.edu/trf/trf.html ). SSRs were identified using BatchPrimer3 v1.0 ( https://wheat.pw.usda.gov/demos/BatchPrimer3 ), and primers were designed with default parameters. e-PCR validation was performed in silico using TBtools to assess amplification across the PLD family. miRNA prediction and interaction network analysis Wheat miRNAs targeting PLDs were predicted using psRNATarget ( https://www.zhaolab.org/psRNATarget/ ). Predicted interactions were filtered by penalty score (< 3). Interaction networks were visualised in Cytoscape v3.9.1. Gene Ontology and KEGG Pathway Analysis for Functional Annotation. PLD gene ontology terms in the wheat genome were identified using Blast2Go software, which gave us detailed protein insights. The GO terms were subsequently classified according to their roles, encompassing cellular components, biological processes, and molecular functions. Furthermore, Blast2Go analysis leveraging the KEGG database, demonstrated PLD's involvement in metabolic pathways. Expression profiling using RNA-seq RNA-seq data from PRJEB24686 were downloaded from the European Nucleotide Archive. Clean reads were mapped to the IWGSC RefSeq v1.1 genome. Transcript abundance was quantified in TPM and log₂-transformed. Expression heatmaps, principal component analysis (PCA), and hierarchical clustering dendrograms were generated with TBtools. Plant material and pathogen inoculation Two wheat ( Triticum aestivum L.) genotypes, PBW 343 (Fusarium head blight-resistant) and HD 2967 (susceptible), were used for experimental validation. Seeds of both cultivars were procured from the Division of Genetics, ICAR–Indian Agricultural Research Institute (IARI), New Delhi, India . Plants were grown in pots containing sterilised soil:sand:FYM (2:1:1) under controlled conditions (22°C, 16 h light/8 h dark photoperiod). At anthesis, spikes were inoculated with Fusarium graminearum isolate FgMS-1 (ITCC No. 3437) , originally obtained from naturally infected wheat spikes from the Indo-Gangetic plains and maintained in the Indian Type Culture Collection, ICAR–IARI, New Delhi, India . The pathogen was cultured on potato dextrose agar (PDA) plates for 5 days at 25°C, and conidial suspensions were prepared in sterile distilled water containing 0.01% Tween-20. Conidia concentration was adjusted to 1 × 10⁵ conidia mL⁻¹ using a haemocytometer. Inoculations were performed by the point-inoculation method , in which 10 µL of conidial suspension was injected into a central floret of each spike. Control spikes were mock-inoculated with sterile water. Spikes were harvested at 48 h post-inoculation (hpi) for RNA extraction and downstream analyses. Multiplex PCR and semi-quantitative RT-PCR validation In silico mapping identified a putative tae-miR160 complementary binding site within the 5′ UTR-proximal region of the TaPLD transcript, as described in the Results section detailing the experimental validation of PLD–miRNA interactions. Two gene-specific primers, Primer 1: TaPLD-miR160-F (forward) and Primer 2: TaPLD-miR160-R (reverse), were designed flanking this region to enable amplification and subsequent validation of the predicted interaction. Total RNA was extracted using TRIzol™ reagent (Invitrogen, USA) and reverse transcribed with the RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, USA). Multiplex PCR was performed using miRNA- and TaPLD -specific primers. Semi-quantitative RT-PCR was conducted under the following conditions: 95°C for 5 min , followed by 30 cycles of 95°C for 30 s , 58°C for 30 s , and 72°C for 30 s , with a final extension at 72°C for 7 min . PCR products were resolved on 1.5% agarose gels stained with ethidium bromide (0.5 µg mL⁻¹) and visualised under UV light using a gel documentation system. Results Identification and classification of wheat PLD genes A total of 178 non-redundant PLD proteins were identified in the wheat genome following removal of redundancy from an initial set of 331 candidates. Based on domain composition, these PLDs were classified into three types: 147 C2-dependent (PLDc, PLDc_2, PLD_C, and C2 domains), 18 PX-PH (PH domain), and 13 uncharacterised isoforms (PLDc_N domain) (Supplementary Table S1 ). C2-dependent PLDs contained typical C2 domains involved in Ca²⁺ binding and lipid interaction, while PX-PH PLDs carried Phox homology (PX) and Pleckstrin homology (PH) domains implicated in membrane targeting. The uncharacterised group lacked canonical domains, suggesting structural divergence. The physicochemical properties of representative wheat PLDs are summarised in Table 1 (See Supplementary Table S2 for full details). Amino acid lengths ranged from 65 to 1131 aa, and molecular weights varied from 7.1 to 123 kDa. The instability indices (< 50) indicated stable proteins, while high aliphatic indices (> 70) suggested thermostability. Grand average of hydropathicity (GRAVY) values were near neutral, reflecting hydrophilicity. Subcellular localisation predictions placed C2 PLDs primarily in the endoplasmic reticulum, chloroplasts, and vacuoles; PX-PH PLDs in the cytoplasm and nucleus; and uncharacterised PLDs in plasma membranes or mitochondria. Table 1 Summary of physicochemical properties of representative wheat phospholipase D (PLD) proteins Property Range observed Representative values Interpretation Amino acid length (aa) 65–1131 Short: 163; Medium: 525; Long: 1131 Wide size variation across isoforms Molecular weight (kDa) 7.1–123 Small: 17.8; Medium: 60.1; Large: 123.2 Includes truncated and full-length PLDs Isoelectric point (pI) 4.05–11.7 Acidic: 5.7; Neutral: 6.8; Basic: 8.9 Distribution across acidic–basic range Instability index 27–49 Mostly < 50 Proteins predicted to be stable Aliphatic index 63–108 Typically, > 70 Indicative of thermostability GRAVY (hydropathicity) -0.86 – +0.40 Near 0 (avg. -0.35) Reflects overall hydrophilicity Subcellular localisation Multiple compartments Chloroplast, cytoplasm, vacuole, ER, nucleus Suggests multifunctional roles Domain architecture, motifs, and structural features Conserved domain analysis revealed six major domains across the PLDs: C2, PLDc, PLDc_2, PLDc_N, PLD_C, and PH (Fig. 1 ; Supplementary Tables S1 and S3). C2 PLDs contained two HKD (HxKxxxxD) catalytic domains, characteristic of phospholipase activity. PX-PH PLDs possessed domains for phosphoinositide binding, while uncharacterised PLDs lacked HKD or IYIENQFF domains. Motif analysis revealed strong conservation of key catalytic motifs across the wheat PLD family. Specifically, the canonical HKD motif, essential for enzymatic activity, was detected in 144 out of 178 PLDs, while the IYIENQFF motif, another highly conserved signature, was present in 129 PLDs (Fig. 2 ; Supplementary Table S4). By contrast, uncharacterised PLD isoforms were generally deficient in these motifs. A comprehensive scan of conserved motifs identified 165 distinct motifs distributed across 178 PLD protein sequences (Fig. 2 A). Within this repertoire, 60 PLDs contained a single HKD motif, 84 harboured two HKD motifs, and two unique isoforms encoded three distinct HKD motifs. Detailed information on the HKD motif sequences, their positions, and distribution across PLD clusters is presented in Supplementary Table S4 and visually illustrated in Fig. 2 B. Secondary structure analysis revealed that random coils dominated the predicted architecture of wheat PLDs, accounting for ~ 45–65% of residues across isoforms (Fig. 3 ; Table 2 ). Extended β-strands were the second most prevalent feature (20–27%), followed by α-helices (8–16%). Class-specific profiles highlighted distinct structural tendencies (Table 2 ). PI-independent PLDs contained 16.44% α-helices, 27.24% extended β-strands, 9.89% β-turns, and 46.44% random coils. PIP2-dependent PLDs exhibited markedly reduced α-helical (8.85%) and β-turn (6.23%) content but were enriched in random coils (63.96%), consistent with greater conformational flexibility. By contrast, PIP2-independent PLDs showed an intermediate composition with 16.03% α-helices, 20.40% extended β-strands, 8.07% β-turns, and 55.49% random coils. Table 2 Secondary structure content (%) of PI independent, PIP2 dependent, and PIP2 independent proteins Secondary Structure Symbol PI Independent PIP2 Dependent PIP2 Independent Alpha Helix (Hh) 16.44% 8.85% 16.03% 310 Helix (Gg) 0.00% 0.00% 0.00% Pi Helix (Ii) 0.00% 0.00% 0.00% Beta Bridge (Bb) 0.00% 0.00% 0.00% Extended Strand (Ee) 27.24% 20.96% 20.40% Beta Turn (Tt) 9.89% 6.23% 8.07% Bend Region (Ss) 0.00% 0.00% 0.00% Random Coil (Cc) 46.44% 63.96% 55.49% Ambiguous Status (?) 0.00% 0.00% 0.00% Other States – 0.00% 0.00% 0.00% Homology modelling and structural evaluation To assess the structural basis of functional divergence among wheat PLDs, representative isoforms from the three major subgroups, PI-independent, PIP2-dependent and, PIP2-independent were subjected to comparative homology modelling followed by validation. Reliable 3D structures were generated for PI-independent and PIP2-dependent isoforms, with GMQE scores ranging from 0.15 to 0.55 and QMEANDisCo values between 0.26 and 0.52, indicating moderate to good model quality. Validation with Ramachandran plots demonstrated that more than 88% of residues fell within the most favoured regions, while only a minor fraction occupied allowed or disallowed regions. This confirms that the predicted models are structurally robust and stereochemically sound (Fig. 4 ). These results provide confidence in using the models to interpret functional divergence in substrate binding, membrane anchoring, and catalytic flexibility. For the PI-independent PLD, four candidate templates were identified, with phospholipase D alpha 1 (25% identity) providing the most reliable model. This structure, resolved at 2.29 Å, was monomeric and bound both Ca²⁺ and 1,2-dioctanoyl-sn-glycero-3-phosphate, reflecting its potential regulatory complexity. The model achieved a GMQE score of 0.55 and a QMEANDisCo score of 0.52 ± 0.05, with 88% of residues in favoured Ramachandran regions (Fig. 4 A). For the PIP2-dependent PLD, two models were generated, with the phospholipase D alpha 1 template (17% identity) providing the best coverage. The resulting model, resolved at 1.80 Å, was monomeric and carried a Ca²⁺ ligand, consistent with calcium-mediated regulation. Quality indices (GMQE 0.15; QMEANDisCo 0.45 ± 0.05) indicated moderate reliability, while the Ramachandran plot placed 88% of residues in favoured regions, just below the ideal 90% benchmark (Fig. 4 B). For the PIP2-independent PLD, the best-fitting model was derived from Protein BAS0735 of unknown function (29% identity). The predicted structure (resolution: 2.90 Å) was also monomeric. Although the GMQE score was low (0.00), the QMEANDisCo score (0.26 ± 0.12) and Ramachandran geometry (94% favoured residues) supported the stereochemical validity of the fold (Fig. 4 C). A direct comparison of these models (Table 3 ) highlighted that, despite relatively low sequence identities to known templates, all three PLDs adopted robust monomeric folds and retained ligand-binding features. While the PIP2-independent PLD showed the best stereochemical geometry, the PI-independent PLD achieved the most balanced combination of GMQE, QMEANDisCo, and ligand complexity, suggesting it may play a particularly versatile role in lipid signalling. Table 3 Homology modelling and structural validation of representative wheat PLD subgroups PLD subgroup Template (best hit) Sequence identity (%) Resolution (Å) Oligomeric state Ligands GMQE QMEANDisCo (± SD) Ramachandran favoured (%) Interpretation PI-independent Phospholipase D α1 25.32 2.29 Monomer Ca²⁺, PA* 0.55 0.52 ± 0.05 88.07 Reliable model, supported by ligand binding PIP2-independent Protein BAS0735 (uncharacterised) 29.41 2.90 Monomer None 0.00 0.26 ± 0.12 93.75 Strong geometry; low GMQE from weak template PIP2-dependent Phospholipase D α1 16.93 1.80 Monomer Ca²⁺ 0.15 0.45 ± 0.05 88.01 Acceptable model, near 90% validation cut-off *PA: 1,2-dioctanoyl-sn-glycero-3-phosphate. Phylogenetic analysis and gene structures A maximum-likelihood phylogenetic tree, constructed using representative isoforms from all three wheat subgenomes (A, B, and D), resolved the 178 PLDs into three major classes: C2-type, PX–PH-type, and an unclassified group, each further divided into distinct clades (Fig. 5 ). Within the C2-type class, three subgroups were observed. The PIP2-dependent PLDs (light green and brown branches) formed a compact cluster with short branch lengths, consistent with high sequence conservation. The PIP2-independent PLDs (pink, light blue, yellow, and purple branches) exhibited greater branching heterogeneity, accompanied by relatively weaker bootstrap support. The third subgroup, PI-independent PLDs (dark blue branches), was resolved as a distinct clade separate from the other C2-type members. The PX–PH-type PLDs (red branches), corresponding to Ca²⁺-independent isoforms lacking the canonical C2 domain, formed a smaller but well-supported clade that displayed relatively long branch lengths. The unclassified group (dark green branches) comprised PLDs that did not consistently cluster within the canonical clades. Several members of this group showed deviations in conserved HKD catalytic motifs or domain composition, and their placement remained basal in the tree. Exon–intron structure analysis revealed considerable variability among wheat PLD isoforms (Fig. 6 ). C2-type PLDs, the most prevalent subgroup, contained between 1 and 10 exons and spanned 2.5–9.5 kb, representing the smallest exon range among the PLD classes. PX–PH-type PLDs displayed greater structural variability, extending over 14–16 kb and comprising 5–19 exons. In contrast, unclassified PLDs were generally smaller, ranging from 6 to 8 kb with 3–6 exons. Despite broad similarities in motif type, length, and distribution across subgroups, exon number and size were clearly divergent. Chromosomal distribution Chromosomal mapping placed the 178 wheat PLD genes across six of the seven homoeologous groups, with no members detected on chromosome 2 (Fig. 7 ). PX–PH-type PLDs were exclusively restricted to chromosome 1 (1A, 1B, 1D), indicating a lineage-specific expansion that has not been reported for lipid signalling genes in other cereals. By contrast, C2-type PLDs displayed a broader distribution: PI-independent isoforms were located on chromosomes 1, 3, 4, 5, and 7, with chromosome 3 harbouring only this subtype, whereas PIP2-dependent members were confined to chromosomes 1, 4, 5, and 7. PIP2-independent PLDs exhibited a more clustered arrangement, being restricted to chromosomes 4, 5, and 6, with chromosome 4A uniquely containing only PIP2-independent isoforms. Uncharacterised PLDs showed a narrow distribution, restricted to chromosomes 5B and 6 (6A, 6B, 6D). Overall, chromosomes 5 and 6 displayed the highest density of PLDs, including C2-type, PIP2-independent, and uncharacterised subgroups, highlighting hotspots of duplication and diversification. Cis-regulatory elements and transcription factor associations Promoter analysis of wheat PLDs identified a wide range of cis-regulatory elements in the 2 kb upstream regions (Fig. 8 ; Supplementary Table S5). Core motifs such as the TATA-box and CAAT-box were detected across nearly all isoforms, confirming competence for basal transcription. In addition, promoters contained hormone- and stress-responsive elements, including CGTCA and TGACG motifs (methyl jasmonate), ABRE (abscisic acid), and ARE (anaerobic induction), pointing to regulation by multiple signalling pathways. In total, 45 functionally annotated cis-elements were identified, categorized into five groups: (i) light-responsive elements, (ii) hormone-responsive motifs, (iii) stress-related motifs, (iv) transcription factor–binding sites, and (v) other regulatory motifs (Fig. 8 ). Elements lacking annotation or of uncertain function were excluded. Complementary analysis of predicted transcription factor binding sites revealed strong associations with five major TF families (q < 0.005), BBR-BPC, C2H2 zinc-finger, ERF, LBD, and MYB (Fig. 9 ; Supplementary Table S6). Among these, C2H2 zinc-finger and ERF TFs were ubiquitous across all PLD types. In contrast, LBD and MYB TFs showed subgroup-specific enrichment, occurring predominantly in PI-independent and PIP2-dependent PLDs, whereas BBR-BPC and MYB were enriched in the PIP2-independent group, with LBD uniquely associated with PX–PH-type PLDs. Tandem repeats and SSR markers Analysis of the wheat PLD family revealed that 19 out of 178 isoforms contained tandem repeats (Fig. 10 ; Supplementary Table S7). Of these 19, however, 10 belonged to the uncharacterised group lacking the conserved HKD catalytic motif and were excluded from functional interpretation. Among the retained isoforms, TaPLD-1A-1Gam1 and TaPLD-1D-1Gam1 each harboured seven repeats, while TaPLD-1B-1Gam1 contained five repeats. Additional duplications were detected in TaPLD-4B-2Alp1 and TaPLD-4D-2Alp2 (two repeats each), whereas TaPLD-4B-Ams1, TaPLD-4B-Ams2, TaPLD-5D-Del8, and TaPLD-7D-2Alp1 each contained single tandem duplications. Thermodynamic evaluation using enthalpy plots indicated that TaPLD-5D-Del8 and TaPLD-7D-2Alp1 exhibited particularly favourable repeat stability, with enthalpy values close to 1.0, suggestive of enhanced structural robustness (Fig. 10 ). Mining of simple sequence repeats (SSRs) across the wheat PLD family yielded a total of 161 primer pairs (Table 2 ; Supplementary Tables S8). Most PLD sequences carried a single patterned pair of SSRs. Among these, 33 primer pairs showed > 50% GC content in both forward and reverse primers, which were selected for further Electronic-PCR (E-PCR) analysis. E-PCR validation demonstrated that 30 primer sets successfully amplified 108 of the 178 PLD sequences, with product sizes ranging from 481 to 780 bp. Analysis of SSR motifs using the TBtools SSRMiner tool revealed a diversity of repeat types, including trinucleotide SSRs (TNRs) across 15 loci (Table 4 ). The number of repeats varied between 5 and 11 per locus, highlighting the polymorphic nature of these SSRs. Table 4 SSR tandem repeat motifs identified in TaPLD genes Sequence Start End Motif Nucleotides (bp) No. of Repeats A-genome PLDs TaPLD-1A-13 132 147 GAGGAGGAGGAGGAG 3 5 TaPLD-1A-1Zet1 88 103 CCTCCTCCTCCTCCT 3 5 TaPLD-6A-N1 251 275 CGGCGGCGGCGGCGGCGGCGGCGG 3 8 TaPLD-6A-N2 269 293 CGGCGGCGGCGGCGGCGGCGGCGG 3 8 TaPLD-6A-Del1 189 213 AGGAGGAGGAGGAGGAGGAGGAGG 3 8 B-genome PLDs TaPLD-1B-P1 37 52 CCTCCTCCTCCTCCT 3 5 TaPLD-6B-Del2 188 206 GAGGAGGAGGAGGAGGAG 3 6 TaPLD-6B-Del2 571 586 CCTCCTCCTCCTCCT 3 5 D-genome PLDs TaPLD-4D-1Gam1 156 180 GCCGCCGCCGCCGCCGCCGCCGCC 3 8 TaPLD-5D-Del8 177 192 AAGAAGAAGAAGAAG 3 5 TaPLD-5D-Del8 461 485 CCACCACCACCACCACCACCACCA 3 8 TaPLD-5D-1Alp1 28 46 CCGCCGCCGCCGCCGCCG 3 6 TaPLD-6D-N1 248 281 CGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGG 3 11 TaPLD-6D-Del1 189 210 AGGAGGAGGAGGAGGAGGAGG 3 7 TaPLD-7D-Pr1 15 30 AGGAGGAGGAGGAGG 3 5 miRNA–PLD interaction networks Two wheat miRNAs, tae-miR9664-3p and tae-miR160, were identified as regulators of five PLD isoforms: TaPLD-4B-1Bet1 , TaPLD-4D-1Gam1 , TaPLD-5A-1Bet1 , TaPLD-3A-1 , and TaPLD-3B-1 (Fig. 11 ; Supplementary Table S9). These isoforms were distributed across chromosomes 3A, 3B, 4B, 4D, and 5A, highlighting widespread regulatory integration across wheat subgenomes. Both miRNAs exhibited strong complementarity with functional domains of the PLD transcripts, consistent with cleavage-based post-transcriptional regulation. Network visualization in Cytoscape revealed distinct regulatory associations: tae-miR9664-3p predominantly targeted PLDs located on chromosomes 4B, 4D, and 5A, whereas tae-miR160 specifically targeted PLDs encoded on chromosomes 3A and 3B. These associations were represented in compact regulatory networks, illustrating direct PLD–miRNA interactions relevant to stress signalling pathways. Functional annotation Blast2GO analysis revealed enrichment of multiple functional categories across PLD isoforms (Supplementary Table S10). For C2-type PLDs, six major GO terms were identified: catalytic activity (GO:003824), lipid metabolic process (GO:0006629), hydroxylase activity (GO:0016787), plasma membrane localisation (GO:0005886), programmed cell death (GO:0012501), and signalling activity (GO:0023052). PX–PH type PLDs shared four of these terms with the C2 group, GO:0006629, GO:0016787, GO:0005886, and GO:0023052, indicating overlapping roles in lipid processing and membrane-associated signalling, while lacking enrichment in programmed cell death and catalytic GO terms. Further, the GO terms were categorised into molecular function, biological process, and cellular component ontologies (Fig. 12 ). Molecular functions were dominated by catalytic and hydroxylase activities, biological processes were enriched in lipid metabolic and signalling functions, and cellular components were primarily associated with plasma membrane localisation. KEGG pathway analysis further reinforced the functional roles of wheat PLD isoforms by mapping their associations with lipid metabolism, particularly glycerophospholipid and ether lipid pathways central to lipid-derived signalling under stress conditions (Fig. 13 ). In the glycerophospholipid metabolism pathway (Fig. 13 A), PLDs were implicated in critical phospholipid turnover processes. Notably, the enzymatic hydrolysis of phosphatidylethanolamine and phosphatidylcholine into 1,2-diacyl-sn-glycerol-3P was highlighted, underscoring the generation of diacylglycerol (DAG) as a key intermediate in lipid signalling and membrane remodelling. The ether lipid metabolism pathway (Fig. 13 B) further demonstrated the contribution of PLDs in the cleavage of plasmenylethanolamine to yield plasmenic acid , a reaction that connects ether lipid dynamics with membrane restructuring. Expression profiling in resistant and susceptible genotypes Expression profiling revealed that wheat PLD isoforms exhibit distinct tissue-specific and genotype-dependent expression patterns (Fig. 14 ), suggesting specialized functional roles. Hierarchical clustering of differentially expressed isoforms under Fusarium graminearum inoculation resolved the 40 PLDs into four major expression groups (A–D), reflecting class-specific dynamics. Group A isoforms, including TaPLD-5B- ( 15 – 19 ), TaPLD-7A- ( 5 – 6 ), and TaPLD-1D-1Gam1 , exhibited broad upregulation across the tissues under stress conditions. Their generalized induction pattern indicates a role in maintaining basal stress responsiveness. Group B isoforms, such as TaPLD-1A- ( 1 – 2 ) and TaPLD-5B- ( 3 – 14 ), showed moderate, tissue-specific induction in rachis and spikes, suggesting contributions to localized defense signaling. Group C members, including TaPLD-6D-N- ( 1 – 4 ) and TaPLD-1A-1Gam1 , were characterized by strong spikelet-enriched expression, with moderate modulation depending on genotype, indicative of conditional stress-responsive regulation. In contrast, Group D isoforms, such as TaPLD-7D-2Alp2 , TaPLD-4A- ( 1 – 4 ), and TaPLD-5D-Del- ( 1 – 5 ), displayed sharp genotype-dependent induction, with resistant cultivars showing pronounced upregulation while susceptible genotypes exhibited weak or no induction. These findings point to the adaptive recruitment of PLDs in resistance signaling. Comparative expression analysis under F. graminearum infection further highlighted a subset of isoforms that were specifically induced in resistant genotype but remained unchanged or suppressed in susceptible genotype (Fig. 14 ), consistent with their conditional activation and genotype-dependent regulation. Overall, the results demonstrated that wheat PLDs are hierarchically organized into coordinated expression modules that integrate tissue-specific functions with inducible defense responses. Experimental validation of PLD–miRNA interactions Computational analysis predicted a potential binding site for tae-miR160 within the 5′ UTR–proximal region of the TaPLD transcript, characterized by complementary base pairing (Fig. 15 A). A two-amplicon multiplex PCR assay was designed to simultaneously amplify a representative PLD fragment and a stress-responsive miRNA (tae-miR160) from wheat tissues. Distinct dual amplicons were observed in both resistant and susceptible genotypes (Fig. 15 B). Strict controls ensured assay specificity; Milli-Q water (-C), primer (+ CP) and DNA (+ CD) controls yielded no signals. These results demonstrate infection-dependent co-accumulation of PLD and miRNA transcripts, providing wet-lab evidence supporting in silico-predicted PLD–miRNA interactions. To further examine PLD–miRNA regulation, semi-quantitative RT-PCR with PLD-specific miRNA-primed (Fig. 15 A) reactions was carried out, revealing genotype-dependent expression dynamics. Following infection, TaPLD transcripts were markedly repressed in the susceptible genotype HD 2967, while expression remained stable or slightly elevated in the resistant genotype PBW 343 (Fig. 15 C). Densitometric normalization against actin confirmed this infection-dependent repression in susceptible genotypes, consistent with transcriptomic clustering patterns (particularly Group D) identified from RNA-seq data. Discussion This study provides the first comprehensive characterisation of the phospholipase D (PLD) gene family in wheat and establishes their roles in defence against Fusarium graminearum , the causal agent of Fusarium head blight (FHB). By integrating genome-wide identification, structural and regulatory analyses, expression profiling, and experimental validation, we uncovered a dynamic miRNA–TF–PLD signalling axis central to wheat immunity. Identification and classification of wheat PLD genes The members of PLD identified in wheat were categorized into three types, including a notable group of uncharacterized members that do not possess canonical catalytic domains. This classification aligns with findings from other cereal species, where the architecture of protein domains and the conservation of sequences help define PLD clades (Zhao et al., 2010a; Hong et al., 2016). The significant abundance of PLDs in wheat, surpassing the number found in many other plant species (Qin and Wang, 2002; Zhao et al., 2012; Guo et al., 2024), underscores the remarkable complexity of the wheat genome. This abundance also suggests a potentially greater functional diversification of PLDs within cereals, emphasizing their significance in plant biology and adaptations. The physicochemical profiling of various isoforms demonstrated significant variations in amino acid length and molecular weight, highlighting the complexity of these proteins. Notably, the PX-PH type PLDs exhibited longer average chain lengths of around 700 amino acids, leading to correspondingly higher molecular weights. Isoelectric point (pI) analyses revealed that PX-PH PLDs typically cluster around neutral pH, while many uncharacterized PLDs have more alkaline pI values. This intriguing variation suggested functional differences in subcellular activities and protein–protein interactions, emphasizing the need for further exploration. Importantly, the instability indices indicated that all PLDs are stable under physiological conditions (Gasteiger et al., 2005), while high aliphatic indices suggested strong thermostability and GRAVY values near zero pointed to a hydrophilic nature. This unique combination of stability, thermostability, and hydrophilicity positions these PLDs as highly adaptable, capable of functioning efficiently in diverse cellular compartments. Indeed, predictions about their subcellular localization suggested their presence in critical areas such as the cytoplasm, vacuole, endoplasmic reticulum, chloroplast, nucleus, peroxisome, plasma membrane, and other organelles. This extensive localization underscores the multifunctional roles of PLDs in mediating stress responses, enhancing membrane dynamics, and facilitating signal transduction (Li et al., 2009; Testerink and Munnik, 2011). Such multifaceted capabilities make PLDs essential players in cellular processes and highlight their importance in biological systems. These properties are consistent with analogous findings from other plant species. For example, in Corchorus spp., PLDs were reported with aliphatic indices in the range 71–87, negative GRAVY values (i.e. hydrophilic), and instability indices indicating stable proteins in both C. capsularis and C. olitorius (Islam et al. 2022). Similarly, in jute, molecular weights of PLD-β1 and PLD-ζ1 approached ~ 88–122 kDa, paralleling the upper range observed in wheat PLDs (Islam et al. 2022). Taken together, this expanded and diversified PLD family in wheat, together with physicochemical traits suggestive of stability and versatility, underpins our hypothesis that PLDs play a significant role in wheat’s defence responses, particularly against Fusarium head blight. Domain structure and motif conservation The in-depth analysis of the domain architecture of wheat PLDs revealed six critical conserved domains. Notably, the majority of C2-type PLDs possessed two highly conserved HKD (HxKxxxxD) catalytic domains, a hallmark of their phospholipase D activity. In contrast, PX–PH PLDs were equipped with unique phosphoinositide-binding PX and PH domains, which allow them to effectively target membranes rich in phosphatidylinositol phosphates. These findings highlighted the sophisticated mechanisms underlying PLD functionality in cereals. A subset of uncharacterised PLDs lacked both HKD and IYIENQFF motifs, suggesting that they may have diverged from canonical catalytic roles or undergone pseudogenisation. Despite overall sequence divergence, motif analysis confirmed strong conservation of core functional residues across most isoforms. Specifically, the HKD motif found in 144 PLDs and the IYIENQFF motif present in 129 PLDs are universally recognized as essential for catalytic activity and substrate binding in eukaryotic PLDs (Qin et al. 2002; Jang et al. 2019). In contrast, motif deficiency in uncharacterised PLDs may indicate a shift towards non-enzymatic or regulatory roles, a phenomenon also noted in other plant gene families where divergence leads to subfunctionalisation (Panchy et al. 2016). Predicted secondary structure analysis indicated a predominance of random coils interspersed with α-helices and β-strands, a feature consistent with conformational flexibility. This structural plasticity, coupled with the stable homology models generated for representative isoforms, likely facilitates PLD interactions with diverse lipid substrates and protein partners, thereby supporting their multifunctional roles in stress signalling, membrane trafficking, and lipid metabolism (Hong et al. 2016; Wang 2020). Together, these findings establish that while wheat PLDs exhibit remarkable sequence diversification, the core catalytic machinery is strongly conserved, underscoring their central role in lipid-mediated signalling and adaptive responses. Homology modelling and structural evaluation The analyses consistently demonstrated resilient monomeric structures, well-conserved ligand-binding sites, and stable conformations, highlighting their reliability even when overall sequence similarity to template structures was comparatively low. This robustness underscores the significance of our findings in PLD structural biology. The PLDα1 model of the PIP2-dependent PLD protein stood out due to its superior coverage, making it highly significant. Notably, this model features a calcium ion ligand, which directly supports the calcium-dependent catalytic mechanism characteristic of C2-type PLDs (Qin et al. 2002; Jang et al. 2019). The evaluation metrics convincingly demonstrated the model's reliability, with elevated values signifying enhanced structural accuracy. While the Ramachandran plot revealed that the residues were slightly below the preferred > 90% threshold, the overall assessment deemed the model both structurally acceptable and highly informative. The BAS0735-derived model for the PIP2-independent PLD protein stood out with the highest coverage and was selected for further exploration. While the GMQE score may raise concerns about structural limitations, the QMEANDisCo global score highlighted solid coverage and environmental consistency. Most notably, the Ramachandran plot revealed that the majority of residues were positioned in favoured regions, exceeding the 90% benchmark and reinforcing the model's credibility. This compelling evidence underscored the model's potential for reliable analysis. Another isoform, independent of PI, also resulted in a PLDα1-based model that offered exceptional coverage, featured ligands for both calcium ions and 1,2-dioctanoyl-sn-glycero-3-phosphate. The evaluation metrics strongly affirmed the structural validity of this model. Despite its Ramachandran plot indicating that most residues were within favoured regions, it slightly fell short of the optimal cut-off. However, the model's overall fold stability and effective ligand retention rendered it a highly acceptable and promising candidate for further exploration. Collectively, these homology models provided strong evidence that, despite low sequence identity to templates, wheat PLDs maintain conserved catalytic folds, monomeric stability, and key ligand-binding capacities. Subtle subgroup-specific differences in GMQE, QMEANDisCo, and Ramachandran metrics highlighted potential divergence in structural robustness and ligand interaction, supporting the functional diversification of PLDs in wheat. These models thus offer a valuable framework for future biochemical and functional studies, aligning with recent advances in structure-guided characterisation of plant PLDs (Hong et al. 2016; Wang 2020; Guo et al. 2024). Phylogenetic analysis and gene structures The phylogeny revealed a polyphyletic pattern, with PLDs forming multiple well-supported clusters that corresponded to their domain composition and motif signatures. Within these clusters, the presence of hallmark motifs—HKD (HxKxxxxD) and IYIENQFF—was consistently observed, confirming the catalytic identity of bona fide PLDs and facilitating the exclusion of uncharacterised or unrelated proteins from the family. This grouping strategy effectively partitioned wheat PLDs into clades with high internal homology, reflecting shared structural and functional traits. Criteria such as protein length, motif arrangement, molecular size, and exon–intron organisation were decisive in defining these subfamilies. Notably, C2-type PLDs typically contained 2–10 exons, while PX–PH PLDs possessed 6–20 exons, consistent with patterns previously reported in rice ( Oryza sativa ), where C2-PLDs and PX–PH PLDs characteristically carried ~ 10 and ~ 20 exons, respectively (Li et al. 2009; Pinosa et al. 2013; Zhao et al. 2010a). Interestingly, our analysis also revealed that some wheat PLDs exhibit reduced exon numbers, likely reflecting intron loss through splicing events. Despite this variability, exon arrangement remained highly conserved within groups, with splicing junctions aligning across orthologous sequences. This structural conservation reinforces the evolutionary stability of PLDs, while intron variation may represent an important mechanism for functional diversification and regulatory innovation. Overall, the integration of phylogenetic clustering and gene structure analysis provides robust evidence of conserved lineage-specific features among wheat PLDs, while also revealing subtle divergence that may underpin functional specialisation. These findings highlight both the structural integrity and evolutionary plasticity of the PLD gene family in cereals. Expansion and diversification of PLDs on wheat chromosomes The chromosomal distribution of wheat PLDs revealed a non-uniform yet widespread pattern across the genome. Of the 178 non-redundant PLD genes, members were distributed across six of the seven wheat chromosomes, except chromosome 2, which lacked any PLD representatives. Interestingly, PX–PH subtype PLDs were exclusively localised on chromosome 1, whereas C2-type PLDs were distributed across nearly all chromosomes except for two specific cases. This pattern underscores the differential chromosomal retention and expansion of PLD subfamilies, shaped by the evolutionary dynamics of the allohexaploid wheat genome. The analysis revealed that most phospholipase D (PLD) genes in wheat likely originated from segmental duplication events. This finding aligns with observations made in other large gene families within polyploid cereals (Panchy et al. 2016; Qiao et al. 2019). While tandem duplications may have led to the localized clustering of C2-type PLDs, segmental duplications across the A, B, and D subgenomes appear to be the primary force driving the expansion of this gene family. These trends are similar to those seen in rice and tomato, where members of the PLD gene family also exhibit evidence of duplication-driven diversification (Zhao et al. 2010a; Guo et al. 2024). The analysis also emphasized the conservation of PLD loci among wheat, which has a significantly larger number of syntenic PLD pairs due to its allohexaploid complexity and the selective retention of stress-responsive genes. Such retention is thought to provide functional robustness under biotic and abiotic stress conditions, aligning with the emerging view that lipid signalling pathways are subject to positive selection in crop genomes (Hong et al. 2016; Wang 2020). Overall, the enrichment specific to certain chromosomes, the absence on chromosome 2, and significant duplication-driven diversification indicate that PLDs in wheat have experienced both expansion and structural reorganization, facilitating functional plasticity and potential neofunctionalization. These results offer new insights into the evolutionary dynamics of lipid-signalling gene families in polyploid cereals. Regulatory complexity through cis-elements and transcription factors Promoter analysis of wheat PLDs uncovered a diverse array of cis-regulatory elements and transcription factors that respond to various developmental and environmental signals, highlighting the role of PLDs as key mediators in hormonal regulation and environmental adaptation. The composition of cis-elements significantly indicated the functional specialization among the different subfamilies of PLD. For PX–PH type PLDs, promoter regions carried the GC-motif, conferring anoxic inducibility, enabling responses to low oxygen stress, and the Box-4 element, associated with light-responsive regulation (Maruyama et al. 2014). In C2-type PLDs, promoters harboured ABRE (ABA-responsive element), ARE (anaerobic responsive element), and CAT-box (meristem expression) motifs, suggesting roles in ABA signalling, hypoxic stress tolerance, and developmental regulation (Nakashima and Yamaguchi-Shinozaki 2013; Schmidt et al. 1990). In contrast, PI-independent PLDs encompassed elements linked to plant growth-promoting hormones such as the TCA-element (salicylic acid responsiveness), alongside a diverse set of light-responsive motifs (LTR, G-box, TGA-motif, GA-motif, TCT-motif, Box-4). Additional motifs included the A-box (general cis-regulatory element) and the O2-site, traditionally associated with regulation of zein metabolism in cereals (Schmidt et al. 1990). The predicted binding sites for transcription factors (TFs) underscore the intricate complexity involved. Members of the C2H2 zinc finger and ERF (ethylene-responsive factor) families have been frequently associated with PLD promoters, highlighting their roles in general stress signaling pathways. In particular, the ERF transcription factor inhibited the growth of FHB in wheat crops by interacting with both the GCC box and non-GCC cis-elements in the promoter region (Gupta et al. 2023). Subgroup-specific associations were also evident: MYB, LBD (LATERAL ORGAN BOUNDARIES DOMAIN), and BBR-BPC (BARLEY B RECOMBINANT/BASIC PENTACYSTEINE) families showed enriched interactions with distinct PLD subtypes. While MYB and NAC TFs have previously been linked to lipid metabolism and stress responses in plants (Wang 2020; Hong et al. 2016), our identification of ERF and BBR-BPC regulators extends the known regulatory landscape of PLDs. The BBR-BPC family is particularly noteworthy as it is involved in seed and flower development, regulates homeotic (HOX) genes, and participates in brassinosteroid signalling, a pathway that has been shown to restrict the growth of Fusarium pathogens (Gupta et al. 2016; Nakashima and Yamaguchi-Shinozaki 2013). This suggests that PLD regulation is intimately connected with canonical stress-related transcription factors (TFs) as well as lipid signaling, which is intricately integrated with developmental and hormonal signaling networks that modulate both pathogen defense and growth. Taken together, these findings underscore the regulatory diversity of wheat PLDs, showing how cis-elements and transcription factor interactions enable fine-tuned responses to hormones, environmental stresses, and developmental cues. The integration of ABA, JA, ethylene, and light signalling pathways with lipid-mediated responses positions PLDs as critical regulatory nodes in stress adaptation and growth regulation. Tandem repeats Tandem repeats within protein-coding sequences are recognised as important drivers of protein diversity, stability, and regulatory capacity. In wheat PLDs, the analysis revealed tandem repeat regions in specific isoforms, notably TaPLD-5D-Del8 and TaPLD-7D-2Alp1, which were associated with elevated expression levels compared to other family members. The presence of these repeats suggests that they may contribute to enhanced protein synthesis efficiency and to greater structural and functional versatility. Such repeat-mediated amplification is thought to influence transcriptional regulation and translation dynamics, ultimately increasing protein abundance under certain developmental or stress conditions. This observation highlights the role of tandem repeats not only in shaping the genetic architecture of PLDs but also in facilitating the functional diversification of the wheat genome, consistent with the broader importance of repeat sequences in the evolution of stress-associated gene families (Gemayel et al. 2010; Moxon and Wills 1999). Together, these findings emphasise the adaptive significance of tandem repeats in modulating PLD gene expression, pointing to potential molecular mechanisms by which wheat fine-tunes lipid signalling capacity in response to environmental challenges. Translational potential of SSR markers SSR markers designed from PLD sequences add a translational dimension to our study. Of the 161 primer pairs developed, 30 amplified PLDs across 108 loci in silico. These markers could be directly applied in marker-assisted selection to track PLD alleles associated with FHB resistance. Few lipid-focused studies have coupled genome-wide analysis with marker development; thus, this resource distinguishes our work from previous lipid metabolism reports (Troncoso-Ponce et al., 2016; Pan et al., 2013), as well as from broader genome-wide lipid gene analyses in crops such as soybean and flax that did not incorporate marker resources (Huang et al., 2021; Ding et al., 2020a; Shankar et al., 2016). miRNA-mediated regulation of PLDs A particularly novel outcome of this study is the identification and experimental validation of miRNA regulation of wheat PLDs. Two miRNAs, tae-miR9664-3p and tae-miR160, were predicted and experimentally confirmed to target PLDs during Fusarium graminearum infection. Multiplex PCR and semi-quantitative RT-PCR assays revealed infection-dependent co-expression and genotype-specific modulation, with resistant and susceptible cultivars displaying contrasting regulation patterns. miR160 has long been implicated in auxin signalling and stress adaptation (Mallory et al. 2005), targeting auxin response factors (ARFs) to fine-tune hormone-dependent growth and defence pathways. Notably, tae-miR160 has been associated with resistance against Magnaporthe oryzae and Phytophthora infestans (Wu et al. 2017), underscoring its dual roles in auxin-mediated development and pathogen defence. miR9664, on the other hand, was originally reported in rice blast resistance (Campo et al. 2013) and more recently linked to FHB resistance in wheat (Kumar et al. 2021; Gupta et al. 2023). Our findings extend this knowledge by demonstrating, for the first time, that tae-miR9664-3p and tae-miR160 directly regulate wheat PLDs, thereby linking miRNA-mediated post-transcriptional control with phospholipase-mediated lipid defence signalling. This establishes a new regulatory layer in wheat immunity, integrating miRNA activity into lipid-based defence pathways critical for resistance to fungal pathogens. Functional annotation Functional annotation of wheat PLDs using GO and KEGG analyses revealed their multifaceted contributions to plant metabolism, signalling, and stress adaptation. GO categorisation linked PLDs to diverse biological processes, including lipid catabolism, cellular signalling, and programmed cell death, consistent with their role in integrating metabolic and defence pathways. KEGG pathway mapping provided more specific insights, highlighting strong associations of wheat PLDs with ether lipid metabolism and glycerophospholipid metabolism, both of which are critical for cellular membrane dynamics and stress responses. PLDs were assigned to the enzymatic category EC 3.1.4.4 (phospholipase D), confirming their catalytic role in hydrolysing terminal phosphodiester bonds of glycerophospholipids (Wang and Wang 2001). Within glycerophospholipid metabolism, PLDs were predicted to catalyse the conversion of phosphatidylethanolamine to 1,2-diacyl-sn-glycerol-3P and phosphatidylcholine to 1,2-diacyl-sn-glycerol-3P. These reactions yield phosphatidic acid (PA), a key lipid second messenger that mediates stress-induced signalling cascades (Hong et al. 2016; Testerink and Munnik 2011). The integration of PLDs into these metabolic pathways highlights their importance in lipid-derived signal generation, membrane remodelling, and hormone-mediated defence responses. Notably, the enrichment of ether lipid and glycerophospholipid pathways aligns with recent reports that PLDs contribute to cellular signalling and membrane trafficking under abiotic and biotic stress conditions. Their capacity to link primary metabolism with defence-associated signalling networks underscores the functional versatility of wheat PLDs. Overall, these annotations illustrate that PLDs in wheat are not limited to basal lipid hydrolysis but act as central regulators of lipid metabolism and stress signalling, broadening our understanding of their physiological and adaptive significance. Divergent expression between resistant and susceptible genotypes RNA-seq expression profiling revealed a pronounced divergence in phospholipase D (PLD) expression between wheat near-isogenic lines (NILs) differing in resistance to Fusarium graminearum . In the susceptible genotype 2890, selective repression of PLDs is predicted to disrupt phosphatidic acid (PA)-mediated signalling, potentially weakening downstream defence pathways and exacerbating vulnerability to infection. This observation aligns with previous reports showing transcriptional suppression of lipid transfer proteins in susceptible wheat lines under fungal attack, highlighting a conserved weakness in lipid-mediated defence networks (Molina and García-Olmedo 1997). Extending these findings, our study identifies PLDs as critical determinants of genotype-specific resistance. Isoform-specific expression patterns revealed functional divergence among PLD groups. Group A isoforms exhibited high basal expression, consistent with housekeeping roles in growth, development, and basal cellular processes (Bargmann and Munnik 2006). A moderate decline in the susceptible genotype suggests these isoforms primarily support developmental processes rather than acute defence responses. Group B isoforms showed moderate, tissue-specific induction in rachis and spike tissues, paralleling observations in Brassica napus , where certain PLDs demonstrate minimal stress responsiveness (Li et al. 2013). Group C members maintained constitutive, spikelet-enriched expression across genotypes, similar to stably expressed tomato PLDs (Guo et al. 2024), indicating roles in lipid metabolism and structural maintenance rather than direct pathogen-triggered defence. Group D isoforms displayed sharp genotype-dependent induction, reminiscent of soybean phospholipase C transcript dynamics under osmotic stress (Chen et al. 2020a). The downregulation of Group D PLDs in the susceptible genotype suggests impaired PA signalling, potentially compromising the activation of downstream defence cascades. The specific suppression of Group D PLDs supports the hypothesis that infection-induced repression of PA biosynthesis undermines lipid-mediated defence networks. Methodological choices enhanced the reliability of these conclusions. Focusing on a single RNA-seq dataset (PRJEB24686) minimized platform-specific artefacts and provided a consistent reference for isoform-level comparisons. Semi-quantitative RT-PCR validation corroborated the RNA-seq trends, confirming that Group D PLD repression is a reproducible, biologically meaningful response. Collectively, these findings indicate that selective transcriptional repression of PLDs in susceptible wheat genotypes disrupts PA-mediated signalling, amplifying susceptibility to F. graminearum . In contrast, maintenance of PLD expression in resistant genotypes preserves signalling capacity and supports effective defence. Wheat PLDs therefore function as hierarchically organized, coordinated modules that integrate tissue-specific roles with inducible defence responses, underscoring their potential as molecular markers for breeding Fusarium-resistant cultivars. Experimental validation of PLD–miRNA interactions Experimental validation confirmed that PLD transcripts co-accumulate with stress-responsive miRNAs, notably tae-miR160, during F. graminearum infection. Multiplex PCR and stem-loop RT-PCR assays revealed genotype-specific expression patterns; resistant cultivars maintained stable PLD transcript levels, whereas susceptible ones exhibited marked repression. These results support a model in which miRNA regulation functions as a molecular switch that fine-tunes PLD-mediated lipid signalling under pathogen stress. This finding aligns with earlier reports demonstrating that suppression of phospholipases compromises host immunity and enhances disease susceptibility in soybean (Chen et al. 2020b) and rice (Zhao et al. 2010b). The present study provides the first experimental evidence in wheat that miRNA-PLD crosstalk contributes to FHB resistance, thereby revealing a novel regulatory layer within the lipid-signalling network and offering new biotechnological targets for crop protection. Recent systems-level analyses further contextualise these results. Rocher et al. (2024) identified a conserved gene regulatory network underlying wheat susceptibility to F. graminearum and demonstrated that fungal core effectors target host master regulators. Additionally, Muslu et al. (2025) characterised non-coding regulatory elements, including miRNAs and lncRNAs, associated with FHB resistance. Collectively, these studies reinforce the centrality of post-transcriptional regulation in wheat defence. Our findings extend these models by revealing a miRNA-PLD module as an additional layer of defence control that integrates lipid signalling and gene regulatory networks. Moreover, PLD has been established as a pivotal mediator of lipid-derived defence signalling (González-Mendoza 2021), and its regulation by miRNAs under abiotic stress (Ding 2013) underscores the evolutionary conservation of this mechanism. Together, these insights suggest that miRNA-guided modulation of PLD activity constitutes a versatile adaptive strategy linking membrane lipid remodelling to immune activation. Conclusion This study presents the first comprehensive genome-wide analysis of the phospholipase D (PLD) gene family in hexaploid wheat, significantly expanding our understanding of lipid signalling in cereal defence. We systematically characterized 178 TaPLD genes, revealing their diverse structural features, complex regulatory landscapes involving specific transcription factors and cis-elements, and distinct genomic distribution shaped by duplication events. A key finding is the divergent expression of specific TaPLD isoforms between FHB-resistant and susceptible wheat genotypes, underscoring their functional importance in the defence response. Crucially, we identified and experimentally validated a novel regulatory axis where a miRNA, tae-miR160, directly target TaPLD transcripts. This post-transcriptional regulation provides a mechanistic explanation for the suppressed PLD-mediated signalling observed in susceptible plants, highlighting a previously unexplored layer of immune modulation in wheat. The functional annotation linking PLDs to critical lipid signalling pathways, coupled with the development of SSR markers from PLD loci, adds a practical dimension to our work. In summary, our results establish PLDs as central players in wheat's immune signalling and unveil a miRNA-PLD module that is critical for FHB resistance. These insights and the molecular resources generated herein provide a solid foundation for future functional studies and biotechnological strategies aimed at enhancing disease resistance in wheat. Declarations Funding This research was supported by the Indian National Science Academy (INSA), New Delhi, under the Visiting Scientist Fellowship awarded to the first author at the International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi (Grant No. INSA/SP/VSP-59/2019–20/), for his PhD research leading to these results. No additional external funding, grants, or commercial support was received specifically for the preparation of this manuscript. The first author gratefully acknowledges the support of the Director, ICAR – National Institute of Biotic Stress Management (NIBSM), Raipur, India, for approving his INSA Visiting Scientist Programme 2019 at the International Centre for Genetic Engineering and Biotechnology, New Delhi, India, under fellowship support from the Indian National Science Academy (INSA), New Delhi. Competing Interests The authors declare that they have no relevant financial or non-financial interests to disclose. Data Availability The datasets generated and/or analysed during the current study are available in the supplementary materials accessible within the manuscript. Additional datasets generated and/or analysed during the current study are available from the corresponding author upon reasonable request. Author Contributions Lalit Kharbikar conceived the study, coordinated the research, performed data analyses and drafted the manuscript Arti Shanware contributed to experimental design, data validation, and interpretation of molecular results. Piyush Ghoshe and Shweta Nandanwar carried out bioinformatics analyses, including gene identification, motif/domain analysis, and phylogenetics. Malkhan Gurjar and Mahender Saharan contributed to pathogen inoculation experiments and disease phenotyping. Pankaj Sharma and Pramod Rai assisted in data curation, and manuscript revision. Simon Edwards provided critical review, editorial input, statistical analyses and international collaboration support. Neeti Sanan-Mishra co-supervised the project, contributed to miRNA prediction and validation experiments, and revised the manuscript. All authors read and approved the final manuscript. 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BMC Plant Biol 12:168. https://doi.org/10.1186/1471-2229-12-168 Supplementary Files PLDdatasupplementary.xls Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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10:45:11\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":190798,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eConserved domain organisation of wheat phospholipase D (PLD) proteins.\\u003c/strong\\u003e\\u003cbr\\u003e\\nConserved domain analysis revealed six major domains across the PLD family: C2 (blue), PLDc (yellow), PLDc_2 (pink), PLDc_N (red), PLD_C (purple), and PH (green). Protein lengths are shown in amino acids (aa) on the scale bar (0–1200 aa). Detailed annotations for each protein are provided in Supplementary Tables S1 and S3.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/a66a7fa7e1c6c040a368714a.png\"},{\"id\":95654596,\"identity\":\"f0538e44-54ae-49fc-9dd0-f80258cd344a\",\"added_by\":\"auto\",\"created_at\":\"2025-11-11 16:12:32\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":174934,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eConserved motif architecture and distribution of HKD catalytic motifs in wheat PLDs. \\u003c/strong\\u003e(A)\\u003cstrong\\u003e \\u003c/strong\\u003eComprehensive analysis of wheat PLD proteins identified 165 conserved motifs distributed across 178 sequences. The motif and exon architectures are depicted as colored boxes, with introns represented by black connecting lines. (B) The distribution of HKD motifs across the 178 sequences is also illustrated, highlighting 123 sequences that possessed one or more HKD domains. Complete details of the HKD motif sequences are provided in Supplementary Table S4.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/2b5398bb2ff9c5429158f48f.png\"},{\"id\":95536576,\"identity\":\"22b73f27-bcd6-437e-804d-7326c0296b19\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":213366,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eSecondary structure prediction of wheat PLD isoforms. \\u003c/strong\\u003ePredicted structural features of representative PI-independent (top), PIP2-dependent (middle), and PIP2-independent (bottom) PLDs are shown. For each isoform, schematic plots display secondary structure elements along the amino acid sequence (upper panel: predicted localization of α-helices, β-sheets, turns, and coils; lower panel: probability scores across residues). Helices (blue), sheets (red), turns (green), and coils (purple) are indicated. Coil-rich regions dominate all isoforms, whereas helices and sheets are interspersed across domains, reflecting structural adaptability.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/47608cca1faa8ea7e3670564.png\"},{\"id\":95536620,\"identity\":\"98bca0ce-1085-4080-90e6-d64e02e6d4de\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:53\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":158444,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eHomology modelling and structural evaluation of representative wheat PLDs.\\u003c/strong\\u003e (A) PI-independent PLD model generated using plant phospholipase D alpha 1 as template (25.32% sequence identity). (B) PIP2-dependent PLD model generated using plant phospholipase D alpha 1 as template (16.93% sequence identity). (C) PIP2-independent PLD model based on Protein BAS0735 (unknown function; 29.41% sequence identity).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/30e002114e82cf1061ff62c9.jpg\"},{\"id\":95536623,\"identity\":\"ba73f310-44c0-4f01-8e2f-4e59923f7240\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:45:09\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":148712,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMaximum-likelihood phylogenetic tree of 178 wheat PLD isoforms from the A, B, and D subgenomes.\\u003c/strong\\u003e Three classes were resolved: C2-type(subgroups of PIP2-dependent, PIP2-independent, and PI-independent PLDs), PX–PH-type (Ca²⁺-independent PLDs lacking the C2 domain), and an unclassified groupwith incomplete HKD motifs or atypical domains. Branch colours denote subgroups.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/70311c66e81f4533576ef277.png\"},{\"id\":95536578,\"identity\":\"c66e9424-1b9a-4c29-b69c-f88889d4fb3a\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":74762,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGene structure and architecture of wheat PLDs. \\u003c/strong\\u003eThe phylogenetic tree was constructed using representative isoforms from the A, B, and D subgenomes. Distinct clades are shaded in different colors to highlight major evolutionary groupings. The corresponding exon–intron structures are shown on the right. Untranslated regions are represented by blue boxes, while coding regions (exons) are depicted as yellow boxes. Intronic regions are shown as connecting lines. The scale bar indicates the number of substitutions per site.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage8.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/54c1e8c739b5593e7cba4d77.png\"},{\"id\":95654281,\"identity\":\"7da2babd-2609-4f4c-b1c5-243af1c36c76\",\"added_by\":\"auto\",\"created_at\":\"2025-11-11 16:10:47\",\"extension\":\"png\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":111276,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eChromosomal Distribution of PLD Genes in Wheat. \\u003c/strong\\u003eEach PLD gene is precisely mapped to its respective chromosomal position, as indicated along the linear chromosome representations. The chromosome numbers are shown at the base of each panel, and the physical distances along each chromosome are indicated by the scale bar in megabases (Mb). Subgenomic distinctions (A, B, and D genomes) are demarcated to highlight the distribution of PLD genes across the hexaploid wheat genome.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage9.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/cb393222e7c1d5746477f976.png\"},{\"id\":95536584,\"identity\":\"c0602fbe-a619-4776-9f0d-a8fbd344a10a\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"png\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":237380,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eCore and stress-related cis-elements in wheat PLD promoters.\\u003c/strong\\u003e Promoter analysis revealed core motifs (TATA-box, CAAT-box) and stress/hormone-related motifs including CGTCA, TGACG, ABRE, and ARE.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage10.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/a37852f0966a0b66be890409.png\"},{\"id\":95536608,\"identity\":\"c2e74059-b71f-429b-beb1-273bfab22ce9\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:53\",\"extension\":\"png\",\"order_by\":9,\"title\":\"Figure 9\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":221784,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003ePredicted transcription factors regulating wheat PLDs.\\u003c/strong\\u003e Significant TF families (BBR-BPC, C2H2, ERF, LBD, MYB) show distinct associations with different PLD subgroups.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage11.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/12620075a9f7430a7e8bdeff.png\"},{\"id\":95536581,\"identity\":\"bc67f823-de1e-4478-8c05-dcd0f78e3809\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"png\",\"order_by\":10,\"title\":\"Figure 10\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":18936,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eKa/Ks Ratio of PLD Tandem Duplication Genes in \\u003c/strong\\u003e\\u003cem\\u003e\\u003cstrong\\u003eTriticum aestivum\\u003c/strong\\u003e\\u003c/em\\u003e\\u003cstrong\\u003e. \\u003c/strong\\u003eAmong the investigated PLDs, 19 genes exhibited multiple duplication events. Ka/Ks ratios indicate whether the duplicated genes are under purifying selection (Ka/Ks \\u0026lt; 1), neutral evolution (Ka/Ks ≈ 1), or positive selection (Ka/Ks \\u0026gt; 1).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage12.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/eae7b6f8c10d82f8ad190661.png\"},{\"id\":95536582,\"identity\":\"0292ad83-fbfb-4dd0-a38d-4d2a915ed5f7\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"png\",\"order_by\":11,\"title\":\"Figure 11\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":18608,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003ePredicted miRNA–target interactions between wheat PLDs and regulatory miRNAs. \\u003c/strong\\u003eThe network shows that tae-miR9664-3p targets three PLD isoforms (\\u003cem\\u003eTaPLD-4B-1Bet1\\u003c/em\\u003e, \\u003cem\\u003eTaPLD-5A-1Bet1\\u003c/em\\u003e, and \\u003cem\\u003eTaPLD-4D-1Gam1\\u003c/em\\u003e), while tae-miR160 regulates \\u003cem\\u003eTaPLD-3A-1\\u003c/em\\u003eand \\u003cem\\u003eTaPLD-3B-1\\u003c/em\\u003e. Red nodes represent miRNAs, green nodes indicate PLD isoforms, and white arrows depict predicted interactions.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Onlinefloatimage13.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/343563433eac66240ecb9352.png\"},{\"id\":95653988,\"identity\":\"a8539032-6e3b-4b1d-8977-4b37d517ad2e\",\"added_by\":\"auto\",\"created_at\":\"2025-11-11 16:07:33\",\"extension\":\"jpg\",\"order_by\":12,\"title\":\"Figure 12\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":194254,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGene Ontology (GO) classification of wheat PLD isoforms. \\u003c/strong\\u003eThe molecular function classification (A) showed that 91% of PLDs were associated with catalytic and binding activities. Highly enriched terms included \\u003cem\\u003ecatalytic activity\\u003c/em\\u003e (GO:0003824), \\u003cem\\u003ehydrolase activity\\u003c/em\\u003e (GO:0016787), \\u003cem\\u003ephospholipase activity\\u003c/em\\u003e (GO:0004620), and \\u003cem\\u003eN-acylphosphatidylethanolamine-specific PLD activity\\u003c/em\\u003e (GO:0070290), alongside binding-related terms such as \\u003cem\\u003ecalcium ion binding\\u003c/em\\u003e (GO:0005509). Within the biological process category (B), approximately 87% of PLDs were assigned to processes related to lipid metabolism, signal transduction, and regulation, including terms such as \\u003cem\\u003elipid metabolic process\\u003c/em\\u003e(GO:0006629), \\u003cem\\u003ephospholipid catabolic process\\u003c/em\\u003e (GO:0009395), and \\u003cem\\u003esignal transduction\\u003c/em\\u003e (GO:0007165). For the cellular component ontology (C), the majority of PLDs (84%) were localised to the plasma membrane and associated structures, as reflected by enriched terms such as \\u003cem\\u003ecell periphery\\u003c/em\\u003e (GO:0071944), \\u003cem\\u003eplasma membrane\\u003c/em\\u003e (GO:0005886), and \\u003cem\\u003eintegral component of membrane\\u003c/em\\u003e (GO:0016021).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"12.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/10aca994c6c7fa29fb5d85c9.jpg\"},{\"id\":95536590,\"identity\":\"3589e839-8028-4e3b-b2a6-575d0e948425\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"jpg\",\"order_by\":13,\"title\":\"Figure 13\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":250911,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eKEGG pathway analysis of wheat PLDs in lipid metabolism. \\u0026nbsp;\\u003c/strong\\u003eIn the glycerophospholipid metabolism pathway (A), PLDs were implicated in essential phospholipid turnover processes. Specifically, the enzymatic hydrolysis of \\u003cem\\u003ephosphatidylethanolamine\\u003c/em\\u003e and \\u003cem\\u003ephosphatidylcholine\\u003c/em\\u003einto \\u003cem\\u003e1,2-diacyl-sn-glycerol-3P\\u003c/em\\u003e was highlighted, underscoring the generation of \\u003cem\\u003ediacylglycerol (DAG)\\u003c/em\\u003e as a key intermediate in lipid signalling and membrane remodelling. The ether lipid metabolism pathway (B) further demonstrated PLD contributions in the cleavage of \\u003cem\\u003eplasmenylethanolamine\\u003c/em\\u003e to yield \\u003cem\\u003eplasmenic acid\\u003c/em\\u003e.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"13.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/26ba3d7645d8cdf82d5837f9.jpg\"},{\"id\":95536601,\"identity\":\"5fd08414-e58e-4c45-b9be-e70bf7d2d90c\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:44:52\",\"extension\":\"jpeg\",\"order_by\":14,\"title\":\"Figure 14\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":80874,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eHierarchical clustering of 40 wheat PLD isoforms under \\u003c/strong\\u003e\\u003cem\\u003e\\u003cstrong\\u003eFusarium graminearum\\u003c/strong\\u003e\\u003c/em\\u003e\\u003cstrong\\u003einoculation resolved them into four expression groups.\\u003c/strong\\u003e Broadly upregulated (Group A), tissue-specific (Group B), spikelet-enriched (Group C), and genotype-dependent stress-responsive isoforms (Group D). Resistant genotype showed strong induction of PLD isoforms, whereas susceptible genotype exhibited weak or no induction.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"groupimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/74a5f527d035ac842d71b3f3.jpeg\"},{\"id\":95654228,\"identity\":\"8b795bc1-5f44-4a81-818c-5fe50131619a\",\"added_by\":\"auto\",\"created_at\":\"2025-11-11 16:10:35\",\"extension\":\"jpg\",\"order_by\":15,\"title\":\"Figure 15\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":166360,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eExperimental validation of \\u003c/strong\\u003e\\u003cem\\u003e\\u003cstrong\\u003eTaPLD\\u003c/strong\\u003e\\u003c/em\\u003e\\u003cstrong\\u003e–miRNA interactions. \\u003c/strong\\u003e(A) In silico mapping predicted tae-miR160 binding within the 5′ UTR–proximal region of TaPLD, and flanking primers (Primer 1: TaPLD-miR160-F(forward) and Primer 2: TaPLD-miR160-R(reverse)) were designed across this site. (B) Multiplex PCR assays amplified both \\u003cem\\u003eTaPLD\\u003c/em\\u003e and tae-miR160 in resistant (PBW 343) and susceptible (HD 2967) genotypes. Negative controls (- C: Milli-Q water, + CP: primer-only, + CD: pathogen DNA) confirmed assay specificity. (B) Semi-quantitative RT-PCR using \\u003cem\\u003eTaPLD\\u003c/em\\u003e-specific miRNA-primed (Primer 1: TaPLD-miR160-F(forward) and Primer 2: TaPLD-miR160-R(reverse)) reactions showed repression in HD 2967 (Lanes 1–3) but stable/slightly elevated expression in PBW 343 (Lanes 4–6). No amplification was observed in \\u003cem\\u003eF. graminearum\\u003c/em\\u003e RNA (Lanes 7–9). Actin served as a positive control (Lane 10). Densitometry confirmed infection-dependent \\u003cem\\u003eTaPLD\\u003c/em\\u003e downregulation in susceptible genotypes, consistent with RNA-seq clustering.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"15.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/f92a5af9fa1a95b95b22ca1b.jpg\"},{\"id\":96245518,\"identity\":\"66c1922e-6698-4e32-95f3-11825e039131\",\"added_by\":\"auto\",\"created_at\":\"2025-11-19 07:20:49\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":4425149,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/dd30946a-e00c-4e96-b80e-f074e176c447.pdf\"},{\"id\":95536723,\"identity\":\"b88ee504-af94-4ec9-80cb-4d0d08a5face\",\"added_by\":\"auto\",\"created_at\":\"2025-11-10 10:45:33\",\"extension\":\"xls\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":4586496,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"PLDdatasupplementary.xls\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7877570/v1/a67096c1c8cac8349ed9a024.xls\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Genome-wide identification of phospholipase D gene family in wheat reveals miRNA-regulated module underlying FHB resistance\",\"fulltext\":[{\"header\":\"Key Message\",\"content\":\"\\u003cp\\u003ePLD gene family analysis in wheat uncovers a miRNA–PLD regulatory module that modulates Fusarium head blight resistance, providing molecular tools for breeding resistant cultivars.\\u003c/p\\u003e\"},{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eWheat (\\u003cem\\u003eTriticum aestivum\\u003c/em\\u003e L.) is one of the most important staple crops worldwide, providing nearly 20% of the global caloric intake and sustaining billions of people as a primary food source (Dweba et al. 2017). However, wheat production faces growing challenges from both abiotic and biotic stresses, which collectively undermine yield, quality, and food security. Among these threats, Fusarium head blight (FHB), caused predominantly by \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e, remains one of the most destructive fungal diseases of wheat. FHB epidemics reduce grain yield and quality while contaminating harvested kernels with mycotoxins such as deoxynivalenol (DON), which pose serious risks to human and animal health (Alisaac and Mahlein 2023; Giedrojć et al. 2025). The global burden of FHB has intensified in recent decades, with climate change further exacerbating its incidence by creating favourable conditions of humidity and warmth for pathogen proliferation (Gonz\\u0026aacute;lez-Mendoza et al. 2021).\\u003c/p\\u003e\\u003cp\\u003eTraditional breeding efforts have introduced moderate resistance in some wheat cultivars, but resistance is quantitative and polygenic, with no single source providing complete protection (Canonne et al. 2011). Therefore, an improved understanding of the molecular and regulatory mechanisms underlying wheat immunity is essential for developing novel genetic and biotechnological strategies to combat FHB.\\u003c/p\\u003e\\u003cp\\u003eLipids and their metabolites play pivotal roles in plant growth, development, and responses to environmental stresses. Phospholipases, enzymes that hydrolyse membrane phospholipids, have emerged as central players in stress signalling, as they generate lipid-derived second messengers that activate downstream defence pathways (Deepika and Singh 2022). In particular, phospholipase D (PLD; EC 3.1.4.4) catalyses the hydrolysis of structural phospholipids to produce phosphatidic acid (PA), a versatile signalling molecule involved in membrane dynamics, vesicle trafficking, cytoskeletal organisation, programmed cell death, and hormone responses (Zhang et al. 2004; Testerink and Munnik 2005; Wang et al. 2006). PA also acts as a docking site for protein kinases and phosphatases, thereby integrating lipid metabolism with cellular signalling networks (Li et al. 2009).\\u003c/p\\u003e\\u003cp\\u003eFunctional studies in Arabidopsis and rice have demonstrated the roles of PLDs in drought tolerance, salt stress adaptation, and pathogen defence. For example, PLDα1 and PLDδ in Arabidopsis regulate abscisic acid (ABA) signalling, stomatal closure, and reactive oxygen species generation (Qin and Wang 2002a; Zhang et al. 2004). In rice, PLDs have been implicated in the regulation of blast resistance and drought stress adaptation (Zhao et al. 2010a). Tomato PLDs modulate lipid signalling during fruit development and pathogen challenge (Guo et al. 2024). These studies highlight the importance of PLDs as molecular switches that coordinate developmental and defence processes.\\u003c/p\\u003e\\u003cp\\u003eDespite this knowledge, the PLD gene family remains poorly characterised in wheat, a hexaploid species with a large, complex genome. Previous genome-wide studies have catalogued PLDs in model plants and some crops, but no systematic analysis has addressed their roles in wheat, especially in relation to FHB. The integration of PLDs into stress-responsive transcriptional networks, their regulation by transcription factors (TFs), and their post-transcriptional modulation by microRNAs (miRNAs) are virtually unexplored in wheat. miRNAs are short, non-coding RNAs that fine-tune gene expression through sequence-specific cleavage or translational repression (Duan et al. 2015). Several studies have reported the involvement of miRNAs in wheat responses to drought, salinity, and pathogen attack (Hao et al. 2022), but their regulation of PLDs remains to be demonstrated.\\u003c/p\\u003e\\u003cp\\u003eGiven the central role of PLDs in lipid-mediated stress signalling and the urgent need to understand molecular mechanisms of FHB defence, we undertook a comprehensive genome-wide characterisation of the PLD gene family in wheat. We identified 178 non-redundant PLDs and classified them based on their domain organisation, phylogenetic relationships, and structural features. We analysed their physicochemical properties, chromosomal distribution, exon\\u0026ndash;intron structures, conserved motifs, cis-regulatory elements, and predicted TF regulators. We also examined their post-transcriptional regulation by wheat miRNAs, validated miRNA\\u0026ndash;PLD interactions experimentally using multiplex PCR and semi-quantitative RT-PCR, and profiled their expression in resistant and susceptible genotypes under FHB infection using RNA-seq.\\u0026nbsp;Finally, we mined simple sequence repeat (SSR) markers from PLD loci, providing tools for genetic mapping and breeding.\\u003c/p\\u003e\\u003cp\\u003eThis integrative study represents the first systematic attempt to link wheat PLDs to FHB defence. By combining computational, transcriptomic, and experimental approaches, we reveal the structural, regulatory, and functional complexity of wheat PLDs, and establish a miRNA\\u0026ndash;TF\\u0026ndash;PLD signalling axis that underpins resistance. Our findings not only expand fundamental understanding of lipid-mediated defence signalling in cereals but also provide practical molecular tools for breeding FHB-resistant wheat cultivars.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eIdentification of PLD genes in wheat\\u003c/h2\\u003e\\u003cp\\u003eProtein sequences of wheat (\\u003cem\\u003eTriticum aestivum\\u003c/em\\u003e L.) were retrieved from the Phytozome v13 and NCBI databases. To ensure comprehensive coverage, both annotated and uncharacterised proteins were included. Initial filtering for PLD domains was performed using Pfam (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://pfam.xfam.org\\u003c/span\\u003e\\u003cspan address=\\\"http://pfam.xfam.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) and the Conserved Domain Database (CDD; \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml\\u003c/span\\u003e\\u003cspan address=\\\"https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). A total of 331 candidate PLDs were identified. Redundant sequences were removed by aligning proteins with Jalview v2.11.2.6 at a 95% identity threshold, resulting in 178 non-redundant PLDs for downstream analysis.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003ePhysicochemical properties and subcellular localisation\\u003c/h3\\u003e\\n\\u003cp\\u003eThe amino acid length, molecular weight, theoretical isoelectric point (pI), instability index, aliphatic index, and grand average of hydropathicity (GRAVY) were calculated using ProtParam (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://web.expasy.org/protparam/\\u003c/span\\u003e\\u003cspan address=\\\"https://web.expasy.org/protparam/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Subcellular localisation was predicted using Plant-mPLoc (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.csbio.sjtu.edu.cn/bioinf/plant-multi/\\u003c/span\\u003e\\u003cspan address=\\\"http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), which integrates sequence-based and annotation-based prediction.\\u003c/p\\u003e\\n\\u003ch3\\u003eDomain, motif, and secondary structure analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eConserved domains were confirmed using Pfam and CDD. Motifs were predicted with MEME Suite v5.4.1 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://meme-suite.org\\u003c/span\\u003e\\u003cspan address=\\\"http://meme-suite.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), with maximum motifs set to 15. Specific motif scans for HKD (HxKxxxxD) and IYIENQFF were conducted using FIMO. Secondary structures were predicted using SOPMA (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html\\u003c/span\\u003e\\u003cspan address=\\\"https://npsa-prabi.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), with parameters set at 70% window size and default thresholds.\\u003c/p\\u003e\\n\\u003ch3\\u003eHomology modelling and structural evaluation (dup: abstract ?)\\u003c/h3\\u003e\\n\\u003cp\\u003eRepresentative PLDs from PI-independent, PIP2-dependent, and PIP2-independent subgroups were modelled using SWISS-MODEL (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://swissmodel.expasy.org\\u003c/span\\u003e\\u003cspan address=\\\"https://swissmodel.expasy.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Structural quality was assessed using Global Model Quality Estimation (GMQE), QMEANDisCo scores, and Ramachandran plots (PROCHECK). Structural visualisation was performed using PyMOL v2.5.\\u003c/p\\u003e\\n\\u003ch3\\u003ePhylogenetic and gene structure analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eMultiple sequence alignment of wheat PLDs was conducted using MUSCLE in ETE3. Phylogenetic trees were constructed with the neighbour-joining method and 1,000 bootstrap replicates, and visualised with iTOL v6. Gene structures, including exon\\u0026ndash;intron organisation, were analysed with GSDS v2.0 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://gsds.cbi.pku.edu.cn\\u003c/span\\u003e\\u003cspan address=\\\"http://gsds.cbi.pku.edu.cn\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eChromosomal distribution\\u003c/h2\\u003e\\u003cp\\u003eChromosomal mapping of PLD genes was performed using the IWGSC RefSeq v1.1 wheat genome assembly available at Wheatomics (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://202.194.139.32/wheatomics/\\u003c/span\\u003e\\u003cspan address=\\\"http://202.194.139.32/wheatomics/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Gene coordinates were extracted, and physical locations visualised with TBtools v2.003.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eCis-regulatory element and transcription factor prediction\\u003c/h3\\u003e\\n\\u003cp\\u003ePromoter sequences (2 kb upstream of the start codon) were retrieved from the wheat genome and analysed for cis-regulatory elements using PlantCARE (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://bioinformatics.psb.ugent.be/webtools/plantcare/\\u003c/span\\u003e\\u003cspan address=\\\"http://bioinformatics.psb.ugent.be/webtools/plantcare/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Putative transcription factors (TFs) associated with PLDs were predicted using PlantTFDB v5.0 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://planttfdb.gao-lab.org\\u003c/span\\u003e\\u003cspan address=\\\"http://planttfdb.gao-lab.org\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003ch3\\u003eTandem repeat and SSR marker analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eTandem repeats within PLDs were detected using Tandem Repeats Finder (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://tandem.bu.edu/trf/trf.html\\u003c/span\\u003e\\u003cspan address=\\\"https://tandem.bu.edu/trf/trf.html\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). SSRs were identified using BatchPrimer3 v1.0 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://wheat.pw.usda.gov/demos/BatchPrimer3\\u003c/span\\u003e\\u003cspan address=\\\"https://wheat.pw.usda.gov/demos/BatchPrimer3\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), and primers were designed with default parameters. e-PCR validation was performed in silico using TBtools to assess amplification across the PLD family.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003emiRNA prediction and interaction network analysis\\u003c/h2\\u003e\\u003cp\\u003eWheat miRNAs targeting PLDs were predicted using psRNATarget (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.zhaolab.org/psRNATarget/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.zhaolab.org/psRNATarget/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Predicted interactions were filtered by penalty score (\\u0026lt;\\u0026thinsp;3). Interaction networks were visualised in Cytoscape v3.9.1.\\u003c/p\\u003e\\u003cp\\u003e\\u003cb\\u003eGene Ontology and KEGG Pathway Analysis for Functional Annotation.\\u003c/b\\u003e\\u003c/p\\u003e\\u003cp\\u003ePLD gene ontology terms in the wheat genome were identified using Blast2Go software, which gave us detailed protein insights. The GO terms were subsequently classified according to their roles, encompassing cellular components, biological processes, and molecular functions. Furthermore, Blast2Go analysis leveraging the KEGG database, demonstrated PLD's involvement in metabolic pathways.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eExpression profiling using RNA-seq\\u003c/h2\\u003e\\u003cp\\u003eRNA-seq data from PRJEB24686 were downloaded from the European Nucleotide Archive. Clean reads were mapped to the IWGSC RefSeq v1.1 genome. Transcript abundance was quantified in TPM and log₂-transformed. Expression heatmaps, principal component analysis (PCA), and hierarchical clustering dendrograms were generated with TBtools.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003ePlant material and pathogen inoculation\\u003c/h2\\u003e\\u003cp\\u003eTwo wheat (\\u003cem\\u003eTriticum aestivum\\u003c/em\\u003e L.) genotypes, \\u003cb\\u003ePBW 343\\u003c/b\\u003e (Fusarium head blight-resistant) and \\u003cb\\u003eHD 2967\\u003c/b\\u003e (susceptible), were used for experimental validation. Seeds of both cultivars were procured from the Division of Genetics, \\u003cb\\u003eICAR\\u0026ndash;Indian Agricultural Research Institute (IARI), New Delhi, India\\u003c/b\\u003e. Plants were grown in pots containing sterilised soil:sand:FYM (2:1:1) under controlled conditions (22\\u0026deg;C, 16 h light/8 h dark photoperiod).\\u003c/p\\u003e\\u003cp\\u003eAt anthesis, spikes were inoculated with \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e isolate \\u003cb\\u003eFgMS-1 (ITCC No. 3437)\\u003c/b\\u003e, originally obtained from naturally infected wheat spikes from the Indo-Gangetic plains and maintained in the \\u003cb\\u003eIndian Type Culture Collection, ICAR\\u0026ndash;IARI, New Delhi, India\\u003c/b\\u003e. The pathogen was cultured on potato dextrose agar (PDA) plates for 5 days at 25\\u0026deg;C, and conidial suspensions were prepared in sterile distilled water containing 0.01% Tween-20. Conidia concentration was adjusted to \\u003cb\\u003e1 \\u0026times; 10⁵ conidia mL⁻\\u0026sup1;\\u003c/b\\u003e using a haemocytometer. Inoculations were performed by the \\u003cb\\u003epoint-inoculation method\\u003c/b\\u003e, in which 10 \\u0026micro;L of conidial suspension was injected into a central floret of each spike. Control spikes were mock-inoculated with sterile water. Spikes were harvested at \\u003cb\\u003e48 h post-inoculation (hpi)\\u003c/b\\u003e for RNA extraction and downstream analyses.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eMultiplex PCR and semi-quantitative RT-PCR validation\\u003c/h2\\u003e\\u003cp\\u003e\\u003cem\\u003eIn silico\\u003c/em\\u003e mapping identified a putative tae-miR160 complementary binding site within the 5\\u0026prime; UTR-proximal region of the TaPLD transcript, as described in the Results section detailing the experimental validation of PLD\\u0026ndash;miRNA interactions. Two gene-specific primers, Primer 1: \\u003cb\\u003eTaPLD-miR160-F\\u003c/b\\u003e (forward) and Primer 2: \\u003cb\\u003eTaPLD-miR160-R\\u003c/b\\u003e (reverse), were designed flanking this region to enable amplification and subsequent validation of the predicted interaction.\\u003c/p\\u003e\\u003cp\\u003eTotal RNA was extracted using \\u003cb\\u003eTRIzol\\u0026trade; reagent\\u003c/b\\u003e (Invitrogen, USA) and reverse transcribed with the \\u003cb\\u003eRevertAid First Strand cDNA Synthesis Kit\\u003c/b\\u003e (Thermo Fisher Scientific, USA). \\u003cb\\u003eMultiplex PCR\\u003c/b\\u003e was performed using miRNA- and \\u003cem\\u003eTaPLD\\u003c/em\\u003e-specific primers. Semi-quantitative RT-PCR was conducted under the following conditions: \\u003cb\\u003e95\\u0026deg;C for 5 min\\u003c/b\\u003e, followed by \\u003cb\\u003e30 cycles\\u003c/b\\u003e of \\u003cb\\u003e95\\u0026deg;C for 30 s\\u003c/b\\u003e, \\u003cb\\u003e58\\u0026deg;C for 30 s\\u003c/b\\u003e, and \\u003cb\\u003e72\\u0026deg;C for 30 s\\u003c/b\\u003e, with a final extension at \\u003cb\\u003e72\\u0026deg;C for 7 min\\u003c/b\\u003e. PCR products were resolved on \\u003cb\\u003e1.5% agarose gels\\u003c/b\\u003e stained with \\u003cb\\u003eethidium bromide (0.5 \\u0026micro;g mL⁻\\u0026sup1;)\\u003c/b\\u003e and visualised under \\u003cb\\u003eUV light\\u003c/b\\u003e using a gel documentation system.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eIdentification and classification of wheat PLD genes\\u003c/h2\\u003e\\u003cp\\u003eA total of 178 non-redundant PLD proteins were identified in the wheat genome following removal of redundancy from an initial set of 331 candidates. Based on domain composition, these PLDs were classified into three types: 147 C2-dependent (PLDc, PLDc_2, PLD_C, and C2 domains), 18 PX-PH (PH domain), and 13 uncharacterised isoforms (PLDc_N domain) (Supplementary Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e). C2-dependent PLDs contained typical C2 domains involved in Ca\\u0026sup2;⁺ binding and lipid interaction, while PX-PH PLDs carried Phox homology (PX) and Pleckstrin homology (PH) domains implicated in membrane targeting. The uncharacterised group lacked canonical domains, suggesting structural divergence.\\u003c/p\\u003e\\u003cp\\u003eThe physicochemical properties of representative wheat PLDs are summarised in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e (See Supplementary Table S2 for full details). Amino acid lengths ranged from 65 to 1131 aa, and molecular weights varied from 7.1 to 123 kDa. The instability indices (\\u0026lt;\\u0026thinsp;50) indicated stable proteins, while high aliphatic indices (\\u0026gt;\\u0026thinsp;70) suggested thermostability. Grand average of hydropathicity (GRAVY) values were near neutral, reflecting hydrophilicity. Subcellular localisation predictions placed C2 PLDs primarily in the endoplasmic reticulum, chloroplasts, and vacuoles; PX-PH PLDs in the cytoplasm and nucleus; and uncharacterised PLDs in plasma membranes or mitochondria.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eSummary of physicochemical properties of representative wheat phospholipase D (PLD) proteins\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"4\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eProperty\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eRange observed\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eRepresentative values\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eInterpretation\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAmino acid length (aa)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e65\\u0026ndash;1131\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eShort: 163; Medium: 525; Long: 1131\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eWide size variation across isoforms\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eMolecular weight (kDa)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e7.1\\u0026ndash;123\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eSmall: 17.8; Medium: 60.1; Large: 123.2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eIncludes truncated and full-length PLDs\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eIsoelectric point (pI)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e4.05\\u0026ndash;11.7\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eAcidic: 5.7; Neutral: 6.8; Basic: 8.9\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eDistribution across acidic\\u0026ndash;basic range\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eInstability index\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e27\\u0026ndash;49\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eMostly\\u0026thinsp;\\u0026lt;\\u0026thinsp;50\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eProteins predicted to be stable\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAliphatic index\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e63\\u0026ndash;108\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eTypically, \\u0026gt;\\u0026thinsp;70\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eIndicative of thermostability\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eGRAVY (hydropathicity)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e-0.86 \\u0026ndash; +0.40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eNear 0 (avg. -0.35)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eReflects overall hydrophilicity\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSubcellular localisation\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMultiple compartments\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eChloroplast, cytoplasm, vacuole, ER, nucleus\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eSuggests multifunctional roles\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eDomain architecture, motifs, and structural features\\u003c/h2\\u003e\\u003cp\\u003eConserved domain analysis revealed six major domains across the PLDs: C2, PLDc, PLDc_2, PLDc_N, PLD_C, and PH (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e; Supplementary Tables S1 and S3). C2 PLDs contained two HKD (HxKxxxxD) catalytic domains, characteristic of phospholipase activity. PX-PH PLDs possessed domains for phosphoinositide binding, while uncharacterised PLDs lacked HKD or IYIENQFF domains. Motif analysis revealed strong conservation of key catalytic motifs across the wheat PLD family. Specifically, the canonical HKD motif, essential for enzymatic activity, was detected in 144 out of 178 PLDs, while the IYIENQFF motif, another highly conserved signature, was present in 129 PLDs (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e; Supplementary Table S4). By contrast, uncharacterised PLD isoforms were generally deficient in these motifs. A comprehensive scan of conserved motifs identified 165 distinct motifs distributed across 178 PLD protein sequences (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA). Within this repertoire, 60 PLDs contained a single HKD motif, 84 harboured two HKD motifs, and two unique isoforms encoded three distinct HKD motifs. Detailed information on the HKD motif sequences, their positions, and distribution across PLD clusters is presented in Supplementary Table S4 and visually illustrated in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eB.\\u003c/p\\u003e\\u003cp\\u003eSecondary structure analysis revealed that random coils dominated the predicted architecture of wheat PLDs, accounting for ~\\u0026thinsp;45\\u0026ndash;65% of residues across isoforms (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e; Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Extended β-strands were the second most prevalent feature (20\\u0026ndash;27%), followed by α-helices (8\\u0026ndash;16%). Class-specific profiles highlighted distinct structural tendencies (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). PI-independent PLDs contained 16.44% α-helices, 27.24% extended β-strands, 9.89% β-turns, and 46.44% random coils. PIP2-dependent PLDs exhibited markedly reduced α-helical (8.85%) and β-turn (6.23%) content but were enriched in random coils (63.96%), consistent with greater conformational flexibility. By contrast, PIP2-independent PLDs showed an intermediate composition with 16.03% α-helices, 20.40% extended β-strands, 8.07% β-turns, and 55.49% random coils.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eSecondary structure content (%) of PI independent, PIP2 dependent, and PIP2 independent proteins\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"5\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSecondary Structure\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSymbol\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003ePI Independent\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003ePIP2 Dependent\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003ePIP2 Independent\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAlpha Helix\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Hh)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e16.44%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e8.85%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e16.03%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003e310 Helix\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Gg)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePi Helix\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Ii)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBeta Bridge\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Bb)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eExtended Strand\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Ee)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e27.24%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e20.96%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e20.40%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBeta Turn\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Tt)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e9.89%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e6.23%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e8.07%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eBend Region\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Ss)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eRandom Coil\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(Cc)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e46.44%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e63.96%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e55.49%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eAmbiguous Status\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e(?)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eOther States\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.00%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eHomology modelling and structural evaluation\\u003c/h2\\u003e\\u003cp\\u003eTo assess the structural basis of functional divergence among wheat PLDs, representative isoforms from the three major subgroups, PI-independent, PIP2-dependent and, PIP2-independent were subjected to comparative homology modelling followed by validation. Reliable 3D structures were generated for PI-independent and PIP2-dependent isoforms, with GMQE scores ranging from 0.15 to 0.55 and QMEANDisCo values between 0.26 and 0.52, indicating moderate to good model quality. Validation with Ramachandran plots demonstrated that more than 88% of residues fell within the most favoured regions, while only a minor fraction occupied allowed or disallowed regions. This confirms that the predicted models are structurally robust and stereochemically sound (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). These results provide confidence in using the models to interpret functional divergence in substrate binding, membrane anchoring, and catalytic flexibility.\\u003c/p\\u003e\\u003cp\\u003eFor the PI-independent PLD, four candidate templates were identified, with \\u003cem\\u003ephospholipase D alpha 1\\u003c/em\\u003e (25% identity) providing the most reliable model. This structure, resolved at 2.29 \\u0026Aring;, was monomeric and bound both Ca\\u0026sup2;⁺ and 1,2-dioctanoyl-sn-glycero-3-phosphate, reflecting its potential regulatory complexity. The model achieved a GMQE score of 0.55 and a QMEANDisCo score of 0.52\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05, with 88% of residues in favoured Ramachandran regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eA).\\u003c/p\\u003e\\u003cp\\u003eFor the PIP2-dependent PLD, two models were generated, with the \\u003cem\\u003ephospholipase D alpha 1\\u003c/em\\u003e template (17% identity) providing the best coverage. The resulting model, resolved at 1.80 \\u0026Aring;, was monomeric and carried a Ca\\u0026sup2;⁺ ligand, consistent with calcium-mediated regulation. Quality indices (GMQE 0.15; QMEANDisCo 0.45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05) indicated moderate reliability, while the Ramachandran plot placed 88% of residues in favoured regions, just below the ideal 90% benchmark (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eB).\\u003c/p\\u003e\\u003cp\\u003eFor the PIP2-independent PLD, the best-fitting model was derived from \\u003cem\\u003eProtein BAS0735\\u003c/em\\u003e of unknown function (29% identity). The predicted structure (resolution: 2.90 \\u0026Aring;) was also monomeric. Although the GMQE score was low (0.00), the QMEANDisCo score (0.26\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12) and Ramachandran geometry (94% favoured residues) supported the stereochemical validity of the fold (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003eC).\\u003c/p\\u003e\\u003cp\\u003eA direct comparison of these models (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e) highlighted that, despite relatively low sequence identities to known templates, all three PLDs adopted robust monomeric folds and retained ligand-binding features. While the PIP2-independent PLD showed the best stereochemical geometry, the PI-independent PLD achieved the most balanced combination of GMQE, QMEANDisCo, and ligand complexity, suggesting it may play a particularly versatile role in lipid signalling.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eHomology modelling and structural validation of representative wheat PLD subgroups\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"10\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePLD subgroup\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eTemplate (best hit)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eSequence identity (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eResolution (\\u0026Aring;)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eOligomeric state\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eLigands\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003eGMQE\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003eQMEANDisCo (\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003eRamachandran favoured (%)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u003cp\\u003eInterpretation\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePI-independent\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePhospholipase D α1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25.32\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e2.29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eMonomer\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eCa\\u0026sup2;⁺, PA*\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.55\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.52\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e88.07\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u003cp\\u003eReliable model, supported by ligand binding\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePIP2-independent\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eProtein BAS0735 (uncharacterised)\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e29.41\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e2.90\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eMonomer\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eNone\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.00\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.26\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.12\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e93.75\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u003cp\\u003eStrong geometry; low GMQE from weak template\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003ePIP2-dependent\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePhospholipase D α1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e16.93\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.80\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eMonomer\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eCa\\u0026sup2;⁺\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.05\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e\\u003cp\\u003e88.01\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c10\\\"\\u003e\\u003cp\\u003eAcceptable model, near 90% validation cut-off\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003e*PA: 1,2-dioctanoyl-sn-glycero-3-phosphate.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003ePhylogenetic analysis and gene structures\\u003c/h2\\u003e\\u003cp\\u003eA maximum-likelihood phylogenetic tree, constructed using representative isoforms from all three wheat subgenomes (A, B, and D), resolved the 178 PLDs into three major classes: C2-type, PX\\u0026ndash;PH-type, and an unclassified group, each further divided into distinct clades (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eWithin the C2-type class, three subgroups were observed. The PIP2-dependent PLDs (light green and brown branches) formed a compact cluster with short branch lengths, consistent with high sequence conservation. The PIP2-independent PLDs (pink, light blue, yellow, and purple branches) exhibited greater branching heterogeneity, accompanied by relatively weaker bootstrap support. The third subgroup, PI-independent PLDs (dark blue branches), was resolved as a distinct clade separate from the other C2-type members.\\u003c/p\\u003e\\u003cp\\u003eThe PX\\u0026ndash;PH-type PLDs (red branches), corresponding to Ca\\u0026sup2;⁺-independent isoforms lacking the canonical C2 domain, formed a smaller but well-supported clade that displayed relatively long branch lengths.\\u003c/p\\u003e\\u003cp\\u003eThe unclassified group (dark green branches) comprised PLDs that did not consistently cluster within the canonical clades. Several members of this group showed deviations in conserved HKD catalytic motifs or domain composition, and their placement remained basal in the tree.\\u003c/p\\u003e\\u003cp\\u003eExon\\u0026ndash;intron structure analysis revealed considerable variability among wheat PLD isoforms (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e). C2-type PLDs, the most prevalent subgroup, contained between 1 and 10 exons and spanned 2.5\\u0026ndash;9.5 kb, representing the smallest exon range among the PLD classes. PX\\u0026ndash;PH-type PLDs displayed greater structural variability, extending over 14\\u0026ndash;16 kb and comprising 5\\u0026ndash;19 exons. In contrast, unclassified PLDs were generally smaller, ranging from 6 to 8 kb with 3\\u0026ndash;6 exons. Despite broad similarities in motif type, length, and distribution across subgroups, exon number and size were clearly divergent.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eChromosomal distribution\\u003c/h2\\u003e\\u003cp\\u003eChromosomal mapping placed the 178 wheat PLD genes across six of the seven homoeologous groups, with no members detected on chromosome 2 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e). PX\\u0026ndash;PH-type PLDs were exclusively restricted to chromosome 1 (1A, 1B, 1D), indicating a lineage-specific expansion that has not been reported for lipid signalling genes in other cereals. By contrast, C2-type PLDs displayed a broader distribution: PI-independent isoforms were located on chromosomes 1, 3, 4, 5, and 7, with chromosome 3 harbouring only this subtype, whereas PIP2-dependent members were confined to chromosomes 1, 4, 5, and 7.\\u003c/p\\u003e\\u003cp\\u003ePIP2-independent PLDs exhibited a more clustered arrangement, being restricted to chromosomes 4, 5, and 6, with chromosome 4A uniquely containing only PIP2-independent isoforms. Uncharacterised PLDs showed a narrow distribution, restricted to chromosomes 5B and 6 (6A, 6B, 6D). Overall, chromosomes 5 and 6 displayed the highest density of PLDs, including C2-type, PIP2-independent, and uncharacterised subgroups, highlighting hotspots of duplication and diversification.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec21\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eCis-regulatory elements and transcription factor associations\\u003c/h2\\u003e\\u003cp\\u003ePromoter analysis of wheat PLDs identified a wide range of cis-regulatory elements in the 2 kb upstream regions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e; Supplementary Table S5). Core motifs such as the TATA-box and CAAT-box were detected across nearly all isoforms, confirming competence for basal transcription. In addition, promoters contained hormone- and stress-responsive elements, including CGTCA and TGACG motifs (methyl jasmonate), ABRE (abscisic acid), and ARE (anaerobic induction), pointing to regulation by multiple signalling pathways. In total, 45 functionally annotated cis-elements were identified, categorized into five groups: (i) light-responsive elements, (ii) hormone-responsive motifs, (iii) stress-related motifs, (iv) transcription factor\\u0026ndash;binding sites, and (v) other regulatory motifs (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e). Elements lacking annotation or of uncertain function were excluded.\\u003c/p\\u003e\\u003cp\\u003eComplementary analysis of predicted transcription factor binding sites revealed strong associations with five major TF families (q\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.005), BBR-BPC, C2H2 zinc-finger, ERF, LBD, and MYB (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003e; Supplementary Table S6). Among these, C2H2 zinc-finger and ERF TFs were ubiquitous across all PLD types. In contrast, LBD and MYB TFs showed subgroup-specific enrichment, occurring predominantly in PI-independent and PIP2-dependent PLDs, whereas BBR-BPC and MYB were enriched in the PIP2-independent group, with LBD uniquely associated with PX\\u0026ndash;PH-type PLDs.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec22\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eTandem repeats and SSR markers\\u003c/h2\\u003e\\u003cp\\u003eAnalysis of the wheat PLD family revealed that 19 out of 178 isoforms contained tandem repeats (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig10\\\" class=\\\"InternalRef\\\"\\u003e10\\u003c/span\\u003e; Supplementary Table S7). Of these 19, however, 10 belonged to the uncharacterised group lacking the conserved HKD catalytic motif and were excluded from functional interpretation. Among the retained isoforms, TaPLD-1A-1Gam1 and TaPLD-1D-1Gam1 each harboured seven repeats, while TaPLD-1B-1Gam1 contained five repeats. Additional duplications were detected in TaPLD-4B-2Alp1 and TaPLD-4D-2Alp2 (two repeats each), whereas TaPLD-4B-Ams1, TaPLD-4B-Ams2, TaPLD-5D-Del8, and TaPLD-7D-2Alp1 each contained single tandem duplications. Thermodynamic evaluation using enthalpy plots indicated that TaPLD-5D-Del8 and TaPLD-7D-2Alp1 exhibited particularly favourable repeat stability, with enthalpy values close to 1.0, suggestive of enhanced structural robustness (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig10\\\" class=\\\"InternalRef\\\"\\u003e10\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eMining of simple sequence repeats (SSRs) across the wheat PLD family yielded a total of 161 primer pairs (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e; Supplementary Tables S8). Most PLD sequences carried a single patterned pair of SSRs. Among these, 33 primer pairs showed\\u0026thinsp;\\u0026gt;\\u0026thinsp;50% GC content in both forward and reverse primers, which were selected for further Electronic-PCR (E-PCR) analysis. E-PCR validation demonstrated that 30 primer sets successfully amplified 108 of the 178 PLD sequences, with product sizes ranging from 481 to 780 bp. Analysis of SSR motifs using the TBtools SSRMiner tool revealed a diversity of repeat types, including trinucleotide SSRs (TNRs) across 15 loci (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). The number of repeats varied between 5 and 11 per locus, highlighting the polymorphic nature of these SSRs.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eSSR tandem repeat motifs identified in TaPLD genes\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eSequence\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eStart\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eEnd\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eMotif\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eNucleotides (bp)\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eNo. of Repeats\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"6\\\" nameend=\\\"c6\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003eA-genome PLDs\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-1A-13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e132\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e147\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eGAGGAGGAGGAGGAG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-1A-1Zet1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e88\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e103\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCCTCCTCCTCCTCCT\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6A-N1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e251\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e275\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCGGCGGCGGCGGCGGCGGCGGCGG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6A-N2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e269\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e293\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCGGCGGCGGCGGCGGCGGCGGCGG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6A-Del1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e189\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e213\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eAGGAGGAGGAGGAGGAGGAGGAGG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"6\\\" nameend=\\\"c6\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eB-genome PLDs\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-1B-P1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e37\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e52\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCCTCCTCCTCCTCCT\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6B-Del2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e188\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e206\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eGAGGAGGAGGAGGAGGAG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e6\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6B-Del2\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e571\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e586\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCCTCCTCCTCCTCCT\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"6\\\" nameend=\\\"c6\\\" namest=\\\"c1\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eD-genome PLDs\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-4D-1Gam1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e156\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e180\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eGCCGCCGCCGCCGCCGCCGCCGCC\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-5D-Del8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e177\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e192\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eAAGAAGAAGAAGAAG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-5D-Del8\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e461\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e485\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCCACCACCACCACCACCACCACCA\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-5D-1Alp1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e28\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e46\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCCGCCGCCGCCGCCGCCG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e6\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6D-N1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e248\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e281\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eCGGCGGCGGCGGCGGCGGCGGCGGCGGCGGCGG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e11\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-6D-Del1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e189\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e210\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eAGGAGGAGGAGGAGGAGGAGG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e7\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u003cp\\u003eTaPLD-7D-Pr1\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e15\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e30\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eAGGAGGAGGAGGAGG\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cdiv id=\\\"Sec23\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003emiRNA\\u0026ndash;PLD interaction networks\\u003c/h2\\u003e\\u003cp\\u003eTwo wheat miRNAs, tae-miR9664-3p and tae-miR160, were identified as regulators of five PLD isoforms: \\u003cem\\u003eTaPLD-4B-1Bet1\\u003c/em\\u003e, \\u003cem\\u003eTaPLD-4D-1Gam1\\u003c/em\\u003e, \\u003cem\\u003eTaPLD-5A-1Bet1\\u003c/em\\u003e, \\u003cem\\u003eTaPLD-3A-1\\u003c/em\\u003e, and \\u003cem\\u003eTaPLD-3B-1\\u003c/em\\u003e (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig11\\\" class=\\\"InternalRef\\\"\\u003e11\\u003c/span\\u003e; Supplementary Table S9). These isoforms were distributed across chromosomes 3A, 3B, 4B, 4D, and 5A, highlighting widespread regulatory integration across wheat subgenomes.\\u003c/p\\u003e\\u003cp\\u003eBoth miRNAs exhibited strong complementarity with functional domains of the PLD transcripts, consistent with cleavage-based post-transcriptional regulation. Network visualization in Cytoscape revealed distinct regulatory associations: tae-miR9664-3p predominantly targeted PLDs located on chromosomes 4B, 4D, and 5A, whereas tae-miR160 specifically targeted PLDs encoded on chromosomes 3A and 3B. These associations were represented in compact regulatory networks, illustrating direct PLD\\u0026ndash;miRNA interactions relevant to stress signalling pathways.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec24\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eFunctional annotation\\u003c/h2\\u003e\\u003cp\\u003eBlast2GO analysis revealed enrichment of multiple functional categories across PLD isoforms (Supplementary Table S10). For C2-type PLDs, six major GO terms were identified: catalytic activity (GO:003824), lipid metabolic process (GO:0006629), hydroxylase activity (GO:0016787), plasma membrane localisation (GO:0005886), programmed cell death (GO:0012501), and signalling activity (GO:0023052). PX\\u0026ndash;PH type PLDs shared four of these terms with the C2 group, GO:0006629, GO:0016787, GO:0005886, and GO:0023052, indicating overlapping roles in lipid processing and membrane-associated signalling, while lacking enrichment in programmed cell death and catalytic GO terms. Further, the GO terms were categorised into molecular function, biological process, and cellular component ontologies (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig12\\\" class=\\\"InternalRef\\\"\\u003e12\\u003c/span\\u003e). Molecular functions were dominated by catalytic and hydroxylase activities, biological processes were enriched in lipid metabolic and signalling functions, and cellular components were primarily associated with plasma membrane localisation.\\u003c/p\\u003e\\u003cp\\u003eKEGG pathway analysis further reinforced the functional roles of wheat PLD isoforms by mapping their associations with lipid metabolism, particularly glycerophospholipid and ether lipid pathways central to lipid-derived signalling under stress conditions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig13\\\" class=\\\"InternalRef\\\"\\u003e13\\u003c/span\\u003e). In the glycerophospholipid metabolism pathway (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig13\\\" class=\\\"InternalRef\\\"\\u003e13\\u003c/span\\u003eA), PLDs were implicated in critical phospholipid turnover processes. Notably, the enzymatic hydrolysis of \\u003cem\\u003ephosphatidylethanolamine\\u003c/em\\u003e and \\u003cem\\u003ephosphatidylcholine\\u003c/em\\u003e into \\u003cem\\u003e1,2-diacyl-sn-glycerol-3P\\u003c/em\\u003e was highlighted, underscoring the generation of diacylglycerol (DAG) as a key intermediate in lipid signalling and membrane remodelling. The ether lipid metabolism pathway (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig13\\\" class=\\\"InternalRef\\\"\\u003e13\\u003c/span\\u003eB) further demonstrated the contribution of PLDs in the cleavage of \\u003cem\\u003eplasmenylethanolamine\\u003c/em\\u003e to yield \\u003cem\\u003eplasmenic acid\\u003c/em\\u003e, a reaction that connects ether lipid dynamics with membrane restructuring.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec25\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eExpression profiling in resistant and susceptible genotypes\\u003c/h2\\u003e\\u003cp\\u003eExpression profiling revealed that wheat PLD isoforms exhibit distinct tissue-specific and genotype-dependent expression patterns (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig14\\\" class=\\\"InternalRef\\\"\\u003e14\\u003c/span\\u003e), suggesting specialized functional roles. Hierarchical clustering of differentially expressed isoforms under \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e inoculation resolved the 40 PLDs into four major expression groups (A\\u0026ndash;D), reflecting class-specific dynamics.\\u003c/p\\u003e\\u003cp\\u003eGroup A isoforms, including \\u003cem\\u003eTaPLD-5B-\\u003c/em\\u003e(\\u003cspan additionalcitationids=\\\"CR16 CR17 CR18\\\" citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e), \\u003cem\\u003eTaPLD-7A-\\u003c/em\\u003e(\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e), and \\u003cem\\u003eTaPLD-1D-1Gam1\\u003c/em\\u003e, exhibited broad upregulation across the tissues under stress conditions. Their generalized induction pattern indicates a role in maintaining basal stress responsiveness. Group B isoforms, such as \\u003cem\\u003eTaPLD-1A-\\u003c/em\\u003e(\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e) and \\u003cem\\u003eTaPLD-5B-\\u003c/em\\u003e(\\u003cspan additionalcitationids=\\\"CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13\\\" citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e), showed moderate, tissue-specific induction in rachis and spikes, suggesting contributions to localized defense signaling. Group C members, including \\u003cem\\u003eTaPLD-6D-N-\\u003c/em\\u003e(\\u003cspan additionalcitationids=\\\"CR2 CR3\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e) and \\u003cem\\u003eTaPLD-1A-1Gam1\\u003c/em\\u003e, were characterized by strong spikelet-enriched expression, with moderate modulation depending on genotype, indicative of conditional stress-responsive regulation. In contrast, Group D isoforms, such as \\u003cem\\u003eTaPLD-7D-2Alp2\\u003c/em\\u003e, \\u003cem\\u003eTaPLD-4A-\\u003c/em\\u003e(\\u003cspan additionalcitationids=\\\"CR2 CR3\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e), and \\u003cem\\u003eTaPLD-5D-Del-\\u003c/em\\u003e(\\u003cspan additionalcitationids=\\\"CR2 CR3 CR4\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e), displayed sharp genotype-dependent induction, with resistant cultivars showing pronounced upregulation while susceptible genotypes exhibited weak or no induction. These findings point to the adaptive recruitment of PLDs in resistance signaling. Comparative expression analysis under \\u003cem\\u003eF. graminearum\\u003c/em\\u003e infection further highlighted a subset of isoforms that were specifically induced in resistant genotype but remained unchanged or suppressed in susceptible genotype (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig14\\\" class=\\\"InternalRef\\\"\\u003e14\\u003c/span\\u003e), consistent with their conditional activation and genotype-dependent regulation. Overall, the results demonstrated that wheat PLDs are hierarchically organized into coordinated expression modules that integrate tissue-specific functions with inducible defense responses.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec26\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eExperimental validation of PLD\\u0026ndash;miRNA interactions\\u003c/h2\\u003e\\u003cp\\u003eComputational analysis predicted a potential binding site for tae-miR160 within the 5\\u0026prime; UTR\\u0026ndash;proximal region of the \\u003cem\\u003eTaPLD\\u003c/em\\u003e transcript, characterized by complementary base pairing (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig15\\\" class=\\\"InternalRef\\\"\\u003e15\\u003c/span\\u003eA).\\u003c/p\\u003e\\u003cp\\u003eA two-amplicon multiplex PCR assay was designed to simultaneously amplify a representative PLD fragment and a stress-responsive miRNA (tae-miR160) from wheat tissues. Distinct dual amplicons were observed in both resistant and susceptible genotypes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig15\\\" class=\\\"InternalRef\\\"\\u003e15\\u003c/span\\u003eB). Strict controls ensured assay specificity; Milli-Q water (-C), primer (+\\u0026thinsp;CP) and DNA (+\\u0026thinsp;CD) controls yielded no signals. These results demonstrate infection-dependent co-accumulation of PLD and miRNA transcripts, providing wet-lab evidence supporting in silico-predicted PLD\\u0026ndash;miRNA interactions.\\u003c/p\\u003e\\u003cp\\u003eTo further examine PLD\\u0026ndash;miRNA regulation, semi-quantitative RT-PCR with PLD-specific miRNA-primed (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig15\\\" class=\\\"InternalRef\\\"\\u003e15\\u003c/span\\u003eA) reactions was carried out, revealing genotype-dependent expression dynamics. Following infection, TaPLD transcripts were markedly repressed in the susceptible genotype HD 2967, while expression remained stable or slightly elevated in the resistant genotype PBW 343 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig15\\\" class=\\\"InternalRef\\\"\\u003e15\\u003c/span\\u003eC). Densitometric normalization against actin confirmed this infection-dependent repression in susceptible genotypes, consistent with transcriptomic clustering patterns (particularly Group D) identified from RNA-seq data.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study provides the first comprehensive characterisation of the phospholipase D (PLD) gene family in wheat and establishes their roles in defence against \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e, the causal agent of Fusarium head blight (FHB). By integrating genome-wide identification, structural and regulatory analyses, expression profiling, and experimental validation, we uncovered a dynamic miRNA\\u0026ndash;TF\\u0026ndash;PLD signalling axis central to wheat immunity.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec28\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eIdentification and classification of wheat PLD genes\\u003c/h2\\u003e\\u003cp\\u003eThe members of PLD identified in wheat were categorized into three types, including a notable group of uncharacterized members that do not possess canonical catalytic domains. This classification aligns with findings from other cereal species, where the architecture of protein domains and the conservation of sequences help define PLD clades (Zhao et al., 2010a; Hong et al., 2016). The significant abundance of PLDs in wheat, surpassing the number found in many other plant species (Qin and Wang, 2002; Zhao et al., 2012; Guo et al., 2024), underscores the remarkable complexity of the wheat genome. This abundance also suggests a potentially greater functional diversification of PLDs within cereals, emphasizing their significance in plant biology and adaptations.\\u003c/p\\u003e\\u003cp\\u003eThe physicochemical profiling of various isoforms demonstrated significant variations in amino acid length and molecular weight, highlighting the complexity of these proteins. Notably, the PX-PH type PLDs exhibited longer average chain lengths of around 700 amino acids, leading to correspondingly higher molecular weights. Isoelectric point (pI) analyses revealed that PX-PH PLDs typically cluster around neutral pH, while many uncharacterized PLDs have more alkaline pI values. This intriguing variation suggested functional differences in subcellular activities and protein\\u0026ndash;protein interactions, emphasizing the need for further exploration.\\u003c/p\\u003e\\u003cp\\u003eImportantly, the instability indices indicated that all PLDs are stable under physiological conditions (Gasteiger et al., 2005), while high aliphatic indices suggested strong thermostability and GRAVY values near zero pointed to a hydrophilic nature. This unique combination of stability, thermostability, and hydrophilicity positions these PLDs as highly adaptable, capable of functioning efficiently in diverse cellular compartments. Indeed, predictions about their subcellular localization suggested their presence in critical areas such as the cytoplasm, vacuole, endoplasmic reticulum, chloroplast, nucleus, peroxisome, plasma membrane, and other organelles. This extensive localization underscores the multifunctional roles of PLDs in mediating stress responses, enhancing membrane dynamics, and facilitating signal transduction (Li et al., 2009; Testerink and Munnik, 2011). Such multifaceted capabilities make PLDs essential players in cellular processes and highlight their importance in biological systems.\\u003c/p\\u003e\\u003cp\\u003eThese properties are consistent with analogous findings from other plant species. For example, in \\u003cem\\u003eCorchorus\\u003c/em\\u003e spp., PLDs were reported with aliphatic indices in the range 71\\u0026ndash;87, negative GRAVY values (i.e. hydrophilic), and instability indices indicating stable proteins in both \\u003cem\\u003eC. capsularis\\u003c/em\\u003e and \\u003cem\\u003eC. olitorius\\u003c/em\\u003e (Islam et al. 2022). Similarly, in jute, molecular weights of PLD-β1 and PLD-ζ1 approached\\u0026thinsp;~\\u0026thinsp;88\\u0026ndash;122 kDa, paralleling the upper range observed in wheat PLDs (Islam et al. 2022).\\u003c/p\\u003e\\u003cp\\u003eTaken together, this expanded and diversified PLD family in wheat, together with physicochemical traits suggestive of stability and versatility, underpins our hypothesis that PLDs play a significant role in wheat\\u0026rsquo;s defence responses, particularly against Fusarium head blight.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec29\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eDomain structure and motif conservation\\u003c/h2\\u003e\\u003cp\\u003eThe in-depth analysis of the domain architecture of wheat PLDs revealed six critical conserved domains. Notably, the majority of C2-type PLDs possessed two highly conserved HKD (HxKxxxxD) catalytic domains, a hallmark of their phospholipase D activity. In contrast, PX\\u0026ndash;PH PLDs were equipped with unique phosphoinositide-binding PX and PH domains, which allow them to effectively target membranes rich in phosphatidylinositol phosphates. These findings highlighted the sophisticated mechanisms underlying PLD functionality in cereals. A subset of uncharacterised PLDs lacked both HKD and IYIENQFF motifs, suggesting that they may have diverged from canonical catalytic roles or undergone pseudogenisation.\\u003c/p\\u003e\\u003cp\\u003eDespite overall sequence divergence, motif analysis confirmed strong conservation of core functional residues across most isoforms. Specifically, the HKD motif found in 144 PLDs and the IYIENQFF motif present in 129 PLDs are universally recognized as essential for catalytic activity and substrate binding in eukaryotic PLDs (Qin et al. 2002; Jang et al. 2019). In contrast, motif deficiency in uncharacterised PLDs may indicate a shift towards non-enzymatic or regulatory roles, a phenomenon also noted in other plant gene families where divergence leads to subfunctionalisation (Panchy et al. 2016).\\u003c/p\\u003e\\u003cp\\u003ePredicted secondary structure analysis indicated a predominance of random coils interspersed with α-helices and β-strands, a feature consistent with conformational flexibility. This structural plasticity, coupled with the stable homology models generated for representative isoforms, likely facilitates PLD interactions with diverse lipid substrates and protein partners, thereby supporting their multifunctional roles in stress signalling, membrane trafficking, and lipid metabolism (Hong et al. 2016; Wang 2020).\\u003c/p\\u003e\\u003cp\\u003eTogether, these findings establish that while wheat PLDs exhibit remarkable sequence diversification, the core catalytic machinery is strongly conserved, underscoring their central role in lipid-mediated signalling and adaptive responses.\\u003c/p\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eHomology modelling and structural evaluation\\u003c/h3\\u003e\\n\\u003cp\\u003eThe analyses consistently demonstrated resilient monomeric structures, well-conserved ligand-binding sites, and stable conformations, highlighting their reliability even when overall sequence similarity to template structures was comparatively low. This robustness underscores the significance of our findings in PLD structural biology.\\u003c/p\\u003e\\u003cp\\u003eThe PLDα1 model of the PIP2-dependent PLD protein stood out due to its superior coverage, making it highly significant. Notably, this model features a calcium ion ligand, which directly supports the calcium-dependent catalytic mechanism characteristic of C2-type PLDs (Qin et al. 2002; Jang et al. 2019). The evaluation metrics convincingly demonstrated the model's reliability, with elevated values signifying enhanced structural accuracy. While the Ramachandran plot revealed that the residues were slightly below the preferred\\u0026thinsp;\\u0026gt;\\u0026thinsp;90% threshold, the overall assessment deemed the model both structurally acceptable and highly informative.\\u003c/p\\u003e\\u003cp\\u003eThe BAS0735-derived model for the PIP2-independent PLD protein stood out with the highest coverage and was selected for further exploration. While the GMQE score may raise concerns about structural limitations, the QMEANDisCo global score highlighted solid coverage and environmental consistency. Most notably, the Ramachandran plot revealed that the majority of residues were positioned in favoured regions, exceeding the 90% benchmark and reinforcing the model's credibility. This compelling evidence underscored the model's potential for reliable analysis.\\u003c/p\\u003e\\u003cp\\u003eAnother isoform, independent of PI, also resulted in a PLDα1-based model that offered exceptional coverage, featured ligands for both calcium ions and 1,2-dioctanoyl-sn-glycero-3-phosphate. The evaluation metrics strongly affirmed the structural validity of this model. Despite its Ramachandran plot indicating that most residues were within favoured regions, it slightly fell short of the optimal cut-off. However, the model's overall fold stability and effective ligand retention rendered it a highly acceptable and promising candidate for further exploration.\\u003c/p\\u003e\\u003cp\\u003eCollectively, these homology models provided strong evidence that, despite low sequence identity to templates, wheat PLDs maintain conserved catalytic folds, monomeric stability, and key ligand-binding capacities. Subtle subgroup-specific differences in GMQE, QMEANDisCo, and Ramachandran metrics highlighted potential divergence in structural robustness and ligand interaction, supporting the functional diversification of PLDs in wheat. These models thus offer a valuable framework for future biochemical and functional studies, aligning with recent advances in structure-guided characterisation of plant PLDs (Hong et al. 2016; Wang 2020; Guo et al. 2024).\\u003c/p\\u003e\\u003cdiv id=\\\"Sec31\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003ePhylogenetic analysis and gene structures\\u003c/h2\\u003e\\u003cp\\u003eThe phylogeny revealed a polyphyletic pattern, with PLDs forming multiple well-supported clusters that corresponded to their domain composition and motif signatures. Within these clusters, the presence of hallmark motifs\\u0026mdash;HKD (HxKxxxxD) and IYIENQFF\\u0026mdash;was consistently observed, confirming the catalytic identity of bona fide PLDs and facilitating the exclusion of uncharacterised or unrelated proteins from the family.\\u003c/p\\u003e\\u003cp\\u003eThis grouping strategy effectively partitioned wheat PLDs into clades with high internal homology, reflecting shared structural and functional traits. Criteria such as protein length, motif arrangement, molecular size, and exon\\u0026ndash;intron organisation were decisive in defining these subfamilies. Notably, C2-type PLDs typically contained 2\\u0026ndash;10 exons, while PX\\u0026ndash;PH PLDs possessed 6\\u0026ndash;20 exons, consistent with patterns previously reported in rice (\\u003cem\\u003eOryza sativa\\u003c/em\\u003e), where C2-PLDs and PX\\u0026ndash;PH PLDs characteristically carried\\u0026thinsp;~\\u0026thinsp;10 and ~\\u0026thinsp;20 exons, respectively (Li et al. 2009; Pinosa et al. 2013; Zhao et al. 2010a).\\u003c/p\\u003e\\u003cp\\u003eInterestingly, our analysis also revealed that some wheat PLDs exhibit reduced exon numbers, likely reflecting intron loss through splicing events. Despite this variability, exon arrangement remained highly conserved within groups, with splicing junctions aligning across orthologous sequences. This structural conservation reinforces the evolutionary stability of PLDs, while intron variation may represent an important mechanism for functional diversification and regulatory innovation.\\u003c/p\\u003e\\u003cp\\u003eOverall, the integration of phylogenetic clustering and gene structure analysis provides robust evidence of conserved lineage-specific features among wheat PLDs, while also revealing subtle divergence that may underpin functional specialisation. These findings highlight both the structural integrity and evolutionary plasticity of the PLD gene family in cereals.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec32\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eExpansion and diversification of PLDs on wheat chromosomes\\u003c/h2\\u003e\\u003cp\\u003eThe chromosomal distribution of wheat PLDs revealed a non-uniform yet widespread pattern across the genome. Of the 178 non-redundant PLD genes, members were distributed across six of the seven wheat chromosomes, except chromosome 2, which lacked any PLD representatives. Interestingly, PX\\u0026ndash;PH subtype PLDs were exclusively localised on chromosome 1, whereas C2-type PLDs were distributed across nearly all chromosomes except for two specific cases. This pattern underscores the differential chromosomal retention and expansion of PLD subfamilies, shaped by the evolutionary dynamics of the allohexaploid wheat genome.\\u003c/p\\u003e\\u003cp\\u003eThe analysis revealed that most phospholipase D (PLD) genes in wheat likely originated from segmental duplication events. This finding aligns with observations made in other large gene families within polyploid cereals (Panchy et al. 2016; Qiao et al. 2019). While tandem duplications may have led to the localized clustering of C2-type PLDs, segmental duplications across the A, B, and D subgenomes appear to be the primary force driving the expansion of this gene family. These trends are similar to those seen in rice and tomato, where members of the PLD gene family also exhibit evidence of duplication-driven diversification (Zhao et al. 2010a; Guo et al. 2024).\\u003c/p\\u003e\\u003cp\\u003eThe analysis also emphasized the conservation of PLD loci among wheat, which has a significantly larger number of syntenic PLD pairs due to its allohexaploid complexity and the selective retention of stress-responsive genes. Such retention is thought to provide functional robustness under biotic and abiotic stress conditions, aligning with the emerging view that lipid signalling pathways are subject to positive selection in crop genomes (Hong et al. 2016; Wang 2020).\\u003c/p\\u003e\\u003cp\\u003eOverall, the enrichment specific to certain chromosomes, the absence on chromosome 2, and significant duplication-driven diversification indicate that PLDs in wheat have experienced both expansion and structural reorganization, facilitating functional plasticity and potential neofunctionalization. These results offer new insights into the evolutionary dynamics of lipid-signalling gene families in polyploid cereals.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec33\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eRegulatory complexity through cis-elements and transcription factors\\u003c/h2\\u003e\\u003cp\\u003ePromoter analysis of wheat PLDs uncovered a diverse array of cis-regulatory elements and transcription factors that respond to various developmental and environmental signals, highlighting the role of PLDs as key mediators in hormonal regulation and environmental adaptation.\\u003c/p\\u003e\\u003cp\\u003eThe composition of cis-elements significantly indicated the functional specialization among the different subfamilies of PLD. For PX\\u0026ndash;PH type PLDs, promoter regions carried the GC-motif, conferring anoxic inducibility, enabling responses to low oxygen stress, and the Box-4 element, associated with light-responsive regulation (Maruyama et al. 2014). In C2-type PLDs, promoters harboured ABRE (ABA-responsive element), ARE (anaerobic responsive element), and CAT-box (meristem expression) motifs, suggesting roles in ABA signalling, hypoxic stress tolerance, and developmental regulation (Nakashima and Yamaguchi-Shinozaki 2013; Schmidt et al. 1990). In contrast, PI-independent PLDs encompassed elements linked to plant growth-promoting hormones such as the TCA-element (salicylic acid responsiveness), alongside a diverse set of light-responsive motifs (LTR, G-box, TGA-motif, GA-motif, TCT-motif, Box-4). Additional motifs included the A-box (general cis-regulatory element) and the O2-site, traditionally associated with regulation of zein metabolism in cereals (Schmidt et al. 1990).\\u003c/p\\u003e\\u003cp\\u003eThe predicted binding sites for transcription factors (TFs) underscore the intricate complexity involved. Members of the C2H2 zinc finger and ERF (ethylene-responsive factor) families have been frequently associated with PLD promoters, highlighting their roles in general stress signaling pathways. In particular, the ERF transcription factor inhibited the growth of FHB in wheat crops by interacting with both the GCC box and non-GCC cis-elements in the promoter region (Gupta et al. 2023). Subgroup-specific associations were also evident: MYB, LBD (LATERAL ORGAN BOUNDARIES DOMAIN), and BBR-BPC (BARLEY B RECOMBINANT/BASIC PENTACYSTEINE) families showed enriched interactions with distinct PLD subtypes. While MYB and NAC TFs have previously been linked to lipid metabolism and stress responses in plants (Wang 2020; Hong et al. 2016), our identification of ERF and BBR-BPC regulators extends the known regulatory landscape of PLDs. The BBR-BPC family is particularly noteworthy as it is involved in seed and flower development, regulates homeotic (HOX) genes, and participates in brassinosteroid signalling, a pathway that has been shown to restrict the growth of \\u003cem\\u003eFusarium\\u003c/em\\u003e pathogens (Gupta et al. 2016; Nakashima and Yamaguchi-Shinozaki 2013). This suggests that PLD regulation is intimately connected with canonical stress-related transcription factors (TFs) as well as lipid signaling, which is intricately integrated with developmental and hormonal signaling networks that modulate both pathogen defense and growth.\\u003c/p\\u003e\\u003cp\\u003eTaken together, these findings underscore the regulatory diversity of wheat PLDs, showing how cis-elements and transcription factor interactions enable fine-tuned responses to hormones, environmental stresses, and developmental cues. The integration of ABA, JA, ethylene, and light signalling pathways with lipid-mediated responses positions PLDs as critical regulatory nodes in stress adaptation and growth regulation.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec34\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eTandem repeats\\u003c/h2\\u003e\\u003cp\\u003eTandem repeats within protein-coding sequences are recognised as important drivers of protein diversity, stability, and regulatory capacity. In wheat PLDs, the analysis revealed tandem repeat regions in specific isoforms, notably TaPLD-5D-Del8 and TaPLD-7D-2Alp1, which were associated with elevated expression levels compared to other family members. The presence of these repeats suggests that they may contribute to enhanced protein synthesis efficiency and to greater structural and functional versatility.\\u003c/p\\u003e\\u003cp\\u003eSuch repeat-mediated amplification is thought to influence transcriptional regulation and translation dynamics, ultimately increasing protein abundance under certain developmental or stress conditions. This observation highlights the role of tandem repeats not only in shaping the genetic architecture of PLDs but also in facilitating the functional diversification of the wheat genome, consistent with the broader importance of repeat sequences in the evolution of stress-associated gene families (Gemayel et al. 2010; Moxon and Wills 1999).\\u003c/p\\u003e\\u003cp\\u003eTogether, these findings emphasise the adaptive significance of tandem repeats in modulating PLD gene expression, pointing to potential molecular mechanisms by which wheat fine-tunes lipid signalling capacity in response to environmental challenges.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\n\\u003ch3\\u003eTranslational potential of SSR markers\\u003c/h3\\u003e\\n\\u003cp\\u003eSSR markers designed from PLD sequences add a translational dimension to our study. Of the 161 primer pairs developed, 30 amplified PLDs across 108 loci in silico. These markers could be directly applied in marker-assisted selection to track PLD alleles associated with FHB resistance. Few lipid-focused studies have coupled genome-wide analysis with marker development; thus, this resource distinguishes our work from previous lipid metabolism reports (Troncoso-Ponce et al., 2016; Pan et al., 2013), as well as from broader genome-wide lipid gene analyses in crops such as soybean and flax that did not incorporate marker resources (Huang et al., 2021; Ding et al., 2020a; Shankar et al., 2016).\\u003c/p\\u003e\\n\\u003ch3\\u003emiRNA-mediated regulation of PLDs\\u003c/h3\\u003e\\n\\u003cp\\u003eA particularly novel outcome of this study is the identification and experimental validation of miRNA regulation of wheat PLDs. Two miRNAs, tae-miR9664-3p and tae-miR160, were predicted and experimentally confirmed to target PLDs during \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e infection. Multiplex PCR and semi-quantitative RT-PCR assays revealed infection-dependent co-expression and genotype-specific modulation, with resistant and susceptible cultivars displaying contrasting regulation patterns.\\u003c/p\\u003e\\u003cp\\u003emiR160 has long been implicated in auxin signalling and stress adaptation (Mallory et al. 2005), targeting auxin response factors (ARFs) to fine-tune hormone-dependent growth and defence pathways. Notably, tae-miR160 has been associated with resistance against \\u003cem\\u003eMagnaporthe oryzae\\u003c/em\\u003e and \\u003cem\\u003ePhytophthora infestans\\u003c/em\\u003e (Wu et al. 2017), underscoring its dual roles in auxin-mediated development and pathogen defence. miR9664, on the other hand, was originally reported in rice blast resistance (Campo et al. 2013) and more recently linked to FHB resistance in wheat (Kumar et al. 2021; Gupta et al. 2023).\\u003c/p\\u003e\\u003cp\\u003eOur findings extend this knowledge by demonstrating, for the first time, that tae-miR9664-3p and tae-miR160 directly regulate wheat PLDs, thereby linking miRNA-mediated post-transcriptional control with phospholipase-mediated lipid defence signalling. This establishes a new regulatory layer in wheat immunity, integrating miRNA activity into lipid-based defence pathways critical for resistance to fungal pathogens.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec37\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eFunctional annotation\\u003c/h2\\u003e\\u003cp\\u003eFunctional annotation of wheat PLDs using GO and KEGG analyses revealed their multifaceted contributions to plant metabolism, signalling, and stress adaptation. GO categorisation linked PLDs to diverse biological processes, including lipid catabolism, cellular signalling, and programmed cell death, consistent with their role in integrating metabolic and defence pathways.\\u003c/p\\u003e\\u003cp\\u003eKEGG pathway mapping provided more specific insights, highlighting strong associations of wheat PLDs with ether lipid metabolism and glycerophospholipid metabolism, both of which are critical for cellular membrane dynamics and stress responses. PLDs were assigned to the enzymatic category EC 3.1.4.4 (phospholipase D), confirming their catalytic role in hydrolysing terminal phosphodiester bonds of glycerophospholipids (Wang and Wang 2001).\\u003c/p\\u003e\\u003cp\\u003eWithin glycerophospholipid metabolism, PLDs were predicted to catalyse the conversion of phosphatidylethanolamine to 1,2-diacyl-sn-glycerol-3P and phosphatidylcholine to 1,2-diacyl-sn-glycerol-3P. These reactions yield phosphatidic acid (PA), a key lipid second messenger that mediates stress-induced signalling cascades (Hong et al. 2016; Testerink and Munnik 2011). The integration of PLDs into these metabolic pathways highlights their importance in lipid-derived signal generation, membrane remodelling, and hormone-mediated defence responses.\\u003c/p\\u003e\\u003cp\\u003eNotably, the enrichment of ether lipid and glycerophospholipid pathways aligns with recent reports that PLDs contribute to cellular signalling and membrane trafficking under abiotic and biotic stress conditions. Their capacity to link primary metabolism with defence-associated signalling networks underscores the functional versatility of wheat PLDs.\\u003c/p\\u003e\\u003cp\\u003eOverall, these annotations illustrate that PLDs in wheat are not limited to basal lipid hydrolysis but act as central regulators of lipid metabolism and stress signalling, broadening our understanding of their physiological and adaptive significance.\\u003c/p\\u003e\\u003cdiv id=\\\"Sec38\\\" class=\\\"Section3\\\"\\u003e\\u003ch2\\u003eDivergent expression between resistant and susceptible genotypes\\u003c/h2\\u003e\\u003cp\\u003eRNA-seq expression profiling revealed a pronounced divergence in phospholipase D (PLD) expression between wheat near-isogenic lines (NILs) differing in resistance to \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e. In the susceptible genotype 2890, selective repression of PLDs is predicted to disrupt phosphatidic acid (PA)-mediated signalling, potentially weakening downstream defence pathways and exacerbating vulnerability to infection. This observation aligns with previous reports showing transcriptional suppression of lipid transfer proteins in susceptible wheat lines under fungal attack, highlighting a conserved weakness in lipid-mediated defence networks (Molina and Garc\\u0026iacute;a-Olmedo 1997). Extending these findings, our study identifies PLDs as critical determinants of genotype-specific resistance.\\u003c/p\\u003e\\u003cp\\u003eIsoform-specific expression patterns revealed functional divergence among PLD groups. Group A isoforms exhibited high basal expression, consistent with housekeeping roles in growth, development, and basal cellular processes (Bargmann and Munnik 2006). A moderate decline in the susceptible genotype suggests these isoforms primarily support developmental processes rather than acute defence responses. Group B isoforms showed moderate, tissue-specific induction in rachis and spike tissues, paralleling observations in \\u003cem\\u003eBrassica napus\\u003c/em\\u003e, where certain PLDs demonstrate minimal stress responsiveness (Li et al. 2013). Group C members maintained constitutive, spikelet-enriched expression across genotypes, similar to stably expressed tomato PLDs (Guo et al. 2024), indicating roles in lipid metabolism and structural maintenance rather than direct pathogen-triggered defence. Group D isoforms displayed sharp genotype-dependent induction, reminiscent of soybean phospholipase C transcript dynamics under osmotic stress (Chen et al. 2020a). The downregulation of Group D PLDs in the susceptible genotype suggests impaired PA signalling, potentially compromising the activation of downstream defence cascades.\\u003c/p\\u003e\\u003cp\\u003eThe specific suppression of Group D PLDs supports the hypothesis that infection-induced repression of PA biosynthesis undermines lipid-mediated defence networks. Methodological choices enhanced the reliability of these conclusions. Focusing on a single RNA-seq dataset (PRJEB24686) minimized platform-specific artefacts and provided a consistent reference for isoform-level comparisons. Semi-quantitative RT-PCR validation corroborated the RNA-seq trends, confirming that Group D PLD repression is a reproducible, biologically meaningful response.\\u003c/p\\u003e\\u003cp\\u003eCollectively, these findings indicate that selective transcriptional repression of PLDs in susceptible wheat genotypes disrupts PA-mediated signalling, amplifying susceptibility to \\u003cem\\u003eF. graminearum\\u003c/em\\u003e. In contrast, maintenance of PLD expression in resistant genotypes preserves signalling capacity and supports effective defence. Wheat PLDs therefore function as hierarchically organized, coordinated modules that integrate tissue-specific roles with inducible defence responses, underscoring their potential as molecular markers for breeding Fusarium-resistant cultivars.\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec39\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003eExperimental validation of PLD\\u0026ndash;miRNA interactions\\u003c/h2\\u003e\\u003cp\\u003eExperimental validation confirmed that PLD transcripts co-accumulate with stress-responsive miRNAs, notably tae-miR160, during \\u003cem\\u003eF. graminearum\\u003c/em\\u003e infection. Multiplex PCR and stem-loop RT-PCR assays revealed genotype-specific expression patterns; resistant cultivars maintained stable PLD transcript levels, whereas susceptible ones exhibited marked repression. These results support a model in which miRNA regulation functions as a molecular switch that fine-tunes PLD-mediated lipid signalling under pathogen stress. This finding aligns with earlier reports demonstrating that suppression of phospholipases compromises host immunity and enhances disease susceptibility in soybean (Chen et al. 2020b) and rice (Zhao et al. 2010b). The present study provides the first experimental evidence in wheat that miRNA-PLD crosstalk contributes to FHB resistance, thereby revealing a novel regulatory layer within the lipid-signalling network and offering new biotechnological targets for crop protection.\\u003c/p\\u003e\\u003cp\\u003eRecent systems-level analyses further contextualise these results. Rocher et al. (2024) identified a conserved gene regulatory network underlying wheat susceptibility to \\u003cem\\u003eF. graminearum\\u003c/em\\u003e and demonstrated that fungal core effectors target host master regulators. Additionally, Muslu et al. (2025) characterised non-coding regulatory elements, including miRNAs and lncRNAs, associated with FHB resistance. Collectively, these studies reinforce the centrality of post-transcriptional regulation in wheat defence. Our findings extend these models by revealing a miRNA-PLD module as an additional layer of defence control that integrates lipid signalling and gene regulatory networks.\\u003c/p\\u003e\\u003cp\\u003eMoreover, PLD has been established as a pivotal mediator of lipid-derived defence signalling (Gonz\\u0026aacute;lez-Mendoza 2021), and its regulation by miRNAs under abiotic stress (Ding 2013) underscores the evolutionary conservation of this mechanism. Together, these insights suggest that miRNA-guided modulation of PLD activity constitutes a versatile adaptive strategy linking membrane lipid remodelling to immune activation.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThis study presents the first comprehensive genome-wide analysis of the phospholipase D (PLD) gene family in hexaploid wheat, significantly expanding our understanding of lipid signalling in cereal defence. We systematically characterized 178 \\u003cem\\u003eTaPLD\\u003c/em\\u003e genes, revealing their diverse structural features, complex regulatory landscapes involving specific transcription factors and cis-elements, and distinct genomic distribution shaped by duplication events.\\u003c/p\\u003e\\u003cp\\u003eA key finding is the divergent expression of specific \\u003cem\\u003eTaPLD\\u003c/em\\u003e isoforms between FHB-resistant and susceptible wheat genotypes, underscoring their functional importance in the defence response. Crucially, we identified and experimentally validated a novel regulatory axis where a miRNA, tae-miR160, directly target \\u003cem\\u003eTaPLD\\u003c/em\\u003e transcripts. This post-transcriptional regulation provides a mechanistic explanation for the suppressed PLD-mediated signalling observed in susceptible plants, highlighting a previously unexplored layer of immune modulation in wheat.\\u003c/p\\u003e\\u003cp\\u003eThe functional annotation linking PLDs to critical lipid signalling pathways, coupled with the development of SSR markers from PLD loci, adds a practical dimension to our work. In summary, our results establish PLDs as central players in wheat's immune signalling and unveil a miRNA-PLD module that is critical for FHB resistance. These insights and the molecular resources generated herein provide a solid foundation for future functional studies and biotechnological strategies aimed at enhancing disease resistance in wheat.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eFunding\\u003c/h2\\u003e\\u003cp\\u003eThis research was supported by the Indian National Science Academy (INSA), New Delhi, under the Visiting Scientist Fellowship awarded to the first author at the International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi (Grant No. INSA/SP/VSP-59/2019\\u0026ndash;20/), for his PhD research leading to these results. No additional external funding, grants, or commercial support was received specifically for the preparation of this manuscript.\\u003c/p\\u003e\\u003cp\\u003eThe first author gratefully acknowledges the support of the Director, ICAR \\u0026ndash; National Institute of Biotic Stress Management (NIBSM), Raipur, India, for approving his INSA Visiting Scientist Programme 2019 at the International Centre for Genetic Engineering and Biotechnology, New Delhi, India, under fellowship support from the Indian National Science Academy (INSA), New Delhi.\\u003c/p\\u003e\\u003cp\\u003eCompeting Interests\\u003c/p\\u003e\\u003cp\\u003eThe authors declare that they have no relevant financial or non-financial interests to disclose.\\u003c/p\\u003e\\u003cp\\u003eData Availability\\u003c/p\\u003e\\u003cp\\u003eThe datasets generated and/or analysed during the current study are available in the supplementary materials accessible within the manuscript.\\u003c/p\\u003e\\u003cp\\u003eAdditional datasets generated and/or analysed during the current study are available from the corresponding author upon reasonable request.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contributions\\u003c/h2\\u003e\\u003cp\\u003eLalit Kharbikar conceived the study, coordinated the research, performed data analyses and drafted the manuscript Arti Shanware contributed to experimental design, data validation, and interpretation of molecular results. Piyush Ghoshe and Shweta Nandanwar carried out bioinformatics analyses, including gene identification, motif/domain analysis, and phylogenetics. Malkhan Gurjar and Mahender Saharan contributed to pathogen inoculation experiments and disease phenotyping. Pankaj Sharma and Pramod Rai assisted in data curation, and manuscript revision. Simon Edwards provided critical review, editorial input, statistical analyses and international collaboration support. Neeti Sanan-Mishra co-supervised the project, contributed to miRNA prediction and validation experiments, and revised the manuscript. All authors read and approved the final manuscript.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAlisaac E, Mahlein A-K (2023) Fusarium head blight on wheat: biology, detection, and integrated management. 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Plant Physiol 163:896\\u0026ndash;906. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1104/pp.113.222091\\u003c/span\\u003e\\u003cspan address=\\\"10.1104/pp.113.222091\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eQiao X, Li Q, Yin H, Qi K, Li L, Wang R, Liu X, Liu S, Zhou Y, Tian Y, Zhang S, Zhang J, Liu X, Wang Y, Liu J (2019) Gene duplication and evolution in recurring polyploidization\\u0026ndash;diploidization cycles in plants. 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Plant Cell 16:151\\u0026ndash;167. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1105/tpc.017707\\u003c/span\\u003e\\u003cspan address=\\\"10.1105/tpc.017707\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZhao J, Duan X, Hua Y, Tang W, Guo W, Zhao Y, Sun X, Li Z (2010a) Genome-wide identification and expression profiling of the phospholipase D gene family in \\u003cem\\u003eOryza sativa\\u003c/em\\u003e. Plant Mol Biol Rep 28:582\\u0026ndash;593. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1007/s11105-009-0181-4\\u003c/span\\u003e\\u003cspan address=\\\"10.1007/s11105-009-0181-4\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZhao J, Wang T, Wang M, Liu Y, Ouyang B (2010b) Phospholipase D is required for rice defence against \\u003cem\\u003eMagnaporthe oryzae\\u003c/em\\u003e. Plant Sci 178:297\\u0026ndash;304. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1016/j.plantsci.2010.02.008\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.plantsci.2010.02.008\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eZhao J, Zhou C, Yang J, Ling Y, Liu X, Wan H, Liu S, Wang G (2012) Genome-wide identification and expression profiling of phospholipase D genes in soybean (\\u003cem\\u003eGlycine max\\u003c/em\\u003e) reveal their potential roles in stress responses. BMC Plant Biol 12:168. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1186/1471-2229-12-168\\u003c/span\\u003e\\u003cspan address=\\\"10.1186/1471-2229-12-168\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Wheat, phospholipase D, Fusarium head blight, miRNA, lipid signalling, SSR\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7877570/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7877570/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003ePhospholipase D (PLD)-mediated lipid signalling is a crucial component of plant defence responses. However, the PLD gene family remains poorly characterised in hexaploid wheat (\\u003cem\\u003eTriticum aestivum\\u003c/em\\u003e L.), particularly regarding its role in resistance to Fusarium head blight (FHB), a devastating fungal disease. This study identified 178 non-redundant PLD genes in the wheat genome and comprehensively analysed their phylogenetic relationships, conserved domains, chromosomal distribution, promoter cis-elements, and expression profiles under \\u003cem\\u003eFusarium graminearum\\u003c/em\\u003e infection. These PLDs were classified into C2-dependent, PX–PH, and uncharacterised types. Promoter analysis revealed stress- and hormone-responsive cis-elements, while expression profiling demonstrated genotype-dependent induction patterns, with several PLDs strongly upregulated in the resistant genotype. We experimentally validated that tae-miR160 targets specific \\u003cem\\u003eTaPLD\\u003c/em\\u003e transcripts, revealing a post-transcriptional regulatory layer. Furthermore, polymorphic SSR markers were developed from PLD loci for potential use in marker-assisted breeding. This study provides the first evidence of a miRNA–PLD regulatory network in wheat defence and highlights PLDs as critical mediators of FHB resistance.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Genome-wide identification of phospholipase D gene family in wheat reveals miRNA-regulated module underlying FHB resistance\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-11-10 10:44:47\",\"doi\":\"10.21203/rs.3.rs-7877570/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"3cef4f41-ccd5-4059-8808-ffddf24dd406\",\"owner\":[],\"postedDate\":\"November 10th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-11-15T13:21:54+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-11-10 10:44:47\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7877570\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7877570\",\"identity\":\"rs-7877570\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}