Genome-wide identification of the MCA gene family and its role in resistance to powdery mildew in wheat

Abstract

Background

Metacaspases (MCAs) play important roles in regulating plant growth and development, as well as programmed cell death under stress conditions.

Results

Based on whole-genome information, a total of 36, 10, 12, 23, 11, nine, nine, six, eight, and five MCA genes were identified in Triticum aestivum, Hordeum vulgare, Triticum urartu, Triticum dicoccoides, Aegilops tauschii, Oryza sativa, Arabidopsis thaliana, Vitis vinifera, Solanum lycopersicum, and Cucumis sativus, respectively. The gene structures, evolutionary relationships, and potential roles of TaMCAs in wheat powdery mildew resistance were systematically analyzed. Phylogenetic analysis classified MCAs into four subgroups (Class I-1, I-2, II-1, and II-2), with members within the same subgroup exhibiting highly similar gene structures. Notably, two pairs of tandemly duplicated genes (TaMCA1A-2/TaMCA1A-3 and TaMCA1B-2/TaMCA1B-3) were identified in wheat. Virus-induced gene silencing and qRT-PCR demonstrated that TaMCA4D-3, as a Class I-2 gene, positively regulates resistance to wheat powdery mildew, and subcellular localization analysis indicated that TaMCA4D-3 is localized in both the nucleus and cytoplasm.

Conclusions

Collectively, these findings provide new insights into the classification and evolutionary relationships of the MCA gene family across plant species and elucidate the role of MCAs in wheat resistance to powdery mildew.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-026-08686-5.

Introduction

Programmed cell death (PCD) is a genetically regulated process in which plant cells undergo death in response to endogenous developmental cues or exogenous environmental stimuli. This process contributes to plant adaptation by eliminating unnecessary or damaged cells, thereby enhancing resistance to environmental stresses and pathogen invasion [1]. In plants, cysteine endopeptidases and serine endopeptidases are two major classes of proteolytic enzymes that play crucial roles in PCD pathways [2]. Cysteine endopeptidases can be further categorized into vacuolar processing enzymes and metacaspases (MCAs or MCs) [3, 4].

Based on protein structure and sequence similarity, plant metacaspase genes can be classified into two types: type I and type II. Both type I and type II MCAs contain a conserved caspase-like catalytic domain composed of a 20 kDa (p20) and a 10 kDa (p10) subunit. Previous studies have shown that the precursor domain of some MCA proteins in type I contain a conserved zinc finger domain similar to that of LESION SIMULATING DISEASE 1 (LSD1) [5–7]. In barley, according to the presence or absence of the LSD1-like zinc finger domain in the precursor domain, type I MCAs can be further divided into two subtypes[8]. In contrast, type II metacaspases possess a linker region of approximately 50 amino acid residues between the p20 and p10 domains [9, 10].

To date, the numbers of MCA genes in Arabidopsis thaliana [11], Oryza sativa [10, 12], Vitis vinifera [13], Solanum lycopersicum [14], Hevea brasiliensis [6], Hordeum vulgare [8], Gossypium Species [15], Cucumis sativus [16], Solanum tuberosum [17], Fragaria vesca, Prunus mume, Prunus persica, Pyrus communis, Pyrus bretschneideri, and Malus domestica [18] have been identified using genomic databases. Numerous studies have demonstrated that MCAs play critical roles in regulating plant development and stress responses [12]. In maize, the accumulation of reactive oxygen species induced by senescence, together with a decline in antioxidant defense capacity, leads to the activation of type II MCA genes ZmMCII-1, ZmMCII-2, and ZmMCII-3, as well as the cleavage of target proteins, ultimately promoting senescence [19]. In pear, five PbMCs are involved in pollen germination and pollen tube growth, whereas three PbMCs participate in fruit development [18]. In potato, the SotubMC1–SotubMC8 exhibit differential expression patterns in roots, stolons, and tubers [17]. Moreover, AtMC9 is strictly localized to differentiating xylem elements and root cap cells undergoing programmed cell death [20]. Collectively, these findings indicate that MCAs exhibit pronounced tissue specificity and diverse functions.

Plants cannot escape environmental challenges through individual movement, remaining continuously exposed to pathogens and a wide range of abiotic stressors [4]. MCAs play important roles in alleviating the detrimental effects of abiotic stresses [21–24]. Overexpression of AtMC3/AtMCA-Ic in Arabidopsis thaliana enhances drought tolerance through two mechanisms: promoting the differentiation of specific vascular tissues and maintaining higher vascular-mediated transport capacity [22]. In Petunia hybrida, PhMC1/PhMCA-Ia, as well as eight out of nine MCA genes in tomato, were upregulated to varying degrees under drought stress [14, 25]. The expression of AtMC8 in Arabidopsis increases under stresses such as ultraviolet irradiation and H₂O₂ treatment, and its overexpression in protoplasts significantly accelerates the PCD process [26]. Under biotic stress, the MCA family gene AtMCP2d in Arabidopsis responds to the mycotoxin fumonisin B1 (FB1). Overexpression of this gene markedly accelerates pathogen-induced cell death, restricts pathogen spread, and enhances plant resistance. In contrast, mcp2d mutants exhibit significantly reduced resistance, confirming the involvement of AtMCP2d in disease resistance [11]. In wheat, TaMCA4 (Type II MCA) and TaMCA1 (Type I MCA) participate in rust fungus-induced PCD, with TaMCA4 acting as a positive regulator. Silencing TaMCA4 weakens PCD and reduces resistance in resistant cultivars [27], whereas TaMCA1 functions as a negative regulator; silencing this gene enhances PCD and resistance in susceptible cultivars [28]. In addition to the species mentioned above, MCA family genes have also been implicated in disease resistance pathways in various plants, including tomato, wheat, grape, and cucumber [29].

Wheat powdery mildew caused by the obligate biotrophic pathogen, Blumeria graminis f. sp. Tritici, is a destructive disease of wheat, which severely affect wheat yield and quality [30–34]. Previous studies have demonstrated that MCA play important roles in plant development and responses to abiotic stresses; however, their functions in wheat responses to biotic stresses remain poorly understood. In this study, we systematically investigated the physicochemical properties, number, evolutionary relationships, and functions of the wheat MCA gene family in resistance to powdery mildew by integrating molecular biology and bioinformatics approaches. Our findings provide valuable genetic resources for wheat powdery mildew research and offer a theoretical basis for the improvement of wheat varieties through the utilization of MCA genes.

Materials and methods

Plant materials and treatment

All experiments were conducted in Xinxiang, China. A mixed race of Blumeria graminis f. sp. tritici (Bgt) was collected from the field and maintained on seedlings of the susceptible wheat cultivar ‘Sumai 3’. The Bgt isolates were maintained in a growth chamber under controlled conditions of 70% relative humidity, with a 14 h light period at 22 °C and a 10 h dark period at 18 °C. The common wheat cultivars ‘Bainong AK58’ was developed by the College of Agriculture, Henan Institute of Science and Technology. ‘Bainong AK58’ was used for RNA extraction also grown at the same condition as ‘Sumai 3’. Seedlings of ‘Bainong AK58’ were inoculated with Bgt at the two-leaf stage, and leaves from five individual plants were collected at 0, 2, 6, 12, 24, 36, and 48 h post inoculation (hpi). Total RNA was extracted using TRIzol reagent (Vazyme, Nanjing, China) according to the manufacturer’s instructions. The common wheat ‘Bainong AK58’ was used for the barley stripe mosaic virus-induced gene silencing (BSMV-VIGS) assay. It was grown at 16 °C for 14 h with light and at 12 °C for 10-h of darkness with 70% relative humidity in a chamber before virus infection.

Quantitative RT-PCR analysis of TaMCA

We used the expression results of wheat MCA gene under powdery mildew stress from WheatOmics 1.0 (http://wheatomics.sdau.edu.cn/expression/wheat.html) and visualized them using TBtools in the form of heat maps [35].

At the same time, RNA samples were reverse-transcribed using the HiScript® III RT SuperMix for qPCR kit (Vazyme, Nanjing, China). Relative expression levels of the target genes were quantified via qRT-PCR using a SYBR Green detection kit and the AceQ qPCR SYBR Green Master Mix (Vazyme, Nanjing, China) on an LC 480 II system (Roche, Germany). The wheat gene TaTubulin used as an internal control. The qRT-PCR program was as follows: an initial denaturation at 95 ℃ for 5 min, followed by 40 cycles of denaturation at 95 ℃ for 10 s and extension at 60 ℃ for 20 s. Relative gene expression levels were calculated using the comparative 2^–ΔΔCT method. All primers used in this study (Table S1) were synthesized by Gene Create (Wuhan, China). The qRT-PCR data is presented in Table S2.

BSMV-VIGS

The TaMCA4D-3 fragment of length 239 bp was amplified using the corresponding primer pairs (Table S1), and then inserted into the γ strain of BSMV to generate the vector BSMV: TaMCA4D-3. The second fully unfolded leaves of Bainong AK58 were infected in vitro with the transcribed virus with BSMV: TaPDS and BSMV: γ-infected leaves as controls. The infected plants grew at 23 ℃, under a 14 h light/10 h dark cycle at 70% relative humidity. The fourth leaves showing symptoms of viral infection were collected and inoculated with mixed Bgt to evaluate disease resistance. For the evaluation of powdery mildew disease, the leaves were placed and cultured on a 6BA-plate with mixed powdery mildew spores. The inoculated leaves were cultured under conditions of 14 h light/22 ℃ and 10 h/darkness 18 ℃ for 6 days. Target gene silencing efficiency was checked by qRT-PCR using the corresponding primer pairs (Table S1).

Subcellular localization

The open reading frame sequence of TaMCA4D-3 (TraesCS4D02G358800.1) was retrieved from the EnsemblPlants database. The primer pair TaMCA4D-1-CDS (Table S1) was used to amplify the coding DNA sequence (CDS) of TaMCA4D-3 from cDNA of the wheat cultivar ‘Bainong AK58’. PCR amplification was performed under the following conditions: an initial denaturation at 95 °C for 5 min, followed by 33 cycles of 95 °C for 15 s, 56 °C for 15 s, and 72 °C for 90 s, with a final extension at 72 °C for 5 min. PCR reactions were carried out using Phanta Flash Master Mix (Vazyme). The amplified products were ligated into vectors using the TA/Blunt-Zero Cloning Kit (Vazyme) and subsequently sequenced by Gene Create. For subcellular localization assay, the full-length TaMCA4D-3 CDS was amplified by PCR from the TA/Blunt-Zero vector containing the TaMCA4D-3 insert using the primers pCambia1305:TaMCA4D-3-F and pCambia1305:TaMCA4D-3-R (Table S1). The PCR product was inserted into the pCambia1305-GFP vector via homologous recombination to generate the pCambia1305-TaMCA4D-3-GFP construct. The recombinant plasmid was then introduced into Agrobacterium tumefaciens strain GV3101. Agrobacterium transformants were cultured in Luria–Bertani (LB) medium containing rifampicin and kanamycin at 28 °C until an OD₆₀₀ of 0.5 was reached. Cells harboring the expression constructs, including pCambia1305:GFP and pCambia1305-TaMCA4D-3-GFP, were collected by centrifugation and resuspended in infiltration buffer (the final working concentration: 10 mM MES, 10 mM MgCl₂, and 100 µM acetosyringone). The Agrobacterium suspensions were infiltrated into leaves of 4-week-old transgenic N. benthamiana plants which carrying the nuclear marker H2B-RFP as previously described [36]. Fluorescence signals of expressed proteins in cells were observed and photographed by laser confocal microscopy 48 h after agrobacterium infiltration (Zeiss LSM780).

Whole genome identification of MCA family members

The genome sequence of wheat (Triticum aestivum, 'Chinese Spring') was downloaded from the International Wheat Genome Sequencing Consortium (IWGSC). Additionally, the genome sequence of Hordeum vulgare (IBSC_v2), Triticum urartu (Tu 2.0), Triticum dicoccoides (WEWSeq_v.1.0), Aegilops tauschii (Aet_v4.0), Oryza sativa (IRGSP-1.0), Arabidopsis thaliana (TAIR10), Vitis vinifera (12X), Solanum lycopersicum (SL3.0) and Cucumis sativus (ASM407v2) were obtained from EnsemblPlants (http://plants.ensembl.org/index.html). The typical MCA domain (PF00656) was downloaded from the Pfam database to serve as the search model. As described by Xu et al. [37], a new Hidden Markov Model (HMM) was constructed to ensure the accuracy of search results. Using the newly established HMM as the search model, the HMMERv3 suite was employed with the hmmbuild function (E-value < 1 × 10⁻²⁰) to identify MCA genes. Candidate sequences were subsequently validated using NCBI-CDD [38]. Only sequences containing complete MCA conserved domains were retained for further analysis (Table S3).

Phylogenetic analysis, gene structure, and conserved motif analysis

Using the maximum likelihood method in MEGA-X software (Poisson model) [39], the MCA family members from ten plants were constructed with 1000 bootstrap replicates. The resulting tree was visualized using EvolView [40]. Exon–intron structure analysis was performed using GFF3 file, and motif analysis was conducted with the MEME program (http://memesuite.org/tools/meme). The maximum number of motifs was set to 20, with an optimal width for each motif ranging from 6 to 50 residues [37]. The structural features and motif compositions of MCA genes were visualized using TBtools [35]. The physicochemical properties of TaMCA proteins were analyzed using the ProtParam (https://web.expasy.org/protparam/).

Gene replication and cis‑acting element analyses

To identify gene duplication events, the Multiple Collinearity Scan toolkit (MCScanX) was utilized [41]. Gene duplication events, syntenic relationships among gene pairs, and chromosome localization of the analyzed genes were visualized using ShinyCircos software (http://shinycircos.ncpgr.cn) [42]. The upstream promoter 2000 bp sequence of MCA gene family members was extracted from the wheat genome using TBtools. Their cis-regulatory elements were predicted by PlantCARE (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) and visualized by TBtools [35].

Results

Identification and phylogenetic analysis of the MCA gene family

To identify MCA gene family members in plant genomes, a hidden Markov model (HMM) profile was used to search the whole-genome sequences of ten plant species. A total of 101 MCA genes were identified in six monocotyledonous species, including 36 TaMCA genes in wheat (Triticum aestivum), 23 TdMCA genes in Triticum dicoccum, 10 HvMCA genes in Hordeum vulgare, 11 AetMCA genes in Aegilops tauschii, 12 TuMCA genes in Triticum urartu, and nine OsMCA genes in rice (Oryza sativa). In addition, 28 MCA genes were identified in four dicotyledonous species, including nine AtMCA genes in Arabidopsis thaliana, six VvMCA genes in grape (Vitis vinifera), eight SlMCA genes in tomato (Solanum lycopersicum), and five CsMCA genes in cucumber (Cucumis sativus) (Table S3).

To further elucidate the phylogenetic relationships of the MCA gene family, a phylogenetic analysis of MCA proteins from six monocotyledonous and four dicotyledonous plant species was performed (Fig. 1). Based on the resulting phylogenetic tree and the classification basis of MCA proteins in the previous report, the MCA proteins were classified into four distinct subgroups: I-1, I-2, II-1, and II-2. Class I-1 comprised 19 type I-1 MCA members, Class I-2 contained 65 type I-2 MCA members, Class II-1 included 32 type II-1 MCA members, and Class II-2 consisted of 13 type II-2 MCA members (Fig. 1).

Fig. 1.

Phylogenetic analysis of metacaspase (MCA) proteins from ten plant species. MCA proteins from Wheat (Triticum aestivum), Hordeum vulgare, Triticum urartu, Triticum dicoccoides, Aegilops tauschii, and Oryza sativa are indicated by different colored symbols. MCA proteins from Arabidopsis thaliana, Vitis vinifera, Solanum lycopersicum and Cucumis sativus are indicated by different colored check marks

Physical and chemical properties and structural analysis of MCA gene family members in wheat

The physicochemical properties of TaMCA proteins were analyzed using the ProtParam tool (Table 1). The results showed that TaMCA proteins ranged from 299 to 448 amino acids in length, with TaMCA5A-3 being the shortest protein (299 amino acids) and TaMCA1D-2 being the longest (448 amino acids). The predicted molecular weights ranged from 32,604.39 to 47,774.04 Da, and the theoretical isoelectric points (pI) varied from 5.08 to 8.78. Based on the instability index, 25 TaMCA proteins, including TaMCA1A-1, were predicted to be unstable (instability index > 40), whereas the remaining members were predicted to be stable.

The conserved motifs and structural features of TaMCA proteins are shown in Fig. 2. All TaMCA proteins contain Motifs 1, 2, 3, 5, 6, 7, and 10, except for TaMCA2B-1, which lacks Motif 10. Members of the Class I contain Motifs 4 and 11, whereas those of the Class II contain Motifs 9 and 13. Within the Class I, compared with Class I-1, Class I-2 additionally contains Motif 16. Similarly, within the Class II, Class II-1 contains Motif 15 compared with Class II-2. These results indicate that members of the MCA within the same class in wheat exhibit highly similar motif compositions, whereas noticeable differences in motif composition exist among different classes. Members of Class I-2 contain three to five exons, whereas those of Class I-1 uniformly contain five exons. All members of Class II-1 (except TaMCA2B-1) contain two exons, while members of subgroup II-2 each contain a single exon. The conserved exon-intron organization among wheat MCA genes within the same subfamily further supports the evolutionary conservation of the MCA gene family.

Fig. 2.

Gene structure and conserved domain organization of TaMCA proteins. A Phylogenetic tree constructed using the Neighbor-Joining (NJ) method. B Conserved motif distribution of MCA proteins. C Exon–intron structure of MCAs

Distribution and replication analysis of MCA gene family members in wheat

Based on the genomic information of MCA genes in wheat, their physical chromosomal locations were determined (Fig. 3). The results showed that wheat MCA genes are distributed across chromosomes 1, 2, 3, 4, and 5. Specifically, 11 TaMCA genes were located on chromosomes 1A, 1B, and 1D; 10 TaMCA genes on chromosomes 3A, 3B, and 3D; seven TaMCA genes on chromosomes 4A, 4B, and 4D; and seven TaMCA genes on chromosomes 5A, 5B, and 5D. Two pairs of tandemly duplicated MCA genes were identified in the wheat genome, namely TaMCA1A-2/TaMCA1A-3 and TaMCA1B-2/TaMCA1B-3. In contrast, no tandem duplication events were detected in the MCA gene family of T. dicoccum.

Fig. 3.

Chromosomal locations, homologous gene pairs, and tandem duplication of MCA genes in T. aestivum. Adjacent MCA genes highlighted in red indicate tandemly duplicated gene pairs

Analysis of cis acting elements of wheat MCA family members

To further explore the potential biological functions of wheat TaMCA genes, cis-acting regulatory elements in their promoter regions were analyzed (Fig. 4). The results revealed the presence of numerous cis-elements associated with plant hormone signaling and responses to biotic and abiotic stresses. These elements included defense- and stress-responsive elements, gibberellin-responsive elements, auxin-responsive elements, abscisic acid–responsive elements, hypoxia-inducible enhancer-like elements, light-responsive elements, low-temperature-responsive elements, as well as regulatory elements involved in palisade mesophyll cell differentiation. Collectively, these findings suggest that TaMCA genes may play important regulatory roles in plant growth, development, and stress responses.

Fig. 4.

Analysis of cis-acting elements

Expression patterns of wheat MCA gene family members under powdery mildew

Powdery mildew is one of the major biotic stresses affecting wheat production. To further investigate the potential involvement of TaMCA genes in the powdery mildew stress response, the expression patterns of wheat MCA family members under powdery mildew at different time points were analyzed using RNA-seq data from the WheatOmics 1.0 (Fig. 5). Under powdery mildew stress, the expression levels of TaMCA3D-3 and TaMCA4D-3 showed a continuous decreasing trend with increasing duration of infection. In contrast, the expression levels of TaMCA1D-1, TaMCA1A-3, TaMCA5A-3 and TaMCA3D-2 exhibited an initial increase followed by a subsequent decrease, while the remaining TaMCAs show relatively minor changes in expression. At 72 h post-inoculation, the transcript levels of TaMCA3D-3, TaMCA5A-3, and TaMCA4D-3 were reduced by 35.58%, 72.09%, and 63.38%, respectively, compared with those at 0 h. Meanwhile, the expression levels of TaMCA1D-1 and TaMCA1A-3 reached their maximum at 24 h, post-inoculation, which were 2.49- and 49.61-fold higher than at 0 h, respectively.

Fig. 5.

Transcriptome heatmap of TaMCA genes under powdery mildew stress. The color scale bar represents the gene expression levels (in log2-based tags per million, TPM) of the genes, and the values shown in square frames represent the corresponding TPM values

To further validate the expression pattern and potential functional role of TaMCAs in response to powdery mildew, qRT-PCR was performed (Fig. 6). Compared with 0 h, except for TaMCA3D-2, the expression levels of most TaMCAs showed significant changes. Among them, the expression levels of TaMCA1A-3 and TaMCA3D-3 showed an increasing trend followed by a decreasing trend (Fig. 6A, D), while the expression levels of TaMCA1D-1 and TaMCA5A-3 showed a decreasing trend (Fig. 6B, F). Compared with 0 h, the expression level of TaMCA4D-3 showed a significant increasing trend under powdery mildew stress. Notably, the transcript level of TaMCA4D-3 at 12 h post-inoculation was 5.78-fold higher than that at 0 h (Fig. 6E).

Fig. 6.

Expression analysis of TaMCAs under Blumeria graminis f. sp. tritici stress by qRT-PCR. Asterisks indicate significant differences (assessed using Duncan’s honestly significant difference test) at P < 0.01**

TaMCA4D-3 positively regulate wheat powdery mildew disease resistance

Based on the RNA-seq and qRT-PCR results, a VIGS assay was performed to verify the role of TaMCA4D-3 (as well as TaMCA5A-4 and TaMCA4B-3) in powdery mildew resistance in the wheat cultivar ‘Bainong AK58’ (Fig. 7). qRT-PCR analysis showed that the expression level of TaMCA4D-3 was significantly reduced in plants infected with BSMV:TaMCA4D-3 compared with control plants (Fig. 7A). Six days after inoculation with Bgt, leaves of BSMV:TaMCA4D-3-silenced plants exhibited reduced resistance to Bgt compared with control plants (Fig. 7B). These results indicate that TaMCA4D-3 functions as a positive regulator of wheat resistance to powdery mildew in ‘Bainong AK58’.

Fig. 7.

Functional analysis of TaMCA4D-3 by BSMV-VIGS in BainongAK58. A Expression of TaMCA4D-3 in BSMV: TaMCA4D-3 and BSMV:γ infected (control) leaves. CK: plants inoculated with BSMV:γ, and 1–2: plants inoculated with BSMV: TaMCA4D-3. Significant differences assessed using Duncan’s honestly significant difference test at P < 0.01**. All the raw data for qRT-PCR are listed in Table S2. B Plants with BSMV: TaMCA4D-3 and BSMV:γ (acted as control) were inoculated with Blumeria graminis f. sp. Tritici. Photos were obtained six days after inoculation

TaMCA4D-3 protein is localized in the nucleus and cytoplasm

To determine the subcellular localization of TaMCA4D-3 in Nicotiana benthamiana cells, the TaMCA4D-3 coding sequence was fused to the pCambia1305: GFP vector and transiently expressed in transgenic N. benthamiana plants which carrying the nuclear marker H2B-RFP. The empty pCambia1305:GFP vector was used as a control. Laser scanning confocal microscopy analysis (Fig. 8) showed that in both the control and TaMCA4D-3–GFP–expressing cells, the red fluorescence signal derived from H2B-RFP was exclusively localized in the nucleus. The green fluorescence signal was detected in both the nucleus and the cytoplasm. Moreover, some of the green fluorescence overlapped with the red fluorescence signal in the nuclear. These results demonstrate that the TaMCA4D-3 protein is localized in both the nucleus and the cytoplasm.

Fig. 8.

Subcellular localizations of TaMCA4D-3 protein in N. benthamiana leave cell. RFP: red fluorescent protein images; GFP: green fluorescent protein images; Bright: images obtained in transmission mode. Merged: merged fluorescent and bright field

Discussion

MCAs are cysteine proteases that are widely distributed in plants [6]. In this study, a genome-wide identification and evolutionary analysis of MCA genes was performed across six monocotyledonous species, including wheat, and four dicotyledonous species. Phylogenetic analysis classified these MCA proteins into four subgroups: Type I-1, Type I-2, Type II-1, and Type II-2 (Fig. 1). Members from both monocotyledonous and dicotyledonous plants were present in each subgroup, and wheat MCA genes exhibited highly conserved gene structures within the same subfamily (Figs. 1, and 2). Previous studies have generally classified plant MCAs into two major subgroups, Type I and Type II, although some studies have proposed a three-subgroup classification, including Type I, Type I*, and Type II. For example, in barley, MCAs are divided into three subgroups, with the Type I* subgroup containing only monocotyledonous barley MCAs [8].In contrast, MCAs from dicotyledonous Gossypium species are classified into only two subgroups, Type I and Type II [15]. By incorporating more MCA proteins from different monocotyledonous and dicotyledonous species, the present study provides a more comprehensive and reliable phylogenetic framework for elucidating the evolutionary relationships of the MCA gene family. Analysis of gene duplication events further revealed that TaMCA1A-2 and TaMCA1A-3, as well as TaMCA1B-2 and TaMCA1B-3 constitute two pairs of tandemly duplicated genes in wheat (Fig. 3). In contrast, no tandem duplication events were detected among MCA genes in T. dicoccum. This finding indicates that tandem duplication contributed to the expansion of the MCA gene family. Consistent with this finding, previous studies have demonstrated that large-scale duplication events play a crucial role in the expansion of the MCA gene family in Rosaceae species [18]. Similarly, tandemly duplicated MCA genes have also been reported in Gossypium arboreum, G. hirsutum, and G. raimondii [15], further highlighting the importance of gene duplication in the evolutionary diversification of the MCA gene family.

Transcriptome analysis revealed that the expression of TaMCA4D-3 was significantly downregulated under powdery mildew stress (Fig. 5). In contrast, qRT-PCR analysis showed a significant upregulation of TaMCA4D-3 in the cultivar ‘Bainong AK58’ under the same stress conditions (Fig. 6E). This apparent discrepancy is most likely attributable to differences in genetic background between the two wheat varieties, suggesting the cultivar-specific regulation of MCA genes during pathogen infection. Such genotype-dependent expression patterns have been widely reported for stress-responsive genes and underscore the importance of functional validation across multiple genetic backgrounds. Functional validation using VIGS demonstrated that TaMCA4D-3 acts as a positive regulator of wheat resistance to powdery mildew. Silencing of TaMCA4D-3 significantly reduced host disease resistance, leading to increased susceptibility to Blumeria graminis f. sp. tritici (Fig. 7B). These results indicate that TaMCA4D-3 plays a critical role in mediating defense responses against powdery mildew infection. Accumulating evidence suggests that metacaspase family members regulate plant disease resistance primarily through regulation of PCD, functioning either as positive or negative regulators depending on the specific gene and stress context. In Arabidopsis, both AtMC1 and AtMC2 participate in salicylic acid precursor benzothiadiazole (BTH)-induced PCD, with AtMC1 acting as a positive regulator and AtMC2 functioning as a negative regulator [43]. Similarly, AtMC4 positively regulates PCD induced by both biotic and abiotic stresses [44]. In rice, OsMCA family members exhibit distinct transcriptional responses to multiple abiotic stresses, including drought, salinity, cold, and heat, as well as biotic stresses caused by Magnaporthe oryzae, Xanthomonas oryzae pv. oryzae, and Rhizoctonia solani infection [12]. In tomato, the type II metacaspase gene LeMCA1 is rapidly induced during Botrytis cinerea–triggered PCD [29], while Arabidopsis AtMC7 and AtMC8 are strongly upregulated in response to Alternaria brassicicola infection and the fungal toxin FB1 [11]. MCAs can also negatively regulate PCD to enhance host resistance. For instance, NbMCA1 in tobacco suppresses excessive PCD and enhances resistance to Colletotrichum destructivum [45]. In contrast, CaMC9 in chili positively regulates pathogen-induced PCD; silencing of this CaMC9 weakens host PCD and enhances resistance, whereas its overexpression promotes excessive PCD and reduces disease resistance [46]. Similarly, boron-induced PCD in barley significantly upregulates HvMC4 while downregulating HvMC5, suggesting antagonistic roles of these two MCAs in PCD regulation [8]. In wheat, TaMCA4 and TaMCA1 have been reported to play opposing roles in rust fungus–induced PCD. TaMCA4 functions as a positive regulator, and its silencing leads to reduced PCD and decreased resistance in resistant cultivars [27], whereas TaMCA1 acts as a negative regulator, and its silencing enhances PCD and disease resistance in susceptible cultivars [28]. In the present study, TaMCA4D-3, a member of the monocot-specific Ⅰ−2 subgroup, was shown to positively regulate wheat resistance to powdery mildew. Notably, recent studies have identified an immune signaling module in wheat consisting of of a type II metacaspase protease (TaMCA-IIa), the endogenous peptide signal TaPep, and the receptor TaPEPR1, which plays a central role in resistance to Fusarium head blight. In this module, TaMCA-IIa functions as a key protease responsible for TaPep maturation by cleaving conserved arginine residues, thereby activating immune signaling pathways[47]. Together, these findings indicate that metacaspase family members from different evolutionary subgroups perform diverse and sometimes opposing roles in regulating PCD and immune responses during fungal disease resistance in wheat.

Conclusion

In this study, an integrative approach combining bioinformatics and molecular biology was employed to identify 101 and 28 MCA genes from the whole genomes of six monocotyledonous and four dicotyledonous plant species, respectively. Phylogenetic analysis classified these MCA proteins into four distinct subgroups (I-1, I-2, II-1, and II-2). Members within the same subgroup exhibited highly conserved exon–intron structures and motif compositions, and tandem duplication events were identified in the wheat MCA gene family, indicating their contribution to gene family expansion. Functional analyses based on qRT-PCR and VIGS demonstrated that TaMCA4D-3 plays a positive regulatory role in wheat resistance to powdery mildew. Collectively, these findings provide valuable insights into the classification, evolutionary diversification, and functional roles of the MCA gene family across plant species and advance our understanding of MCA-mediated defense mechanisms in wheat against fungal diseases.

Abbreviations

MC/MCA

Metacaspases

PCD

Programmed cell death

LSD

LESION SIMULATING DISEASE

Bgt

Blumeria graminis f. sp. tritici

AK58

Bainong AK58

BSMV-VIGS

Barley stripe mosaic virus-induced gene silencing

Authors’ contributions

Ping Hu, Xinjie Zhu and Jun Xu completed the experimental design, experimental process, data analysis, initial draft of the paper, and writing revisions for this study; Lu Zhang, Kaige Zhou and Xinjie Zhu completed the experimental process and experimental data; Chengwei Li and Haiyan Hu participated in experimental design and paper writing revision. All authors have read and agreed to the final text.

Funding

This study was funded by the Basic Research Special Project of Key Research Projects in Higher Education Institutions of Henan Province (No. 24ZX013), National Natural Science Foundation of China (No. 31901538). Henan Province Science and Technology Research Project (No. 252102110290).

Data availability

Datasets supporting the findings of this study are available within the article and its supplementary materials.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.