MIR396d-p3 Negatively Regulates Apple Resistance to Colletotrichum gloeosporioides via MdUGT89A2 and MdRGA3

Abstract

Apple (Malus domestica) is an economically important fruit crop, but its production is affected by Glomerella leaf spot, a devastating disease caused by the fungal pathogen Colletotrichum gloeosporioides. MicroRNA (miRNA) is a kind of non-coding RNA that plays an important role in the process of plant–pathogen interactions. However, little is known about the miRNAs that influence apple resistance against C. gloeosporioides. A novel miRNA, MIR396d-p3, was identified through small RNA sequencing (sRNA-seq). Functional analyses revealed that MIR396d-p3 negatively regulates apple resistance to C. gloeosporioides. In addition, MdUGT89A2 and MdRGA3 were confirmed as targets of MIR396d-p3 using 5′ RACE and heterologous expression assays. We further found that overexpressing MdUGT89A2 and MdRGA3 induce apple disease resistance to C. gloeosporioides, while silencing of MdUGT89A2 and MdRGA3 reduces resistance to C. gloeosporioides. These results indicate that MIR396d-p3 plays a role in the response to the infection of C. gloeosporioides through regulating the expressions of MdUGT89A2 and MdRGA3. This research provides a new perspective on the interaction between apples and C. gloeosporioides and offers possible targets for resistance breeding.

1. Introduction

Apple (Malus domestica) is a major fruit crop worldwide but suffers significant yield losses due to persistent fungal pathogens [1]. Apple glomerella leaf spot (GLS), caused by Colletotrichum gloeosporioides (C. gloeosporioides), leads to defoliation and a marked decline in apple yield [2]. The main varieties of apple in the world, such as “Golden Delicious” and “Gala”, are universally susceptible to GLS, thereby exacerbating the impact of this disease [3]. High levels of humidity and temperature lead to recurrent outbreaks of GLS that affect both leaves and fruits [4]. Chemical control continues to be the predominant approach for managing apple GLS disease at this time, but treatments have negative repercussions, impacting environmental health and jeopardizing food safety. Deciphering the resistance mechanisms of apples against C. gloeosporioides, along with cultivating new resistant germplasm, would be a more effective approach.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally by binding to target mRNAs and inhibiting their translation or promoting degradation [5]. Mounting evidence has revealed that miRNAs perform critical regulatory roles in plant–pathogen interactions [6]. In particular, miRNAs play vital regulatory roles in the response of apple to various fungal pathogens, such as Botryosphaeria dothidea [7,8,9,10], Alternaria alternata [11,12,13], and C. gloeosporioides [14]. However, the precise mechanisms by which miRNAs mediate apple resistance to C. gloeosporioides are still not well understood. Specifically, the role of miR396 in regulating apple resistance to C. gloeosporioides has not yet been reported, while the regulation of immune responses to pathogenic infections by miR396 in Arabidopsis [15], rice [16], tomato [17], and soybean [18] has been documented.

UDP-glycosyltransferases (UGTs) are pivotal biotransformation enzymes that have developed across a wide range of living organisms, including bacteria, fungi, plants, and animals [19]. UGTs are essential for the glycosylation of small molecules [20]. This process can modify the homeostasis of these compounds by influencing their chemical activity, degradation, and distribution. UGTs are involved in various processes related to plant growth and defense response [21,22,23]. For example, UGT73C7 is a pathogen-induced glycosyltransferase in Arabidopsis that enhances disease resistance by redirecting phenylpropanoid metabolism and upregulating the expression of the SNC1 gene, a key component in plant immunity [21]. In addition, UDP-glucosyltransferase HvUGT13248 is conferred type II resistance to Fusarium head blight (FHB) in barley by glucosylating the mycotoxin deoxynivalenol (DON) to its nontoxic form, DON-3-O-glucoside (D3G), and demonstrates that mutations in HvUGT13248 increase susceptibility to F. graminearum infection [22]. Given these findings [21,22], we hypothesize that UGTs may play a pivotal role in apple resistance to C. gloeosporioides. However, there have been no reports on the study of UGTs in the disease resistance of apples.

Plant disease resistance genes (R genes) are the most recognized group of resistance gene analogs (RGAs), playing a vital role in sensing and defending against various plant pathogens [24]. This typical R gene structure usually comprises three domains: a leucine-rich repeat (LRR), a nucleotide-binding domain (NBD), and a signaling domain, which includes the Toll/IL-1 receptor (TIR), RESISTANCE TO POWDERY MILDEW 8 (RPW8), and the coiled-coil (CC) domain [25]. In addition, R genes and RGAs serve as essential genetic resources for managing plant diseases and offering immune protection against significant pathogen-related damage. Therefore, it is essential to dissect the role of RGAs in the resistance of apples to C. gloeosporioides.

This study used sRNA-seq technology to analyze how apple miRNA responds to the infection of C. gloeosporioides. At the same time, a novel miRNA, MIR396d-p3, is identified as the research object of this study. Then we predicted and verified through 5′ RACE and heterologous expression assays that MdUGT89A2 and MdRGA3 are direct targets of MIR396d-p3. To further confirm this regulatory relationship, expression profiling of MIR396d-p3 and its target genes was detected in susceptible and resistant cultivars. In addition, we found that MIR396d-p3 regulates resistance to C. gloeosporioides by modulating the expression of MdUGT89A2 and MdRGA3 through functional analyses. Taken together, this research provides a new perspective on the interaction mechanism between apples and C. gloeosporioides.

2. Material and Methods

2.1. Plant Material and Pathogen Cultures

The apple cultivars “Royal Gala” (abbreviated as “GL-3”) and “Fuji” (“FJ”) were maintained in vitro using Murashige and Skoog basal medium containing specific plant growth regulators: 0.6 mg·L⁻¹ benzylaminopurine (BAP), 0.4 mg·L⁻¹ α-naphthaleneacetic acid (NAA), and 0.2 mg·L⁻¹ gibberellin A3 (GA3). The plant materials were grown at 25 ± 1 °C under controlled conditions and a 16/8 h light/dark cycle with a light intensity of 120 μmol m⁻² s⁻¹ in humidity-controlled chambers maintaining saturated moisture. For experimental standardization, in vitro-developed apple plantlets at 28 days of maturity were systematically selected as biological material for subsequent experiments.

Nicotiana benthamiana were sown in a mix (vermiculite, perlite, and soil in a 1:1:1 ratio). N. benthamiana plantlets were cultivated under controlled environmental conditions, including a temperature regime of 22 ± 1 °C, a 16/8 h light/dark cycle with a light intensity of 120 μmol m⁻² s⁻¹, and 80% relative humidity.

The C. gloeosporioides strain W16, preserved in our laboratory, was grown on potato dextrose agar (PDA) medium at 28 °C for 3 days [26]. A sterilized toothpick was then employed to abrade the mycelial surface to promote sporulation. After an additional 4 days of incubation, we rinsed the mycelium and spores on the plate with sterile water. We filtered the resulting suspension through four layers of sterile gauze to remove mycelial fragments. We collected the filtrate containing spores and adjusted the spore concentration to 1 × 10⁶ conidia·mL⁻¹ for the subsequent experiments.

2.2. sRNA-Seqencing and Identification of Differentially Expressed microRNAs (DE-miRNAs)

To investigate whether miRNAs are involved in the response of apple plants to C. gloeosporioides infection, we performed sRNA-seq analysis using the susceptible cultivar “GL-3”. Newly emerged apical leaves (3–4 leaves per plant) were inoculated with a conidial suspension of C. gloeosporioides. Samples were collected 24 h post-inoculation, with three bottles of leaves pooled as one biological replicate, and three independent biological replicates were subjected to sequencing analysis. Total RNA from “GL-3” plants, both inoculated with C. gloeosporioides and uninoculated controls, was extracted using a column method according to the method reported by Zhang et al. [27]. The quantification and purity evaluation of total RNA were performed with Nanodrop (Life Technologies, Carlsbad, CA, USA) and a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). Subsequently, the small RNA libraries were assembled using the 5′-phosphate-dependent method and were sequenced on an Illumina HiSeq 2000/2500 platform [28].

The obtained raw data were selected by aligning them against various RNA databases, including the RFam database and the Repbase database, resulting in valid small RNA data for subsequent analysis [29]. In order to screen for differentially expressed miRNAs, we utilized p-values and fold change for selection. The specific criteria were log₂|(fold change)| ≥ 1 and p-value < 0.05.

2.3. Bioinformatics Analysis

The target genes of candidate miRNA and the RNA secondary structure of candidate precursor miRNA were predicted using the psRNATarget web server [30] (https://www.zhaolab.org/psRNATarget/, accessed on 21 March 2025) and the UNAFold Web Server (http://www.unafold.org, accessed on 21 March 2025), respectively. To understand how many plant species contain candidate miRNA families and the evolutionary relationship between candidate miRNA and the reported candidate miRNA family in apple, we downloaded all relevant information from the miRBase database. Meanwhile, we used MEGA_12.0.10 software to construct a phylogenetic tree about candidate precursor miRNA.

Similarly, the promoter sequence of candidate miRNA was obtained from the GDR database by aligning it with the apple genome sequence [28], and cis-acting elements in the promoter were analyzed using the PlantCARE web server (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 20 January 2025). Finally, visualization of the results was performed using TBtools v2.061 [31].

2.4. Rapid Amplification of cDNA Ends Assay

Total RNA was obtained as described above. First strand cDNA was synthesized at 42 °C for 90 min and at 70 °C for 15 min using 5′ TS Oligo. Then, rapid amplification of cDNA ends (RACE) was conducted using the 5′ GSP provided in the HiScript-TS 5′/3′ RACE Kit. Nested PCR was then performed for multiple rounds of amplification to obtain positive bands. Subsequently, 24 randomly selected clones were sent for sequencing to a company.

2.5. Plasmid Construction

35S: MIR396d-p3 construct. The sequence of the MIR396d-p3 precursor was introduced into the pFGC5941 vector at the NcoI/BamHI site.

35S: STTM-MIR396d-p3 construct. A fragment containing two partially complementary sequences of MIR396d-p3, separated by a 48-base pair short spacer, was artificially synthesized and introduced into the pFGC5941 binary vector.

35S: MdUGT89A2-GUS construct. The full coding sequence of MdUGT89A2, excluding the stop codon, was introduced into the pFGC5941 vector at the NcoI/BamHI site.

35S: MdRGA3-GUS construct. The complete coding sequence of MdRGA3, without the stop codon, was inserted into the pFGC5941 binary vector at the NcoI/BamHI site.

35S: MdUGT89A2 construct. The coding sequence of MdUGT89A2 was introduced into the pFGC5941 binary vector.

35S: MdRGA3 construct. The gene sequence of MdRGA3 was cloned into the pFGC5941 binary vector.

RNAi construct. Two fragments with the sense and antisense sequences of MdUGT89A2 and MdRGA3 were inserted into the flanking regions of the pFGC5941 intron, respectively.

2.6. Agrobacterium-Mediated Transient Transformation

Transformation of all recombinant constructs was performed in Agrobacterium tumefaciens GV3101 cells. A single colony of Agrobacterium was grown in LB liquid medium containing rifampin (50 μg⋅mL⁻¹) and kanamycin (50 μg⋅mL⁻¹). Subsequently, the bacteria were suspended in a buffer solution composed of 10 mM MgCl₂, 10 mM MES, and 100 μM acetosyringone, with a pH adjusted to 5.6. The suspension was incubated at 25 °C in the dark for 2 h prior to its use in transient transformation experiments.

2.7. Histochemical Staining and GUS Activity Quantification

GUS staining assay was conducted on N. benthamiana infiltrated leaves according to previously reported methods [32]. The N. benthamiana leaves utilized for histochemical GUS staining were subjected to an incubation at 37 °C overnight. Subsequently, they were placed in a series of ethanol solutions with increasing concentrations (30%, 50%, and 70%) to facilitate visualization.

To further quantify GUS activity, the fluorometric 4-methylumbelliferyl-β-D-glucuronide (MUG) method was employed. The specific method should be carried out in accordance with the GUS gene quantitative detection Kit (Coolaber Science & Technology, Beijing, China). A unit of GUS activity is characterized by the production of 1 nM of 4-methylumbelliferone per minute for each milligram of soluble protein. In each treatment, 10 leaves corresponding to each construct were collected for detection.

2.8. RT-qPCR Assay

To validate the expression patterns of miRNAs and their target genes, total RNA was extracted using a column-based method at 4 d post-transfection. For temporal profiling of miRNA expression, additional samples were harvested at 24 and 72 h post-transfection, followed by RNA extraction using the same protocol. First-strand cDNA was generated through the HiScript II 1st Strand cDNA Synthesis Kit (Vazyme Biotech Co., Ltd., Nanjing, China). The expression level of mature MIR396d-p3 was analyzed using stem-loop real-time quantitative PCR, with 5S rRNA and MdActin serving as internal controls. RT-qPCR was conducted in accordance with the instructions provided for ChamQ SYBR qPCR Master Mix using CFX Connect TM Real-Time System (BIO-RAD, Hercules, CA, USA). The 2^−∆∆CT method was used to calculate relative expression levels of the corresponding genes [33].

To quantify fungal biomass, fungal and plant DNA extraction kits (Sangon Biotech, Shanghai, China) were employed to isolate C. gloeosporioides DNA and apple genomic DNA from leaf samples collected at 48 h post-inoculation, respectively. Subsequently, the fungal Cgβ-Tubulin gene and the apple MdActin gene were selected as internal reference genes for biomass quantification. Utilizing the same RT-qPCR reaction conditions and calculation procedures as described for the RT-qPCR assay, biomass data were obtained.

2.9. Statistical Analysis

The statistical analyses were implemented using GraphPad Prism 10 software. The data are expressed as the mean ± standard error (SE). One-way ANOVA followed by Tukey’s test (p < 0.05) was used to analyze significant differences.

3. Results

3.1. Analysis of Apple Small RNA Sequencing Response to C. gloeosporioides

To investigate whether miRNAs of apple are involved in the response to C. gloeosporioides infection, sRNA-seq was conducted, and the clean data were obtained. First, we removed miRNAs mapped to two positions of the same precursor on the genome; the unique count of candidate RNAs was obtained. The length distribution analysis of the above miRNAs is shown in Figure S1B. According to Figure S1B, we found that the most abundant small RNAs produced in the leaves of “GL-3” apple were 24 nt in length, followed by 23 nt, 22 nt, and 21 nt. Additionally, 284 conserved miRNAs belonged to 47 miRNA families (Figure S1A). Among these families, miR156 is the largest, with a total of 37 members, followed by the miR166, miR167, and miR159 families, which contain 17, 15, and 14 members, respectively. Furthermore, there are some miRNA families with only one member, such as miR1510, miR4243, miR7533, miR7125, and miR8775.

To better understand the DE-miRNAs and their target genes, we performed GO (Gene Ontology) enrichment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis on the predicted target genes. The results are shown in Figure S1C,D. According to Figure S1C,D, the target genes of the DE-miRNAs are mainly enriched in biological processes such as defense response, regulation of transcription by RNA polymerase II, cell differentiation, cellular response to iron ions, and signal transduction. The KEGG analysis results indicate that the target genes of the DE-miRNAs play significant roles in pathways related to spliceosomes, plant–pathogen interactions, starch and sucrose metabolism, and MAPK signaling. Based on the GO and KEGG analyses, it can be concluded that these target genes of DE-miRNAs play important roles in the response of “GL-3” apple leaves to C. gloeosporioides infection.

3.2. Validation of sRNA-Seq Data Using RT-qPCR

To investigate the credibility of sRNA-seq, the expression profiles of nine differentially expressed miRNAs (DE-miRNAs), including miR395a, MIR10994-p5_1ss6TC, MIR10986-p3_1ss21GT, MIR2916-p5_1ss5AG, MIR390a-p3, miR156e_R+1, MIR395c-p5, miR167a, and PC-3p-4885_278, were detected through RT-qPCR at 0 h, 24 h, and 72 h post-infection. As shown in Figure 1, RT-qPCR demonstrated that miR395a exhibited a significant increase as the infection time increases; this trend is consistent with the sRNA-seq data. Similarly, the expression levels of MIR10994-p5_1ss6TC and MIR10986-p3_1ss21GT also show an increase with the increase in the infection time, and the expression levels are also increasing. Interestingly, most of these miRNAs were upregulated at 24 h or 72 h, except miR167a and PC-3p-4885_278. In general, the results from RT-qPCR aligned well with the sRNA-seq data.

3.3. Identification and In Silico Analysis of miRNA Response to C. gloeosporioides

To investigate the possible miRNAs response to C. gloeosporioides, we selected a miRNA of particular interest, MIR396d-p3, based on p-values and fold change (FC). This is because miR396 is a highly conserved small RNA molecule that has been identified in a wide range of plant species. According to the miRBase database (version 22.1), information about the miR396 family has been found in 52 plant species (Figure S2). miR396 may hold significant research value. Meanwhile, MIR396d-p3 expression significantly increased after 24 h of infection, indicating its response to C. gloeosporioides infection (Figure 2A). First, we predicted the RNA secondary structure of the MIR396d-p3 precursor through the UNAFold Web Server. The results were shown as Figure 2B: the MIR396d-p3 precursor can form a secondary structure, indicating that the miRNA precursor may be stable and capable of being successfully processed into mature miRNA. Meanwhile, by aligning with the apple genome, it was found that the MIR396d-p3 precursor is located between positions 2032169 and 2032271 on chromosome 2 (Figure 2C).

To understand which environmental factors might influence MIR396d-p3, we predicted the cis-acting elements in the promoter region of the MIR396d-p3 precursor. The results, shown in Figure S3, indicate that factors such as pathogen infection, light, jasmonic acid, and abscisic acid can influence its expression. In addition, by comparing with the existing apple miR396 in the miRBase database, we found that apple miR396 is highly conserved, despite some genetic evolution observed in MIR396d-p3 (Figure 2D and Figure S4).

3.4. MIR396d-p3 Cleaves MdUGT89A2 and MdRGA3 Transcripts

To screen the target genes of MIR396d-p3, we conducted a series of computational predictions through psRNATarget. As shown in Table S1, eight target genes were selected based on their predicted interactions with MIR396d-p3, including 1-aminocyclopropane-1-carboxylate synthase 7-like, transcription factor bHLH111-like, receptor protein kinase ZmPK1, WAT1-related protein, disease resistance protein RGA3, UDP-glycosyltransferase 89A2 (UGT89A2), peroxidase 29, and serine acetyltransferase. Next, we conducted 5′ RACE experiments on these eight target genes and found that only UGT89A2 and RGA3 interacted with MIR396d-p3 (Figure 3A). To further clarify that MIR396d-p3 can cleave MdUGT89A2 and MdRGA3 transcripts, we performed heterologous expression in N. benthamiana. First, we constructed 35S:MIR396d-p3 and the corresponding 35S-UGT89A2:GUS, 35S-RGA:GUS using the Cloning Kit V2 (Figure 3B). Then, we co-injected them into N. benthamiana to assess their expression and detected GUS activity to determine if they interacted. Meanwhile, 35S:GUS served as a positive control, and 35S:MIR396d-p3 served as a negative control. As shown in Figure 3D, 35S-UGT89A2:GUS and 35S-RGA:GUS did not show significant differences compared to 35S:GUS; however, when they were co-expressed with MIR396d-p3, their expression levels were significantly reduced, indicating that MIR396d-p3 can cleave MdUGT89A2 and MdRGA3 transcripts. GUS staining also exhibited a similar phenotype (Figure 3C).

To assess the expression pattern of MIR396d-p3 and its target genes MdUGT89A2 and MdRGA3 in the susceptible variety “GL-3” and the resistant variety “FJ”, RT-qPCR assay was conducted at 0, 24, and 72 h post-C. gloeosporioides infection. As shown in Figure 4, the expression level of MIR396d-p3 was significantly upregulated in”GL-3”, while MdUGT89A2 and MdRGA3 were strikingly downregulated. Meanwhile, the expression level of MIR396d-p3 in “FJ” continuously decreases as the infection time increases, while MdUGT89A2 and MdRGA3 were upregulated. Collectively, MIR396d-p3 can negatively regulate the expression of MdUGT89A2 and MdRGA3.

3.5. Responsiveness of MIR396d-p3 to C. gloeosporioides Infection

To investigate the involvement of MIR396d-p3 in the apple’s response to C. gloeosporioides, we cloned the MIR396d-p3 precursor into the pFGC5941 vector to construct the MIR396d-p3 overexpression vector (Figure 5A). Then the overexpressed constructed vector was transformed into the resistant apple cultivar “FJ” via Agrobacterium-mediated transformation. The expression level of MIR396d-p3 was assessed through RT-qPCR at 4 d post-inoculation. As shown in Figure 5B, the expression level of MIR396d-p3 was significantly higher in the MIR396d-p3 overexpression plants compared to wild-type “FJ” and the pFGC5941 EV control (EV).

Disease lesion areas were measured at 2 d post-C.gloeosporioides inoculation. The OE-MIR396d-p3 plants exhibited significantly larger lesions compared to “FJ” and EV (Figure 5C,D). In addition, C. gloeosporioides biomass in the OE-MIR396d-p3 plants was significantly higher than in the “FJ” and EV plants (Figure 5E). Based on these results, we therefore predicted that the MIR396d-p3 is involved in the apple resistance response to C. gloeosporioides.

To further explore the function of MIR396d-p3 during the C. gloeosporioides infection, we constructed an MIR396d-p3 silencing (STTM-MIR396d-p3) vector using STTM technology (Figure 6A). To evaluate the efficiency of silence, the STTM-MIR396d-p3 vector was introduced into the susceptible apple cultivar “GL-3” via Agrobacterium-mediated transformation. We found that the expression level of MIR396d-p3 was significantly reduced in STTM-MIR396d-p3 plants, indicating that the MIR396d-p3 is successfully silencing (Figure 6B). Subsequently, these leaves were inoculated with C. gloeosporioides. After 2 days of inoculation, disease lesion areas were counted. Compared to the “GL-3” and EV plants, the STTM-MIR396d-p3 plants displayed significantly reduced lesion areas (Figure 6C,D). The reduced C. gloeosporioides biomass in STTM-MIR396d-p3 plants, quantified by RT-qPCR, further supports the observed effect that MIR396d-p3 silencing enhances apple resistance to C. gloeosporioides. These findings strongly indicate MIR396d-p3 negatively affects resistance to C. gloeosporioides.

3.6. MdUGT89A2 and MdRGA3 Are Involved in the Resistance to C. gloeosporioides in Apple

We next examined the impact of MdUGT89A2 and MdRGA3 on apple’s resistance to C. gloeosporioides. Full-length MdUGT89A2 and MdRGA3 sequences were amplified and cloned into the pFGC5941 vector to generate overexpression constructs (Figure S5). The construct was subsequently introduced into “GL-3” by Agrobacterium-mediated infiltration. RT-qPCR analysis confirmed successful overexpression of MdUGT89A2 and MdRGA3 in the OE-MdUGT89A2 and OE-MdRGA3 plants at 4 d post-transformation, respectively (Figure 7A). Lesion areas were measured 2 days following C. gloeosporioides inoculation. The OE-MdUGT89A2 and OE-MdRGA3 plants displayed a significantly reduced lesion area compared with the “GL-3” and EV plants. This similar result was further confirmed by the relative biomass (Figure 7D). These results indicated MdUGT89A2 and MdRGA3 positively regulate apple resistance to C. gloeosporioides.

We used RT-qPCR to detect the expression level of MdUGT89A2 and MdRGA3 in the corresponding RNAi-silenced plants and found that MdUGT89A2 expression was reduced by approximately ~76.74%, while MdRGA3 expression was reduced by ~69.2%, relative to control plants (Figure 8A). Following inoculation with C. gloeosporioides, the lesion size was assessed on RNAi-MdUGT89A2, RNAi-MdRGA3, “FJ”, and EV plants at 2 d post-inoculation. Silencing of MdUGT89A2 and MdRGA3 resulted in significantly larger lesions compared to “FJ” and EV plants. Consistent with the larger lesion sizes, C. gloeosporioides biomass was significantly elevated in plants with RNAi-mediated silencing of MdUGT89A2 and MdRGA3 (Figure 8D). Collectively, MdUGT89A2 and MdRGA3 function as positive regulators of apple resistance to C. gloeosporioides.

4. Discussion

In this study, we investigated the role of microRNA (miRNA) in apple’s response to C. gloeosporioides, the causal agent of GLS. Through sRNA sequencing, a novel miRNA, MIR396d-p3, was identified. Bioinformatic analysis of MIR396d-p3 target genes and its promoter region indicated that MIR396d-p3 may regulate key aspects of biological processes, including plant defense, signal transduction, plant–pathogen interactions, and light-mediated responses. Previous studies have reported the involvement of Arabidopsis miR396 in mediating immune responses against fungal pathogens [15]. Therefore, we hypothesize that MIR396d-p3 may also play a role in apple’s defense against C. gloeosporioides infection.

MiR396-mediated cleavage of growth-regulating factors (GRFs) has been observed in diverse plant species, including switchgrass (Panicum virgatum) [34], rice (Oryza sativa) [16], Arabidopsis (Arabidopsis thaliana) [15], and poplar (Populus spp.) [35], tomato (Solanum lycopersicum) [36], and soybean (Glycine max) [18]. The miR396-GRF regulatory module represents a novel and efficient mechanism for modulating plant growth, development, and responses to environmental stresses. Interestingly, our integrated analysis of bioinformatics prediction and experimental validation identified two novel MIR396d-p3 target genes, MdUGT89A2 and MdRGA3. These previously unreported targets significantly advance our understanding of the miR396-mediated regulatory mechanisms underlying plant stress responses.

Plants have independently evolved UDP-glycosyltransferases (UGTs) with specific substrate specificities, enabling fine-tuned regulation of defensive secondary metabolites and thereby resisting pathogen infection. They work by attaching glucose to various substances, such as toxins, hormones, and other metabolites [20]. This process usually helps detoxify harmful substances, protecting the plant from damage. In relation to fungal pathogens, UGTs can alter mycotoxins produced by the fungus, making them less harmful and impeding the pathogen’s ability to cause infection [23]. We found that overexpressing MdUGT89A2 enhances resistance to C. gloeosporioides. This discovery opens new avenues for developing disease-resistant apple varieties by manipulating this crucial regulatory pathway. However, we have not yet studied the potential substrates of UGTs and what immune responses are activated in response to pathogen infection. On the other hand, MdRGA3 belongs to the family of R genes, which are essential for recognizing and defending against pathogen attacks [37,38]. Overexpression of MdRGA3 significantly increases the resistance to C. gloeosporioides infection. This further supports the notion that MdRGA3 is crucial for apple resistance to C. gloeosporioides.

miRNAs, as key regulatory molecules, orchestrate a complex network of gene expression in response to pathogen infection, including in apples [39]. For example, Md-miR156ab and Md-miR395 target WRKY transcription factors, thereby affecting resistance to Alternaria alternata by modulating the expression of pathogenesis-related (PR) genes [13]. Similarly, Md-miR482 has been confirmed to regulate the expression of NBS-LRR genes, with overexpression of miR482 attenuating disease resistance by inhibiting MdTNL1 expression [12]. To our knowledge, there is no report about the involvement of miR396 in the interaction between apple and pathogenic fungi. This study is the first to reveal the regulatory role of MIR396d-p3 in apple–fungal interactions. In addition, RGA3 (a member of the R gene family) and UGT89A2 (a key regulator of secondary metabolism) were reported as MIR396d-p3 target genes for the first time. This highlights the complexity of plant immune responses, which are mediated by both R genes and the regulation of secondary metabolite biosynthesis. This study not only fills the research gap regarding miRNA in apple—C. gloeosporioides interactions but also enriches the molecular basis of apple disease resistance mechanisms through integrating various regulatory networks.

In addition, several strategies can be employed to enhance disease resistance in plant breeding, including traditional breeding methods, marker-assisted selection, and various genetic engineering techniques. One particularly promising approach focuses on manipulating small RNA pathways. This involves either suppressing small RNAs that inhibit defense responses or boosting the expression of genes that confer resistance, thereby enhancing the plant’s immune response and the ability to resist pathogenic bacteria.

5. Conclusions

In summary, this study reveals that MIR396d-p3 negatively regulates apple resistance to C. gloeosporioides by suppressing the expression of MdUGT89A2 and MdRGA3. Functional analyses demonstrated that overexpressing MdUGT89A2 or MdRGA3 enhances tolerance to C. gloeosporioides, while silencing MdUGT89A2 or MdRGA3 increases susceptibility to C. gloeosporioides. This study identifies a novel MIR396d-p3-MdUGT89A2/MdRGA3 regulatory axis, deepening the understanding of the mechanism of miRNA in the interaction between apples and pathogenic fungi, and also provided references for potential resistance breeding sites.