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Article

Genome-Wide Identification of miRNAs in Oily Persimmon (Diospyros oleifera Cheng) and Their Functional Targets Associated with Proanthocyanidin Metabolism

by
Meng Zhang
1,2,
Rong Wu
3,
Xinlong Hu
1,2,
Zhengrong Luo
3,
Qinglin Zhang
3,* and
Sichao Yang
1,2,*
1
Jiangxi Key Laboratory of Horticultural Crops (Fruit, Vegetable & Tea) Breeding, Horticultural Institute, Jiangxi Academy of Agricultural Sciences, Nanchang 330200, China
2
Nanchang Key Laboratory of Germplasm Innovation and Utilization of Fruit and Tea, Horticultural Institute, Jiangxi Academy of Agricultural Sciences, Nanchang 330200, China
3
National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan 430070, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2025, 11(1), 41; https://doi.org/10.3390/horticulturae11010041
Submission received: 29 October 2024 / Revised: 22 December 2024 / Accepted: 27 December 2024 / Published: 5 January 2025
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Abstract

:
Cultivated persimmon (Diosspyros kaki Thunb.) is a hexaploid (mostly) or a nonaploid with high heterozygosity, hindering molecular genetic studies on proanthocyanidin (PA) metabolism, which is a major trait for persimmon astringency. Recently, one of its wild diploid relative species, oily persimmon (Diospyros oleifera), has been assembled with a chromosome-level reference. Thus, oily persimmon is now regarded as a model plant for discovering new genes associated with PA metabolism, which is highly accumulated in the fruits of this genus. In our study, we identified genome-wide microRNAs (miRNAs) and their precursor sequence based on the chromosome-scale genome of oily persimmon and the miRNA database of “Eshi 1” according to the sequence alignment and secondary structure accession. The targets were predicted on the psRNATarget software based on the genome CDS database. The size, conservation, diversity, stem-loop hairpin structures, and genome location of miRNA or the precursor sequence were analyzed by bioinformatics tools. The promoter elements of the miRNA genes were predicted on the promoter-2.0 software, which indicated that the abundant cis-acting elements were light responsiveness, promoter, and enhancer regions. The qRT-PCR assay was performed to elucidate the potential expression patterns of precursor miRNA and their targets during fruit development, and one target gene, DkMYB22, of miR2911 was verified to promote the conversion of soluble tannins into insoluble tannins involved in the deastringency in persimmons. Together, this study provides a robust foundation for further functional verification of these miRNAs associated with the natural deastringency process in persimmon, thereby facilitating advancements in persimmon fruit breeding.

1. Introduction

Persimmon (D. kaki Thunb.) belongs to the Diospyros genus, Ebeneceae family. According to the Flora of China, there are about 500 species of Diospyros, 60 of which have been found in China. The Diospyros genus is mainly distributed in the tropics and subtropics, and less in the temperate zone, which includes D. kaki Thunb., Diospyros lotus, D. oleifera, Diospyros rhombifolia, Diospyros glandulosa, and Diospyros glandulosa. D. kaki Thunb. is hexaploid (2n = 6x = 90) and is a representative species of the Diospyros genus, with about 1000 species [1,2]. D. lotus and D. oleifera are common diploid (2n = 2x = 30), they are widely used as rootstocks [3]. Persimmon fruit, stems, and leaves contain a lot of tannin, which is the main raw material for the synthesis of persimmon lacquer. Different from the fruit of D. kaki and D. lotus, the D. oleifera fruit has a trichome structure on the surface and can secrete oil (Figure 1). Thus, the material D. oleifera is also called “Youshi” traditionally in China, which means “oil persimmon” in Chinese [4]. According to the phylogenetic relationship of D. oleifera and other Diospyros genus, based on the reported genome sequence information, we can find that D. oleifera and D. kaki have a very close relationship, which indicates that the D. oleifera could be used as a model plant for studies on D. kaki [5].
Proanthocyanidins (PAs) are high molecular phenolic compounds that are polymerized by flavan-3-ol units. During fruit development, persimmons accumulate large amounts of PAs in vacuoles of “tannic cells”, resulting in a dry or wrinkled feeling due to the coagulation of proteins in the mouth [6]. The biosynthesis of PAs includes four pathways of metabolism, and most of the structural genes have already been identified [7]. Moreover, the transcription factors that regulate the expression of those genes, such as MYB2, MYB4, DkbZIP5, DkMYB14, basic helix–loop–helix (bHLH), and WD-repeat (WDR) protein gene, have also been verified [6,8]. The J-PCNA loses the astringency at the early stage of fruit development due to the “dilution effect”, where the tannin cells stop developing at the early stage when the fruit is still growing, so the astringency removal predominantly occurs via tannin dilution as the fruit grows larger. The natural deastringency of C-PCNA is also due to the “dilution effect”, but it more tends toward the “coagulation effect”, where the soluble PAs react with the acetaldehyde to convert into insoluble PAs [9,10]. In addition, it is reported that the genes related to acetaldehyde metabolism, including alcohol dehydrogenase (DkADH1), pyruvate decarboxylase (DkPDC1, and DkPDC2), and aldehyde dehydrogenase (ALDH), are probably involved in the natural deastringency of C-PCNA fruit [10].
MiRNAs are endogenous and non-coding small RNAs, which are involved in post-transcriptional gene regulation through RNA degradation or translational repression [11]. At present, the miRNAs have been reported to be involved in various biological functions, such as cell proliferation, response to abiotic stress, signal transduction, metabolism, and inflammation [12]. Particularly, in model plants like Arabidopsis, rice, Medicago truncatula, and wheat, a lot of miRNAs have been identified with the advent of next-generation sequencing technology [13]. But for the persimmon, the miRNAs involved in the PA mechanism have still not been identified. In this study, we characterized D. oleifera miRNAs based on the D. oleifera genome and information available in miRNA databases, which will be helpful for subsequent studies on the natural deastringency mechanisms of Chinese PCNA persimmon.

2. Materials and Methods

2.1. Date Collection for the Prediction of miRNAs and Pre-miRNAs in Persimmon

The D. oleifera genome and CDS database were downloaded from the Diospyros Genome Database (https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA532832; accessed on 14 January 2022), and the ‘Eshi 1’ persimmon miRNAs were downloaded from NCBI (http://www.ncbi.nlm.nih.gov/sra/?term=SRX796050; http://www.ncbi.nlm.nih.gov/sra/?term=SRX796055; accessed on 17 August 2022). We performed a BLAST analysis with an e-value of 1000, word size of 7, and mismatch value of less than 4 nt by submitting the ‘Eshi 1’ persimmon miRNAs as the queries and selecting the oily persimmon genome as the subject to predict the new miRNAs from the oil persimmon genome [14]. The sequence data approximately 505 bp upstream and downstream of the sequence alignment site of the query miRNAs on the oily persimmon genome were used to predict the pre-miRNAs with the following criteria: (i) sequences without any multi-loop structures at the mature miRNA region in the potential precursors or hairpin structures, (ii) the stem-loop structure includes the mature miRNA, (iii) the mature miRNA and miRNA* sequence does not extend to the head of the hairpin structure, (iv) the mature miRNA has less than 6 nt mismatches with miRNA* that do not include any loop or break, (v) there are no mismatches in the cleavage region of the DICER-LIKE enzyme on the hairpin structure, and (vi) the formation of the stem-loop structure has a value for MFEI ≥ 0.41 [15,16].

2.2. Phylogenetic and Conservation Analysis of the miRNAs

To investigate the phylogenetic relationships of the identified miRNAs (miR156, miR395, miR396, and miR2911), we downloaded the corresponding mature miRNA sequences from Arabidopsis thaliana, Citrus clementine, Citrus sinensis, Malus domestica, Manihot esculenta, M. truncatula, Nicotiana tabacum, Picea abies, Populus trichocarpa, Solanum lycopersicum, and Vitis vinifera using the miRBase database. Subsequently, a multiple sequence alignment was performed using DNAMAN9.0. The maximum likelihood statistical method was used to generate a phylogenetic tree based on the Tamura–Nei model and 1000 boot-strap repeats using the MEGA7.0 software. The conservation analysis of the identified miRNAs and pre-miRNAs was conducted on WebLogo (Version 2.8.2).

2.3. Predicting the Target Genes of the miRNAs

Based on the mature miRNAs and the gene sequence information of D. oleifera, a target gene prediction was made using psRNATarget software. The predicted target gene sequences were compared with seven databases using a BLAST algorithm (NR (https://ftp.ncbi.nih.gov/blast/db/, accessed on 25 August 2022), Swiss-Prot (http://www.uniprot.org/, accessed on 17 August 2022), GO (Gene Ontology, http://www.geneontology.org/, accessed on 17 August 2022), COG (http://www.ncbi.nlm.nih.gov/COG/, accessed on 17 August 2022), KEGG (Kyoto Encyclopedia of Genes and Genomes, http://www.genome.jp/kegg/, accessed on 17 August 2022), KOG (https://ftp.ncbi.nih.gov/pub/COG/KOG/kog, accessed on 17 August 2022), and Pfam (http://pfam.xfam.org/, accessed on 17 August 2022) to obtain the annotation information of all the identified miRNA target genes, including the number of annotations for each and the prediction results based on different samples. In addition, the annotations were used to further analyze the number of differentially expressed miRNA target genes between samples.

2.4. Genome Location of the miRNAs in D. oleifera

The miRNAs were located on the chromosome according to the chromosome length information of the D. oleifera genome using MG2C software (v2.1).

2.5. RNA Extraction and cDNA Synthesis

Total RNA was extracted from the fruit flesh of oily persimmon utilizing RNAiso Plus reagent (Tiangen, Beijing, China) according to the manufacturer’s protocol. The brightness of the 28 S/18 S bands and the absence of obvious dragging were determined via 1% agarose gel electrophoresis. The RNA concentration was determined using a Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). cDNA was synthesized using PrimeScript 1st Strand cDNA Synthesis Kit (TaKaRa, Dalian, China) for use in the qRT-PCR assay.

2.6. RT-qPCR Analysis of the Pre-miRNAs and Their Target Genes

Primer Premier 5 software was used to design RT-qPCR primers, and persimmon actin was used as the internal reference gene for RT-qPCR analysis. The primers used are shown in Supplemental Table S1. The reaction conditions were TB Green Premix Ex Taq II, 10 μL; cDNA template, 2 μL; forward and reverse primers, 0.8 μL each; and dd H2O, 6.4 μL. The PCR procedure was 95 °C for 30 s; 95 °C for 5 s, then 60 °C for 30 s, for a total of 40 cycles; 72 °C 20 s. There were 3 technical replicates for each gene, and the relative gene expression was calculated using the 2−∆∆Ct method.

2.7. Predicting the Cis-Acting Elements in the Promoter Region of the Pre-miRNA Genes

To investigate the regulation mechanism of transcriptional factors on the pre-miRNAs, we obtained the potential promoter region sequences from D. oleifera genome data and predicted the potential cis-acting elements. Specifically, we chose the TSSs that were located most distally from the mature miRNAs’ start positions for the MIR genes with multiple TSSs to predict the cis-acting elements.

2.8. PA Content Measurement

The content of soluble and insoluble PAs in the fruits and transient transformed leaves were determined using the Folin−Ciocalteu method [17].

2.9. Subcellular Localization

The upstream and downstream specific primers DkMYB22F1 and DkMYB22R1 (Supplemental Table S1) of DkMYB22 were designed to contain restriction sites for BamH I and Kpn I. A pMDC32-DkMYB22 plasmid with the correct sequencing was used as a template for PCR amplification. Then, the PCR product and 101LYFP empty vector were double-digested with BamH I and Kpn I, and the extracted products were purified and linked with T4 DNA ligase to construct the 35S::DkMYB22-YFP subcellular localization vector. The correctly sequenced plasmid was transferred into Agrobacterium GV3101 using electroporation. The 35S::DkMYB22-YFP plasmid and the auxiliary vector p19 were re-suspended and mixed evenly, and the re-suspended liquid was injected into the back of healthy N. benthamiana leaves using a 1 mL disposable syringe. After 72 h of light culture, the distribution of the YFP fusion protein in the tobacco leaves was observed using laser confocal microscopy (BX63, Olympus, Japan).

2.10. Transient Transformation in Persimmon Leaves

After designing the pairs of attB site + gene specific primers DkMYB22 OE_attB-F/R, DkMYB22i_attB-F/R (Supplemental Table S1), the plasmid containing the DkMYB22 sequence was used as the template to amplify the full-length and partial gene specific fragments of DkMYB22. The over-expression vector pMDC32-DKMYB22 and the interference expression vector pH7GWIWG2-DkMYB22 were then constructed using gateway technology and the full-length and partial gene fragments, respectively. The constructed expression vectors were introduced into Agrobacterium GV3101 via the heat shock method, and the transient expression of persimmon leaves in vivo was performed following previously described methods [18].

3. Results

3.1. Identification of miRNA Precursors Involved in the PA Mechanism in Persimmons

A total of 229 predicted miRNA precursors were obtained from a search of the available ‘Eshi 1’ small RNA datasets. The pre-miRNAs can be sorted into four main groups with different size ranges: 52 pre-miRNA156 from 83 to 256 bp, 72 pre-miRNA395 from 66 to 226 bp, 102 pre-miRNA396 from 74 to 277 bp, and 3 pre-miRNA2911 from 75 to 95 bp. In order to identify the possible miRNA precursors in D. oleifera, after aligning the known miRNAs with the D. oleifera genome and considering proper secondary structures, we identified 22 miRNA precursors that belong to four families. The predicted secondary structures of the miRNAs are shown in Figure 2. This identification of miRNAs indicates that the miRNAs involved in the PA mechanism widely exist in the D. oleifera genome.

3.2. Alignments and Conservation Analysis of the miRNA Precursor Sequences in D. oleifera

We performed an alignment analysis of each of the four identified miRNA families in the ‘Eshi 1’ miRNA database and the predicted miRNA precursors for ‘D. oleifera’ to detect the presence of conserved sequences using DNAMAN9.0, each of which showed nucleotide sequence similarity to different members of the same miRNA family, including MIR156 (36.77%), MIR395 (51.92%), MIR396 (34.91%), and MIR2911 (72.77%) (Supplemental Figure S1). Overall, there is a highly conserved mature miRNA sequence in every member of the pre-miRNAs that belong to the same family. We also constructed a graph by aligning the consensus structure of multiple RNA sequences in the web-based tool RNALogo. As a result, the mature miRNA region showed strong conservation, while large diversity existed in the loop regions of the MIR genes (Figure 3).

3.3. MiRNA Gene Clusters in D. oleifera

We performed a clustering and conservation analysis of the four identified miRNA families (miR156, miR395, miR396, and miR2911) along with previously reported miRNAs from M. domestica, C. sinensis, V. vinifera, A. thaliana, M. truncatula, and S. lycopersicum. The results show that nucleotide sequences were highly similar between members of the same miRNA family in different species, including miR156 (62.65%), miR395 (77.59%), miR396 (66.59%), and miR2911 (95%) (Supplemental Figure S2). As a result of the clustering analysis, dk-miR156a/c/d/g/h was grouped with vvi-miR156i and csi-miR156f-5p, dk-miR156e was grouped with mdm-miR156z, and dk-miR156b/f was grouped with ctr-miR156 and mdm-miR156e (Figure 4A). Regarding miR395, dk-miR395a/b was grouped with vvi-miR395c and ath-miR395a, dk-miR395c was grouped with mtr-miR395h and vvi-miR395i, and dk-miR395d was grouped with mtr-miR395h (Figure 4B). For miR396, dk-miR396a was grouped with csi-miR396a-5p, dk-miR396b/g was grouped with csi-miR396a-3p, dk-miR396c was grouped with csi-miR396f-3p and ath-miR396b-3p, dk-miR396d/h was grouped with mes-miR396a, dk-miR396e/i was grouped with ptc-miR396b and mdm-miR396b, dk-miR396f was grouped with ptc-miR396d, dk-miR396j was grouped with csi-miR396e-5p and mes-miR396e, and dk-miR396k was grouped with ptc-miR396e-5p (Figure 4C). Typically, multiple MIR genes exist in the genome in a clustered manner, forming polycistronic primary transcripts during transcription. We mapped these miRNAs to the genome using the MG2C software, which revealed that miR156a was located on Chr3/14, miR156b was located on Chr1/8/15, miR156e was located on Chr4/14, miR156h was located on Chr14, miR395b was located on Chr2, miR396b was located on Chr6, miR396e was located on Chr3/10/12/14, miR396f was located on Chr10, and miR2911a/b was located on Chr6/12/14 (Supplemental Figure S3).

3.4. MiRNA Target Prediction and Functional Analysis

Target genes were predicted using bioinformatics based on almost perfect matching of the miRNA and target gene sequences. The biological functions of the identified miRNAs were further estimated by annotating the functions of the predicted target genes of the miRNAs. A total of 35 gene targets were predicted for the four miRNAs.
A large amount of research, including bioinformatics analysis and experimental verification, has reported that many of the target genes of miRNAs are transcription factors involved in plant growth and development and the regulation of secondary metabolism. In this study, we also predicted a large number of similar transcription factors to be the targets of the identified miRNAs. MYB transcription factors comprise a protein family with a conserved MYB DNA binding domain and are considered to be involved in the regulation of secondary metabolism, cell morphogenesis, meristem formation, and the cell cycle. Our results showed that MYB proteins might be the target of miR156 and miR2911. Moreover, we predicted that miR156 directly regulated the squamosa promoter-binding-like protein 2/6/7/9/13A/16/18, and miR395 directly regulated the transcription factor bHLH48/90/147. Aside from MYB, bHLH, SPL, ERF, and WD transcription factors, there were several genes with structural enzyme function that have been detected as the targets of miRNAs, such as alcohol dehydrogenase (miR156), PDC2 (miR396), laccase-11-like (miR396), and transmembrane 9 superfamily member 1 (miR396) (Table 1).

3.5. Cis-Acting Elements in D. oleifera miRNA Promoters

We were able to accurately locate the miRNA promoter sequence by identifying the TSSs of each of the 12 miRNA genes. Typically, miRNA gene promoters are predicted using TSS sequences 2000 bp, 1000 bp, and 800 bp upstream to fully recognize putative promoter motifs. In this study, the sequence 2000 bp upstream of the TSSs of the 12 miRNA genes was used to reveal the putative promoter elements according to the PlantCARE database. TATA boxes were detected in all 12 examined D. oleifera miRNA promoter regions, which implied that the promoter characteristics of these miRNA genes were the same as those of the protein-coding genes.
In addition to the TATA and CAAT boxes, we identified more than 1429 promoter elements for the 12 miRNA genes. Among these cis-acting elements, the promoter and enhancer regions were the most abundant (detected 168 times among the 12 sequences). More specifically, miR156b-Chr8 and miR156e-Chr4 (21) contained the most promoter and enhancer regions, followed by miR395b-Chr2 (20). The second most abundant element was the light-responsive element (137). miR396f-Chr10 and the miR156e-Chr4 (16) have the most light-responsive elements, followed by miR396f-Chr10 (14). The third most abundant element was the MeJA-responsive element. Moreover, seed-specific regulation, circadian control, and endosperm expression were only detected in miR156e-Chr14, miR396b-Chr6 and miR2911-Chr12, respectively (Figure 5). Therefore, we speculate that light is involved in the miRNA regulation of persimmon proanthocyanidin metabolism.

3.6. Expression Level of Pre-miRNAs and Corresponding Targets During Fruit Development in Persimmons

To explore the expression patterns of the pre-miRNAs and their target genes in the persimmon fruit during development, pre-miRNAs (MIR156a, MIR396b, MIR396e, and MIR2911b) were chosen for qRT-PCR analysis. MIR156a was downregulated at 2.5–25 WAB (weeks after bloom). The expression level of MIR396b was low at 2.5–10 WAB and significantly upregulated at 25 WAB. MIR396e showed a downregulated expression trend at 2.5–25 WAB and decreased significantly at 10–25 WAB. The expression level of MIR2911b showed a trend of downregulation at 2.5–5 and 10–25 WAB and was slightly downregulated at 5–10 WAB (Figure 6). This implies that the expression levels of MIR156a, MIR396e, and MIR2911b are positively correlated with the change in PA content during fruit development, while the expression of MIR396b is negatively correlated with the change in PA content during fruit development.
The expression level of MIR156a’s target genes showed various trends over the course of development. ADH3 remained basically unchanged from 2.5 to 10 WAB and showed a significant downregulation trend at 10 to 25 WAB. The expression level of bHLH48 showed upregulated expression at 2.5–15 WAB and was downregulated at 15–25 WAB. SPL9 showed an upward trend at 2.5–25 WAB. For MIR396, the expression level of the target gene WD40 showed a trend of downregulation at 2.5–25 WAB, where bHLH90 showed upregulated expression at 2.5–10 WAB and was downregulated at 10–25 WAB. The expression level of the target gene WRKY6 of MIR2911 showed a trend of upregulation at 2.5–25 WAB (Figure 7).
The expression pattern of MIR156a was negatively correlated with the expression pattern of bHLH48 at 5–10 WAB and negatively correlated with the expression pattern of SPL9 at 2.5–25 WAB, indicating that miR156a negatively regulates the expression of SPL9. At 5–25 WAB, the expression pattern of MIR396b was negatively correlated with the expression pattern of WD40, indicating that miR396b negatively regulates the expression of WD40. The expression pattern of MIR396e was negatively correlated with the expression level of bHLH90 at 5–10 WAB. At 5–25 WAB, the expression pattern of MIR2911b was negatively correlated with the expression pattern of WRKY6, indicating that miR2911b negatively regulates the expression of WRKY6. Taken together, these data suggest that miR156 and miR2911 may repress the expression of their corresponding target genes that negatively regulate the natural deastringency process, while miR396b positively regulates the C-PCNA persimmon fruit natural deastringency via the repression of WD40.

3.7. The Functional Analysis of the Target Gene DKMYB22 of miR2911

Interestingly, among the target genes corresponding to these miRNAs, we found that an MYB transcription factor named DkMYB22 plays a key role in the late stage of the natural deastringency of C-PCNA persimmon. It was predicted to be a target gene of miR2911. To verify the function of DkMYB22 in deastringency in persimmon, we analyzed the expression level of DkMYB22 and the tannin content change pattern in fruit over the course of development in ‘Ganfang 1’. DkMYB22 showed a trend of upregulation, and the expression pattern of DkMYB22 showed a negative relationship with the change tendency of the tannin content (Figure 8). Subcellular localization was carried out in tobacco leaf cells to further confirm that DkMYB22 is located in the nucleus (Figure 9). Next, the over-expression vector pMDC32-DkMYB22 (OE-DkMYB22) and silencing-expression vector pH7GWIWG2-DkMYB22 (SE-MYB22) were transiently transfected into leaf tissue of ‘Ganfang 1’ in vivo. This indicated that the transient overexpression of DkMYB22 upregulated DkMYB22 significantly, which resulted in a decrease in soluble tannins and an increase in insoluble tannins, while the transient silencing of DkMYB22 downregulated DkMYB22, which resulted in an increase in soluble tannins and a decrease in insoluble tannins (Figure 10). Taken together, DkMYB22 may promote the conversion of soluble tannins to insoluble tannins, which is a part of the deastringency process in persimmon.

4. Discussion

At present, with the publication of the persimmon genome, there is an abundance of information resources and entry points for the study of the molecular mechanisms of persimmon’s secondary metabolism. Therefore, the molecular research on persimmon can be improved at the genomic level [19]. Based on the existing high-quality diploid and hexaploid genomes of persimmon, it would be very convenient to screen and verify the miRNAs related to each metabolic pathway over the course of persimmon development to provide strong scientific evidence for studies on genetic breeding and molecular mechanisms of C-PCNA.
The study of persimmon tannin metabolism is the most important topic to explore within the natural deastringency of persimmon [20]. As a diploid, the oily persimmon is rich in persimmon PA substances and is ideal for studying persimmon PA metabolism [19]. Although a large number of structural genes and key transcription factors involved in persimmon PA metabolism have been identified at the transcriptome and metabolome levels [7,21], there are few reports on the level of miRNAs involved in this metabolism, particularly genome-wide miRNA identification and functional studies. Through comprehensive analysis of the D. oleifera genome database and the ‘Eshi 1’ miRNA database using bioinformatics methods, four miRNA family members were fully screened and accurately located on different chromosomes of D. oleifera, and 22 miRNA precursor sequences were identified. The research shows that plant miRNA precursors are relatively diverse in structure and size [22]. After analyzing the length distribution of the pre-miRNAs, we found that lengths of 77–99, 100–186, and 200–284 nt accounted for 17.9%, 73.36%, and 3.06% of all the pre-miRNAs, respectively. Overall, this distribution of pre-miRNA lengths is similar to the corresponding distributions in Arabidopsis, rice, cotton, and maize [23]. In plant genomes, homologous genes involved in plant secondary metabolism are often clustered within the same region on a chromosome [24]. We also found that different members of the same miRNA family are closely linked to each other on the same chromosome.
MiRNAs are highly conserved in plants, so we often use miRNAs with known functions in one plant to identify unknown miRNAs in another. In addition, the sequence of one miRNA in different plants is highly similar, and the mature miRNA and precursor miRNA sequences between distant relatives have conserved sequence segments [25], which has certain reference significance for identifying miRNA functions. In recent years, functional research on miRNAs has emerged as a focal point in model plants. However, the functional characterization of miRNAs in fruit trees is very limited due to complex chromosome ploidy and long growth cycles; therefore, it is a good starting point to analyze the evolution and function of miRNAs from a phylogenetic perspective [26]. Based on a homology-based search, it can be confirmed that the identified miRNA has a phylogenetic relationship with the known miRNA function in other species. miRNAs target different mRNAs due to variations in their sequences [27]. Consistent with previous findings, phylogenetic and conservation analysis indicated that the miRNAs we identified are conserved across species [28]. In our study, a homology-based search was performed to determine the phylogenetic relationship of the identified dk-miRNAs to miRNAs from other species. It was verified that the dk-miR156 is conserved in C. sinensis, Citrus trifoliate, V. vinifera, and M. domestica; dk-miR395 is conserved in V. vinifera and M. truncatula; and dk-miR396 is conserved in C. sinensis, M. esculenta, P. trichocarpa, and M. domestica.
PAs are phenolic polymers resulting from the polymerization of flavan-3-ol units, which accumulate in the vacuoles of specific cells during fruit development [6]. Their strong antioxidant capacity is very beneficial to human health. They can effectively prevent cancer and cardiovascular diseases and also play an important role in alleviating hypercholesterolemia, anti-oxidation, and scavenging free radicals [29,30]. In this study, a total of 39 candidate genes that may be involved in the regulation of PA metabolism were predicted to be targeted by the four miRNA family members. In addition to the predicted target genes directly involved in tannin biosynthesis, some important structure genes and transcript factors related to secondary metabolite biosynthesis, transport, and catabolism were also identified as target genes for miR-156, miR-395, miR-396, and miR-2911. Interestingly, miR396 was predicted to target eight genes that contain the D. kaki pyruvate decarboxylase 2 (PDC2) mRNA and F-box/WD-40 repeat-containing protein, which suggests that miR396 might be a key miRNA involved in PA metabolism. Many varieties of miR396 have been shown to be involved in plant growth and development. In rice, the main function of OsmiR396 is to regulate floral organ differentiation and rice panicle formation [31,32], and it also targets the OsGRF8 transcript factors that regulate the expression of OsF3H genes directly involved in flavonoid biosynthesis [33]. In Arabidopsis, miR396a repressed the expression of bHLH74 to regulate the growth of seedling roots [34]. However, the regulation mechanism of miR396 in PA biosynthesis still needs further verification. In plants, miR156 has been classified as a member of the miRNA family due to its high sequence similarity and conserved target genes, SPLs [35]. In Arabidopsis and Cirtus, miR156 has been shown to cleave SPL transcription factors [36,37]. In addition, Arabidopsis miR156 was shown to target SPL9, which could directly inhibit the expression of anthocyanin biosynthetic genes by interfering with the stability of the MYB-bHLH-WD40 transcriptional activation complex that negatively regulates the biosynthesis of anthocyanin [38]. Similarly, we assumed that miR156 might regulate PAs in persimmon. Moreover, it has been reported that the transcript factors DkWRKY3 and DkWRKY15 promoted the conversion of soluble PAs to insoluble PAs, as in the natural deastringency process, by regulating the expression of the DkPK1 gene [39]. Here, we suggest that DkWRKY and DkMYB22 were targeted by miR2911 and may be involved in PA metabolism. Interestingly, we demonstrated that the transcription factor DkMYB22 is a positive regulator that promotes the conversion of soluble PAs into insoluble PAs.
To clarify the role of transcriptional regulation by miRNAs in regulating PA metabolism, it is necessary to conduct in-depth research on miRNA gene promoters. To date, promoters of almost all miRNA genes found in different plant species have been detected through bioinformatics analyses, such as O. sativa [40], populus species [41], flax (Linum usitatissimum) [42], soybean (Glycine max) [43], Arabidopsis [44,45], and sorghum bicolor [40]. miRNA analysis revealed some genetic bases of astringency development (PA synthesis and removal) in persimmon via precipitation. D. oleifera is one of the original species of cultivated persimmon, and its miRNA data are a valuable basis for the genetic improvement of persimmon fruit, which helps improve the deastringency regulatory network of persimmon fruit and accelerate persimmon breeding.

5. Conclusions

Our study identifies tannin metabolism-related genes based on the miRNA genomic sequence information of D. oleifera. After miRNA mature sequence alignment analysis and precursor sequence secondary structure prediction analysis, we identified 22 miRNA precursors in the D. oleifera genome, which belong to four families. Of the miRNAs, miR396 repressed the expression of WD40, which works in synergy to regulate the structural genes responsible for PA biosynthesis. However, towards fruit ripening, miR156/SPL regulates the stabilization of the MYB-bHLH-WD40 complex, leading to decreased PA production. In the process of tannin solidification, miR2911 regulates the WRKY transcription factors, which interact with PK to promote the conversion of soluble PAs to insoluble PAs. Interestingly, another target gene of miR2911, DkMYB22, was verified to be involved in the deastringency of persimmon by promoting the coagulation of soluble tannins.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/horticulturae11010041/s1, Figure S1. Precursor sequence alignment of miR156 (A), miR395 (B), miR396 (C), and miR2911 (D) in D. oleifera with ‘Eshi 1’; Figure S2. Multiple sequence alignment of miR156 (A), miR395 (B), miR396 (C), and miR2911 (D) in D. oleifera with M. domestica, C. sinensis, V. vinifera, A. thaliana, M. truncatula, S. lycopersicum, M. esculenta, etc.; Figure S3. The genomic location of D. oleifera miRNA involved in tannin biosynthesis. Table S1. The primers used in this study.

Author Contributions

Investigation, formal analysis, writing—original draft, and methodology, M.Z.; formal analysis, writing—review and editing, and validation, S.Y.; validation, R.W.; conceptualization and resources, Z.L. and X.H.; formal analysis, supervision, and writing—review and editing, Q.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Jiangxi Academy of Agricultural Sciences Basic Research and Talent Training Project, grant number JXSNKYJCRC202327; the Natural Science Foundation of China, grant number 32460736; and the Natural Science Foundation of Jiangxi Province, grant number 20242BAB20293.

Data Availability Statement

The original contributions presented in this study are included in the article and supplementary material. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Images of D. oleifera. (A) Mature tree. (B) The fruit developing on the tree. (C) Mature fruits.
Figure 1. Images of D. oleifera. (A) Mature tree. (B) The fruit developing on the tree. (C) Mature fruits.
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Figure 2. Secondary structures of the miRNA precursors involved in the tannin mechanism in D. oleifera.
Figure 2. Secondary structures of the miRNA precursors involved in the tannin mechanism in D. oleifera.
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Figure 3. Conservation analysis of the MIR genes and mature miRNAs. (A) The conservation analysis of MIR156, MIR395, MIR396, MIR2911 in D. oleifera with the ‘Eshi 1’ database sequence. (B) The conservation analysis of the miR156, miR395, miR396, and miR2911 in D. oleifera only.
Figure 3. Conservation analysis of the MIR genes and mature miRNAs. (A) The conservation analysis of MIR156, MIR395, MIR396, MIR2911 in D. oleifera with the ‘Eshi 1’ database sequence. (B) The conservation analysis of the miR156, miR395, miR396, and miR2911 in D. oleifera only.
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Figure 4. Phylogenetic analysis of miR156 (A), miR395 (B), and miR396 (C) of D. oleifera and M. domestica, C. sinensis, V. vinifera, A. thaliana, M. truncatula, S. lycopersicum, M. esculenta, etc. The red dots represent miRNAs associated with tannin metabolism identified from the D. oleifera genome.
Figure 4. Phylogenetic analysis of miR156 (A), miR395 (B), and miR396 (C) of D. oleifera and M. domestica, C. sinensis, V. vinifera, A. thaliana, M. truncatula, S. lycopersicum, M. esculenta, etc. The red dots represent miRNAs associated with tannin metabolism identified from the D. oleifera genome.
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Figure 5. Prediction of cis-acting elements in the miRNA promoters in D. oleifera. We selected sequence approximately 2 kb upstream of the 12 MIR genes and used the TSSs to predict promoter cis-acting elements in the D. oleifera genomic data. The ordinate is the quantity, and the abscissa is the name of the miRNA.
Figure 5. Prediction of cis-acting elements in the miRNA promoters in D. oleifera. We selected sequence approximately 2 kb upstream of the 12 MIR genes and used the TSSs to predict promoter cis-acting elements in the D. oleifera genomic data. The ordinate is the quantity, and the abscissa is the name of the miRNA.
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Figure 6. Expression level of MIR156a (A), MIR396b (B), MIR396e (C), and MIR2911b (D) in C-PCNA ‘Eshi 1’ during fruit development.
Figure 6. Expression level of MIR156a (A), MIR396b (B), MIR396e (C), and MIR2911b (D) in C-PCNA ‘Eshi 1’ during fruit development.
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Figure 7. QRT-PCR analysis of the target genes of miR156 (ADH3, bHLH48, and SPL9), miR396 (WD40 and bHLH90) and miR2911 (WRKY6) in C-PCNA ‘Eshi 1’ fruit during development. The expression patterns of (A) ADH3, (B) bHLH48, (C) SPL9, (D) WD40, (E) bHLH90, and (F) WRKY6.
Figure 7. QRT-PCR analysis of the target genes of miR156 (ADH3, bHLH48, and SPL9), miR396 (WD40 and bHLH90) and miR2911 (WRKY6) in C-PCNA ‘Eshi 1’ fruit during development. The expression patterns of (A) ADH3, (B) bHLH48, (C) SPL9, (D) WD40, (E) bHLH90, and (F) WRKY6.
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Figure 8. Analysis of the tannin content change pattern and DkMYB22 expression pattern during the fruit development in ‘Ganfang 1’. (A) The soluble tannin content change during fruit development in ‘Ganfang 1’. (B) The insoluble tannin content change during fruit development in ‘Ganfang 1’. (C) The change in expression level of DkMYB22 during fruit development in ‘Ganfang 1’.
Figure 8. Analysis of the tannin content change pattern and DkMYB22 expression pattern during the fruit development in ‘Ganfang 1’. (A) The soluble tannin content change during fruit development in ‘Ganfang 1’. (B) The insoluble tannin content change during fruit development in ‘Ganfang 1’. (C) The change in expression level of DkMYB22 during fruit development in ‘Ganfang 1’.
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Figure 9. The subcellular localization of DkMYB22 in tobacco epidermal cells.
Figure 9. The subcellular localization of DkMYB22 in tobacco epidermal cells.
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Figure 10. Function analysis of the target gene DkMYB22 of miR2911. (A). QRT-PCR analysis of the expression levels of DkMYB22 in the leaves 10 days after transient over-expression and silencing of DkMYB22. (B). Determination of soluble tannin content in the leaves 10 days after the transient over-expression and silence-expression of DkMYB22. (C). Determination of insoluble tannin content in the leaves 10 days after over-expression and silence-expression of DkMYB22. CK represents the blank control that transiently expressed the empty vector. The data correspond to the means ± SD of three biological replicates relative to an ACTIN housekeeping control and normalized against the control value. Statistical significance was assessed using one-way analysis of variance (ANOVA) followed by Duncan’s multiple range test (** p < 0.01).
Figure 10. Function analysis of the target gene DkMYB22 of miR2911. (A). QRT-PCR analysis of the expression levels of DkMYB22 in the leaves 10 days after transient over-expression and silencing of DkMYB22. (B). Determination of soluble tannin content in the leaves 10 days after the transient over-expression and silence-expression of DkMYB22. (C). Determination of insoluble tannin content in the leaves 10 days after over-expression and silence-expression of DkMYB22. CK represents the blank control that transiently expressed the empty vector. The data correspond to the means ± SD of three biological replicates relative to an ACTIN housekeeping control and normalized against the control value. Statistical significance was assessed using one-way analysis of variance (ANOVA) followed by Duncan’s multiple range test (** p < 0.01).
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Table 1. Description of the target transcripts of the miRNAs.
Table 1. Description of the target transcripts of the miRNAs.
miRNAsTarget TranscriptsDescription
miR156EVM0020578.2Squamosa promoter-binding-like protein 18
EVM0013648.1
EVM0005209.1Transcription factor MYB4
EVM0014735.1Alcohol dehydrogenase 3
EVM0025134.1
EVM0016011.1
EVM0008150.1
EVM0009573.1
EVM0031798.1F-box-like/WD repeat-containing protein
EVM0024972.1Squamosa promoter-binding-like protein 13A
EVM0006611.3Squamosa promoter-binding-like protein 16
EVM0031300.1Squamosa promoter-binding-like protein 9
EVM0022316.1
EVM0012089.2Squamosa promoter-binding-like protein 2
EVM0031388.1
EVM0021122.1Squamosa promoter-binding-like protein 6
EVM0016005.3
EVM0014405.1Squamosa promoter-binding-like protein 7
EVM0025944.2Basic helix-loop-helix DNA-binding superfamily protein isoform 1
EVM0012958.1Transcription factor bHLH48
miR395EVM0006832.1Transcription factor bHLH147
miR396EVM0004765.1Transcription factor bHLH90
EVM0013146.1WD repeat-containing protein 74
EVM0022732.1Diospyros kaki pyruvate decarboxylase 2 (PDC2) mRNA
EVM0031521.1Laccase-11-like
EVM0031715.1Diospyros kaki ethylene response factor 3 (ERF3) mRNA
EVM0011729.1WD repeat-containing protein 75
EVM0021485.1F-box/WD-40 repeat-containing protein
EVM0019662.1Transmembrane 9 superfamily member 1
miR2911EVM0018100.1Ethylene-responsive transcription factor TINY-like
EVM0030558.1Ethylene-responsive transcription factor CRF2
EVM0005439.1Transcription factor MYB22
EVM0014721.1WD repeat-containing protein 44-like
EVM0019487.1Probable WRKY transcription factor 72
EVM0030913.1WRKY transcription factor 6 partial mRNA
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Zhang, M.; Wu, R.; Hu, X.; Luo, Z.; Zhang, Q.; Yang, S. Genome-Wide Identification of miRNAs in Oily Persimmon (Diospyros oleifera Cheng) and Their Functional Targets Associated with Proanthocyanidin Metabolism. Horticulturae 2025, 11, 41. https://doi.org/10.3390/horticulturae11010041

AMA Style

Zhang M, Wu R, Hu X, Luo Z, Zhang Q, Yang S. Genome-Wide Identification of miRNAs in Oily Persimmon (Diospyros oleifera Cheng) and Their Functional Targets Associated with Proanthocyanidin Metabolism. Horticulturae. 2025; 11(1):41. https://doi.org/10.3390/horticulturae11010041

Chicago/Turabian Style

Zhang, Meng, Rong Wu, Xinlong Hu, Zhengrong Luo, Qinglin Zhang, and Sichao Yang. 2025. "Genome-Wide Identification of miRNAs in Oily Persimmon (Diospyros oleifera Cheng) and Their Functional Targets Associated with Proanthocyanidin Metabolism" Horticulturae 11, no. 1: 41. https://doi.org/10.3390/horticulturae11010041

APA Style

Zhang, M., Wu, R., Hu, X., Luo, Z., Zhang, Q., & Yang, S. (2025). Genome-Wide Identification of miRNAs in Oily Persimmon (Diospyros oleifera Cheng) and Their Functional Targets Associated with Proanthocyanidin Metabolism. Horticulturae, 11(1), 41. https://doi.org/10.3390/horticulturae11010041

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