Next Article in Journal
Comet Assay: Multifaceted Options for Studies of Plant Stress Response
Next Article in Special Issue
Boosting Tomato Resilience in Tanzania: Grafting to Combat Bacterial Wilt and Abiotic Stress
Previous Article in Journal
Improving the Nutrient Management of an Apple Orchard by Using Organic-Based Composites Derived from Agricultural Waste
Previous Article in Special Issue
Mediator Subunit RhMED15a Regulates Drought Tolerance in Rose
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Horticulturae
Volume 10
Issue 2
10.3390/horticulturae10020173
horticulturae-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Joint Analysis of Small RNA and mRNA Sequencing Unveils miRNA-Mediated Regulatory Network in Response to Methyl Jasmonate in Apocynum venetum L.

by
Jinhua Tan
1,†,
Xiaowei Han
2,3,†,
Qi Liu
1,
Tashi Dorjee
1,
Yijun Zhou
1,
Huigai Sun
2,3,* and
Fei Gao
1,*
1
College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
2
School of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China
3
Traditional Chinese Medicine Processing Technology Inheritance Base of the State Administration of Traditional Chinese Medicine (Hebei), Shijiazhuang 050200, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Horticulturae 2024, 10(2), 173; https://doi.org/10.3390/horticulturae10020173
Submission received: 9 January 2024 / Revised: 6 February 2024 / Accepted: 9 February 2024 / Published: 15 February 2024
(This article belongs to the Special Issue Studies on Biotic and Abiotic Stress Responses of Horticultural Plants)
Browse Figures
Versions Notes

Abstract

:
Apocynum venetum L. is a natural fiber and medicinal plant species with significant economic value. Jasmonic acid is an endogenous growth regulatory substance present in higher plants that participate in plant growth, development, and defense. As important endogenous single-stranded RNA molecules, microRNA (miRNA) plays an important role in the post-transcriptional regulation of plant genes. A combination of miRNA and mRNA sequencing techniques was used to systematically identify the methyl jasmonate miRNAs and mRNAs in A. venetum. Up to 135 conserved and 26 species-specific miRNAs have been identified in A. venetum. These miRNAs mainly target genes that encode transcription factors and enzymes. The expression levels of 23 miRNAs, including miR398 and miR482, significantly changed after MeJA treatment. A total of 1778 genes were differentially expressed under MeJA treatment, of which 825 were upregulated and 953 were downregulated. The main biological processes enriched in these differentially expressed genes were redox balance, secondary metabolism, photosynthesis, and plant hormone signal transduction. Joint analysis of the miRNAs and mRNA revealed that MeJA-responsive miRNAs function by forming regulatory modules, including miR398-CSD, miR482-NBS-LRR, miR156-SPL10, and miR164-NAC056, which further regulate multiple biological processes, including redox balance, disease resistance, and morphogenesis in A. venetum. This study provides important information to understand the biological roles of miRNAs in A. venetum.

1. Introduction

Apocynum venetum L., also known as LUOBUMA in China, is a perennial subshrub of the Apocynaceae family [1]. This plant is widely distributed in Xinjiang, Inner Mongolia, Gansu, Qinghai, and other regions of China, and there is large-scale artificial cultivation of A. venetum in Qinghai, Heilongjiang, and Xinjiang. A. venetum is a medicinal plant with multiple therapeutic and healthcare functions [2]. Research has shown that A. venetum has good pharmacological effects by lowering blood pressure, blood lipids, and acting as an antidepressant. The main active pharmaceutical ingredients of A. venetum include flavonoids, such as quercetin, hyperoside, and isoquercetin. A. venetum is a hemp crop. The fibers prepared from the stem skin of A. venetum are slender and soft and are often used to make underwear and other textiles. A. venetum can tolerate saline–alkali stress and often grows on desert edges and coastal areas; thus, it has important ecological value [3]. In addition, A. venetum blooms beautifully and can be used as an ornamental plant. At present, the research of A. venetum mainly focuses on the analysis of chemical composition and their pharmacological action, and there are few studies on hormone response in A. venetum.
Jasmonates (JAs) include jasmonic acid (JA), methyl jasmonate (MeJA), derivatives of volatile MeJA, and derivatives of JA amino acids, which are plant signaling molecules in the oxylipin family [4]. MeJA is a methylated form of JA. After entering plant cells through the stomata, MeJA undergoes a series of chemical reactions to form JA, which together participate in the induction of plant defense reactions. JA mediates tolerance to drought, salt, heat, and cold stress, as well as resistance to pathogens and insects, and induces embryogenesis, flowering, and senescence [5]. It also involves tripartite interactions between insect vectors, viruses, and plants [6]. Research has found that exogenous application of MeJA increased the antioxidant enzyme activity of banana, thereby increasing their resistance to Fusarium oxysporum [7]. Exogenous JA application can increase the ability of Alyssum inflatum to resist heavy metal stress by reducing H2O2 concentration and increasing photosynthetic pigments [8]. MeJA can enhance the ability of Malus crabapple to resist O3 stress by increasing photosynthetic rate and antioxidant activity, and reducing lipid peroxidation [9]. However, little is known about the effects of MeJA on various biological processes and metabolic pathways in A. venetum.
Analyzing the JA response in A. venetum at the gene expression level helps understand the effects of JA on various biological processes and metabolic pathways in plants. In addition to classical transcriptome sequencing, analyzing the role of JA in miRNA regulation can provide a deeper understanding of JA-related transcriptional regulatory networks in plants. With an approximate length of 18 to 24 nt, microRNAs (miRNAs) are a class of endogenous single-stranded non-coding small RNAs that negatively regulate protein-coding genes at the posttranscriptional level. MiRNAs interact with their target mRNAs in two ways: cleavage induced degradation and translation inhibition. In plants, miRNA-targeted mRNAs are primarily cleaved and degraded by precise cleavage at the 10th or 11th base [10,11]. MiRNAs play key roles in regulating plant growth, development, and responses to environmental cues [12,13]. Emerging evidence has highlighted the responsiveness of miRNAs to various environmental stressors such as high salinity, drought, and low temperatures. Several studies have demonstrated that some miRNAs, such as miR156, miR166, miR398, miR482, and miR858, are involved in abiotic stress responses by targeting transcription factors and other functional genes, including SQUAMOSA Promoter-Binding Protein-Like (SPL) [14], HD-zip [15], Cu/Zn-superoxide dismutase (SOD; CSD) [16], NBS-LRR [17], and R2R3-MYB transcription factor [18].These miRNAs are believed to play crucial roles in the regulation of plant hormones, signal transduction, plant–pathogen interactions, and metabolic pathways. Plants contain both conserved and species-specific miRNAs. The systematic identification of all miRNAs in a specific species is of great value for understanding their biological characteristics and regulation. Many plant species have undergone systematic identification of miRNAs, including cabbage [19], jojoba [20], Chinese olive [21], tea plant [22], and ginkgo [23], but there have been no reports on miRNAs in A. venetum.
The present study employed high-throughput nucleic acid sequencing technology and bioinformatics methods to systematically identify conserved and species-specific miRNAs in A. venetum, as well as their corresponding target genes. Transcriptome sequencing was conducted to determine the gene profiling in leaves of A. venetum under MeJA treatment. Based on the joint analysis of the alterations in the expression levels of both miRNAs and mRNA, a regulatory network of the MeJA response mediated by miRNAs was constructed. This study advances our understanding of the molecular mechanisms associated with the MeJA response in A. venetum and the biological role of miRNAs in plants.

2. Materials and Methods

2.1. Plant Materials and Stress Treatments

Seeds of A. venetum were collected from Korla (E 85°88′, N 41°4′) in the Xinjiang Uygur Autonomous Region of China. A. venetum seeds were first washed with ultrapure water, sterilized with 75% ethanol for 30 s, washed several times with ultrapure water to remove residual ethanol, sterilized with 5% sodium hypochlorite (NaClO) for 5 min, washed three times with sterile water, and dried with filter paper to remove surface moisture. The sterilized seeds were immersed in ultrapure water at a temperature of 4 °C for 24 h. The seeds were germinated in 10 L pots, which consisted of a combination of nutrient soil and vermiculite in a 1:1 ratio.
The seedlings were grown at 25/20 °C (d/n) under a photosynthetic photon flux density of 150 µmol m−2 s−1 with long-day conditions (16/8 h light/dark cycle). Five months after gemination, seedlings that exhibited comparable heights were randomly allocated in four groups. The first group comprised seedlings that were unstressed and was denoted as CK. In the second group, 1 mM of MeJA (Sigma-Aldrich, Madrid, Spain) was topically applied to the foliage for 72 h (MeJA group). In the third group, the leaves were sprayed with 50 mM methyl viologen (MV) for 24 h (MV group). In the fourth group, leaves were sprayed with 1 mM MeJA for 72 h. Subsequently, a spray treatment with 50 mM MV was administered for 24 h (MeJA+MV group). The MeJA solution used in our experiment was prepared by dissolving it with 95% ethanol, and a total of 5 mL of MeJA solution was used for each seedling. Leaf samples of the three biological replicates were collected and rapidly cryopreserved in liquid nitrogen until RNA extraction.

2.2. Physiological and Biochemical Analysis

Relative electrolyte leakage (REL) was measured using the method described by Yasar and Yang, respectively [24,25]. Malondialdehyde (MDA) content and the activity of SOD in A. venetum leaves were detected using the MDA detection kit and SOD kit, respectively. These kits were manufactured by Jiancheng Bioengineering Ltd. (Nanjing, China). The accumulation of H2O2 and O2− in the leaves of A. venetum was analyzed using 3,3′-diaminobenzidine (DAB)-staining and nitro blue tetrazolium (NBT)-staining according to previously described methods [26]. For each sample, the leaves from the three A. venetum seedlings were taken for histochemical staining, and leaves from the MV and MeJA+MV groups were chosen at random for imaging.

2.3. Chromosomal Positioning of miRNA Precursor

Chromosomal mapping was conducted to identify and locate conserved and species-specific miRNA precursor sequences in the chromosomes of A. venetum. To accomplish this, the online platform MapGene2Chrom (http://mg2c.iask.in/mg2c_v2.1/, accessed on 2 August 2023) [27] was utilized.

2.4. Transcriptome Sequencing and Data Analysis

The total RNA of A. venetum leaves was extracted by the TRIzol method. RNA integrity was assessed using electrophoresis (Bio-Rad Laboratories, Hercules, CA, USA). The RNA samples were sent to Baimaike Gene Technology Co., Ltd. (http://www.biomarker.com.cn/archives/24629, accessed on 2 July 2023). (Hangzhou) for library (350 bp) construction, and the libraries were sequenced using the Illumina HiseqTM4000 platform.
Initially, clean reads were obtained using Cutadapt 4.7 software, which effectively eliminated adaptor and ow-quality reads from the dataset [28]. Furthermore, sequencing reads were aligned to the A. venetum genome (unpublished data) using Hisat2 2.2.1 software [29]. StringTie 1.3.6 software was used to assemble the reads [30]. Third, genes were annotated using Trinotate v4.0.0 software, which was compared with Non-Redundant Protein Sequences in NCBI (NR) [31], Nucleotide Collection (NT), Universal Protein (Uniprot) [32], Kyoto encyclopedia of genes and genomics database (KEGG) [33], Clusters of orthogonal groups of proteins (COG) [34], and Gene ontology (GO) [35] databases to obtain the functional annotation information of genes in A. venetum. The differentially expressed genes (DEGs) were identified using DESeq2 3.11 software [36], with a screening threshold of |log2Ratio| ≥ 1 and q value ≤ 0.05. GO and KEGG pathway enrichment analyses of DEGs in A. venetum was carried out by R 3.6.3 software.

2.5. Utilization of Small RNA Sequencing Techniques Coupled with Comprehensive Data Analysis

Small RNA libraries were prepared using a TruSeq Small RNA sample Preparation Kit (Illumina, San Diego, CA, USA) in accordance with established procedures. Subsequently, the six libraries were sequenced by single-end sequencing on the Illumina HiSeq 2500 platform (Baimaike Gene Technology [Hangzhou] Co., Ltd., Hangzhou, China).
Adaptor and low-quality sequences were removed using Trimmomatic v0.35, as described by Bolger [37]. The miRNA sequences and their corresponding precursors were identified usingMiRDeep2 and miRPlant software, as described by Friedlander [38,39]. Sequence fragments with mismatched bases < 4 and no base insertions or deletions were considered known miRNAs and were called conserved miRNAs. Unmatched sequences that were in line with the identification standard of “high reliability miRNA”, were considered species-specific miRNA [40].
The differentially expressed miRNA (DEMs) in A. venetum were determined by employing DESeq2 software, and the criteria were set as |log2Ratio| ≥ 1 and q-value ≤ 0.05. The target genes of all miRNAs in A. venetum were predicted using psRNAtarget software (http://plantgrn.noble.org/psRNATarget/, accessed on 2 December 2023) with default parameters.

2.6. qRT-PCR Analysis of miRNAs and Their Targeting mRNAs

cDNA was obtained by reverse transcription of the extracted A venetum RNA, using the miRcute miRNA plus cDNA first-strand synthesis kit and the FastKing gDNA Displacing RT Supermix kit from TIANGEN. The cDNA reaction solution that was acquired underwent 100-fold dilution and was subsequently used as a template for qRT-PCR.
Forward, reverse, and universal reverse primers for miRNAs (Supplementary Table S1) were designed using Primer 3.0 (https://primer3.ut.ee/, accessed on 2 August 2023). The expression levels of both the target mRNAs and miRNAs were analyzed by qRT-PCR, and the internal references used were eIF and 18s rRNA, respectively.
qRT-PCR amplification was performed on an Applied Biosystems QuantStudio 5 (Thermo Fisher Scientific, Waltham, MA, USA) using the miRcute plus miRNA fluorescence quantitative detection kit and the qPCR SuperMix kit (TIANGEN, China). The reaction system and qPCR procedures were set up according to the manufacturer’s instructions. Each reaction was repeated three times independently, and the relative expression of each miRNA or target gene was analyzed using the 2−ΔΔCt method [41].

2.7. Promoter Analysis of miRNAs in A. venetum

PLACE version 30.0 [42] software (https://www.dna.affrc.go.jp/PLACE/?action=newPlaceSite&site=S000453, accessed on 2 August 2023) was utilized to predict cis-acting elements situated approximately 1500 bp upstream of the precursor sequences of miRNAs.

2.8. Double-Luciferase Reporter Gene Test

The double-luciferase reporter assay test [43] was used to validate the targeting relationship between miRNAs and their predicted targets. The precursor sequence of miR398 was ligated to the pGreen II 62 SK vector, and the coding sequence of its target (CSD) was fused to the pGreen II 0800-LUC vector. The primers listed in Supplementary Table S1 were designed using Snapgene 3.2.1. The design process considered the precursor sequences of miR398, as well as the sequences of its target. Additionally, sequences of the pGreen II 62 SK and pGreen II 0800-LUC vectors were considered during the primer design process. After the protoplast of Arabidopsis thaliana was extracted [44], the luciferase signal was identified using the Bio-Lite TM luciferase system kit (Vazyme, Nanjing, China) 12 h later. Each luciferase signal was tested using five independent replicates.

3. Results

3.1. Identification and Characterization of Conserved and Species-Specific miRNAs in A. venetum

To identify the miRNAs within A. venetum and examine their responses to MeJA, we constructed six small RNA libraries, including three MeJA-treated groups and three control groups, followed by high-throughput sequencing. Each library yielded approximately 20.39 million raw reads. After eliminating adaptors, sequences of low quality, and sequences shorter than 18 nucleotides, every library yielded a range of 9.73 to 16.10 million clean reads. These clean reads had lengths varying from 19 to 24 nucleotides and high sequence quality (Supplementary Table S2).
A total of 135 conserved miRNAs were identified in A. venetum, belonging to 26 conserved miRNA families (Supplementary Table S3). The family with the highest number of miRNAs was miR166, which consisted of 25 members. The miR396 family had 13 members, the miR319 family had 12 members, and the miR171, miR167, and miR399 families had 10, 8, and 8 members, respectively. Five of the miRNA families contained only one miRNA member (Figure 1A).
All the miRNAs predicted by miRBase with more than four mismatches were classified as species-specific. The present investigation identified 26 miRNAs specific to A. venetum, utilizing a set of established criteria for discerning miRNA annotations with high and low confidence (Supplementary Table S4). Eight miRNAs were classified as high-confidence miRNAs, namely ave-miRN1, ave-miRN2, ave-miRN6, ave-miRN10, ave-miRN17, ave-miRN18, ave-miRN22, and ave-miRN23, which exhibited stable secondary structures (Figure 1B,C) and high expression levels.

3.2. Chromosomal Localization of Identified miRNAs in A. venetum

Chromosomal localization analysis of the miRNAs showed that the miRNA precursors were distributed on all 11 chromosomes (Figure 2). Many miRNAs are distributed on chromosomes 2, 8, and 3, with 23, 18, and 17 miRNA precursors, respectively. However, only one species-specific miRNA was found on chromosome 9, and no conserved miRNAs were found on this chromosome. Notably, several conserved miRNAs were clustered on the chromosomes, including miR156, miR157, miR159, miR160, miR162, miR164, miR166, miR167, miR169, miR171, miR172, miR390, miR391, miR395, miR398, miR399, miR403, miR477, and miR482. The three largest clusters comprised eight miR399, five miR395, and five miR167.

3.3. Prediction and Functional Analysis of Target Genes of miRNA in A. venetum

The miRNA target gene prediction software psRNAtarget was used to predict the target genes of both conserved and species-specific miRNAs in A. venetum. A total of 43,484 target genes, encompassing 15,938 unique genes, were identified. Among these, 11,450 genes were targeted by conserved miRNAs, while 5834 genes were targeted by species-specific miRNAs in A. venetum (Supplementary Tables S5 and S6).
To gain insights into the potential functions of the predicted target genes in A. venetum, GO enrichment analysis was conducted. GO enrichment analysis in conserved miRNA in A. venetum showed that the enriched biological process terms include ‘metabolic process’, ‘response to stimulus’, ‘growth’, and ‘nitrogen utilization’, and enriched GO molecular function terms include ‘transporter activity’, ‘transcription regulator activity’, ‘antioxidant activity’, and ‘molecular adaptor activity.’ The cellular component terms that exhibited the highest level of enrichment were predominantly associated with ‘cellular anatomical entity’ and ‘protein-containing complex’ (Figure 3A). GO enrichment analysis in species-specific miRNAs in A. venetum showed that the enriched biological process terms include ‘biological regulation’, ‘developmental process’, ‘pigmentation’, ‘carbon utilization’, and ‘sulfur utilization’, and enriched GO molecular function terms include ‘catalytic activity’, ‘antioxidant activity’, ‘transporter activity’, and ‘nutrient reservoir.’ The most enriched cellular component terms were the same as those used in the GO enrichment analysis of the conserved miRNAs (Figure 3C).
The metabolic pathways enriched in the miRNA target genes were identified using KEGG analysis. The enriched metabolic pathways in the conserved miRNAs were related to the MAPK signaling pathway, ABC transporters, biosynthesis of secondary metabolites, and plant–pathogen interactions (Figure 3B). The enriched metabolic pathways in species-specific miRNAs in A. venetum were associated with ABC transporters, flavonoid biosynthesis, phenylalanine, tyrosine, tryptophan biosynthesis, anthocyanin biosynthesis, and betalain biosynthesis (Figure 3D).

3.4. Identification of miRNAs Responding to MeJA Application in A. venetum

Twenty-three DEMs were identified in A. venetum by comparing the expression profiles of the miRNAs in the CK and MeJA groups (Figure 4A). Among them, 16 miRNAs were upregulated by MeJA treatment, including six conserved miRNAs and 10 species-specific miRNAs. Among the conserved miRNAs induced by MeJA, the upregulation of ave-miR171e-3p was the highest, since it was 3.18 times higher than that in the CK group. Among the species-specific miRNAs induced by MeJA, the upregulation of ave-miRN17-5p was the highest, since it was 3.55 times higher than that of the CK group (Figure 4B). In response to MeJA treatment, seven miRNAs in A. venetum were found to be downregulated. Among these, five miRNAs were conserved, while the remaining two were specific to A. venetum (Figure 4B).
Ten DEMs, including five conserved and five species-specific miRNAs, were randomly selected for qRT-PCR verification. The changes in miRNA expression under MeJA treatment, estimated based on small RNA sequencing data, were generally consistent with the results of qRT-PCR (Figure 4C), indicating that the results of the miRNA differential expression analysis in this study are reliable.

3.5. Promoter Analysis of MeJA-Responsive miRNAs

To understand the potential expression characteristics of the MeJA-responsive miRNAs in A. venetum, promoter analysis software was used to predict the presence and distribution of cis-acting elements in the promoter regions of these miRNAs. A large number of cis-acting elements are involved in the response to hormones and abiotic stress in the promoter regions of these miRNAs (Figure 5, Supplementary Table S7). Among them, ABRE is closely linked to the response of ABA, CGTCA and TGACG motifs play roles in the response to MeJA, GARE motif participates in GA response, MBS is related to drought response, LTR is associated with low-temperature response, and TC- rich repeats are involved in plant defense.
Not surprisingly, there are multiple copies of cis-acting elements involved in the MeJA response in the promoter regions of nearly half of the MeJA-responsive miRNAs. These miRNAs are both conserved and species-specific. In the promoter region of over 65% of miRNAs, cis-acting elements are involved in the ABA response, and the copy number of cis-acting elements carried by the promoter of the conserved miRNA is significantly higher than that of species-specific MeJA-responsive miRNAs.

3.6. Functional Analysis of Targets of MeJA-Responsive miRNAs in A. venetum

A total of 5664 gens (involving 5010 unique genes) were targeted by 23 MeJA-responsive miRNAs, including 2731 targets of conserved DEMs and 2405 targets of species-specific DEMs.
GO enrichment analysis can help researchers understand the functions and biological processes in which a group of genes is enriched. The possible functions of these target genes in response to MeJA in A. venetum were clarified using GO enrichment analysis. GO enrichment analysis, in the conserved DEMs, showed that the response to MeJA in A. venetum was associated with biological processes, including ‘metabolic process’, ‘response to stimulus’, ‘growth’, and ‘nitrogen utilization’, and enriched GO molecular function terms were ‘transporter activity’, ‘transcription regulator activity’, ‘antioxidant activity’, and ‘molecular adaptor activity’. Additionally, ‘cellular anatomical entity’, and ‘protein-containing complex’ were the two most enriched cellular component GO terms (Figure 6A). GO enrichment analysis in species-specific DEMs showed that the response to MeJA in A. venetum was associated with biological processes, including ‘biological regulation’, ‘developmental process’, ‘pigmentation’, ‘carbon utilization’, and ‘sulfur utilization’, and enriched GO molecular function terms were ‘catalytic activity’, ‘antioxidant activity’, ‘transporter activity’, and ‘nutrient reservoir’. The most enriched cellular component terms were the same as those used in the GO enrichment analysis of the conserved miRNAs (Figure 6C).
KEGG is helpful for studying genes and their expression information as a whole. It not only provides the metabolic pathways in which genes may participate, but also provides a comprehensive explanation of the catalytic reactions of enzymes produced by these genes. Metabolic pathways enriched in the target genes of the DEMs were investigated using KEGG annotation. KEGG enrichment analysis of conserved DEMs showed that the response to MeJA in A. venetum was related to ABC transporters, biosynthesis of secondary metabolites, oxidative phosphorylation, flavone and flavonol biosynthesis, and plant–pathogen interactions (Figure 6B). KEGG enrichment analysis of species-specific DEMs showed that the response to MeJA in A. venetum was related to anthocyanin biosynthesis, ribosome biogenesis in eukaryotes, phenylalanine, tyrosine and tryptophan biosynthesis, photosynthesis, and alanine, aspartate, and glutamate metabolism (Figure 6D).

3.7. Transcriptome Analysis of the Response to MeJA in A. venetum

To investigate changes in gene expression levels in response to MeJA in A. venetum leaves, six cDNA libraries were created and sequenced from A. venetum leaves cultivated under normal conditions and after MeJA application. In total, 37.08 Gb of sequencing data with a GC content of approximately 44% and a Q30 value of 93.04% were retrieved after low-quality sequences were removed (Supplementary Table S2). The expression levels of each mRNA under the CK and MeJA treatments were compared to identify the DEGs in A. venetum. In A. venetum, 1778 DEGs were identified, including 825 upregulated and 953 downregulated genes (Figure 7A,B).
To validate the gene expression calculated using the transcriptome data, ten DEGs were randomly chosen, and their expression levels were confirmed by qRT-PCR (Figure 7C). The expression patterns revealed by qRT-PCR analysis agreed with those observed by transcriptome sequencing, indicating the reliability of the transcriptome sequencing results.
For GO functional analysis, DEGs were segregated into 2862 GO categories. These categories encompassed 1881 classifications related to biological processes, 244 classifications associated with cellular components, and 737 classifications related to molecular functions. GO enrichment analysis in DEGs showed that the response to MeJA in A. venetum was associated with biological processes, including ‘metabolic process’, ’response to stimulus’, ’developmental process’, and ‘signaling’, and the enriched GO molecular function terms were ‘catalytic activity’, ‘transporter activity’, ‘antioxidant activity’, ‘signal transducer activity’, and ‘transcription regulator activity’. The most enriched cellular component terms were ‘cell’, ‘membrane’, ‘organelle’, and ‘extracellular region’ (Figure 7E). KEGG enrichment analysis of the DEGs revealed 31 significantly enriched pathways, including plant hormones, signal transduction, porphyrin, secondary metabolism, and photosynthesis (Figure 7D).

3.8. Joint Analysis of miRNA and mRNA Sequencing in A. venetum under MeJA Application

To identify the miRNA–mRNA interaction pairs in A. venetum leaves under MeJA treatment, a comprehensive analysis was conducted by integrating datasets from small RNA and transcriptome sequencing. Consequently, 2819 miRNA-target pairs were identified, including 12 MeJA-responsive conserved miRNAs and 1614 targets, as well as 11 MeJA-responsive species-specific miRNAs and 1205 targets in A. venetum (Supplementary Tables S8 and S9). These miRNA–mRNA interaction pairs regulate many biological processes involved in the response to MeJA in A. venetum, including reactive oxygen species (ROS), homeostasis (miR398-CSD), plant defense (miR482-TIR-NBS-LRR), plant growth and development (miR156-SPL10, miR399-PHO2), and signal transduction (miR164a-5p-NAC056) (Figure 8).

3.9. Dual-Luciferase Reporter Analysis Proving the Targeting Relation between miR398 and CSD2

miRNA target prediction indicated that CSD2 (TRINITY_DN9077_c0_g1_i2) was the target of ave-miR398a-3p. The double-luciferase reporter method is a dependable experimental approach for identifying and confirming the specific interactions between miRNAs and their targets. Compared with 62 SK+CSD2 cells, the ratio of luciferase/Renilla in Pre-miR398+CSD2 cells decreased significantly. These results indicated that miR398 negatively regulates CSD expression in Arabidopsis protoplasts. qRT-PCR analysis showed that the expression profiles of ave-miR398a-3p and CSD2 (TRINITY_DN9077_c0_g1_i2) exhibited contrasting alterations in A. venetum (Figure 7C), which also supported the targeting relation between miR398 and CSD (Figure 9C).

3.10. MeJA Treatment Improved Tolerance of A. venetum to Oxidative Stress

MV treatment can lead to oxidative stress in plant tissues. After 24 h of MV treatment, all A. venetum leaves in the MV group showed significant curling, whereas after treating the leaves of A. venetum with MeJA and then MV for 24 h, only a few leaves in the MeJA+MV group showed slight curling (Figure 10A).
MDA is a lipid peroxide decomposition substance produced by free radicals, which can hinder the normal metabolism of cells and even lead to death. REL indicates the degree of cell membrane damage, and the lower the value, the stronger the membrane stability. Therefore, REL and MDA content, which are frequently employed as established markers for assessing cellular membrane impairment, can reflect the degree of lipid peroxidation in plants. REL and MDA levels were measured 24 h after MV treatment. The results showed that both the MeJA group and CK group exhibited no significant change in REL and MDA levels. After MV treatment, REL and MDA values in both the MeJA+MV and MV groups increased significantly. However, compared with that in the MV group, the magnitude of the increase in REL and MDA values was significantly smaller in the MeJA+MV group (Figure 10B,C). Collectively, these results indicate that MeJA improved the tolerance of A. venetum to MV-induced oxidative stress.

3.11. Tolerance to Oxidative Stress Induced by MeJA Is Related to the Elevation of SOD Enzyme Activity

DAB and NBT staining are effective methods for detecting the accumulation of H2O2 and O2− in plants. To investigate the effect of MeJA on ROS levels in A. venetum leaves, DAB and NBT staining were performed on leaves from the MV and MeJA+MV groups. The staining of A. venetum leaves in the MeJA+MV group was lighter than that in the MV group, indicating that MeJA treatment inhibited the MV-induced increase in ROS levels caused by MV (Figure 11A).
MeJA may affect the activity of the SOD enzyme through miR398. Therefore, the SOD enzyme activities in the CK, MeJA, MV, and MeJA+MV groups were detected. SOD enzyme activity in A. venetum leaves significantly increased after MeJA treatment (MeJA vs. CK and MeJA+MV vs. MV) (Figure 11B).

4. Discussion

A. venetum is an economically, industrially, and ecologically useful crop. MeJA improves environmental stress tolerance in many plants. MiRNAs are a class of endogenous, single-stranded regulatory RNA molecules that may play important regulatory roles in the MeJA response in A. venetum. In this study, we conducted a large-scale MeJA-responsive miRNA analysis in A. venetum, which contributes to the adaptation of organisms to biological and abiotic stresses. By predicting and annotating miRNAs, we identified conserved and species-specific miRNAs in A. venetum. Through the association analysis of small RNA sequencing data and transcriptome sequencing data, high-confidence miRNA target genes were predicted, miRNA–mRNA interaction pairs involved in the MeJA response were obtained, and interaction networks between miRNAs and different target genes were constructed.
In this study, 135 conserved miRNAs belonging to 26 gene families were identified in A. venetum. Based on the degree of conservation, these miRNA families can be classified into five groups. Group 1 comprises ubiquitous miRNAs, including miR156, miR166, miR167, miR168, and miR172. Group 2 miRNAs are present in most taxonomic groups, including miR159, miR160, miR162, miR164, miR169, miR171, miR319, and miR390. Group 3 miRNAs were poorly enriched in monocots, including miR391, miR482, and miR2111. Group 4 miRNAs were enriched in dicots, including miR403. Group 5 miRNAs [45], including miR395, miR398, miR399, miR408, and miR827, were enriched in angiosperms.
A total of 26 species-specific miRNAs were identified in A. venetum, eight of which were identified as high-confidence species-specific miRNAs because they met the criteria for novel miRNA identification [46]. The abundances of the eight high-confidence species-specific miRNAs ranged from hundreds to tens of thousands. Among them, ave-miRN1 was the most abundant (71903 reads), and miRN9 was the least abundant (18 reads). The remaining 18 possible new miRNAs had stable hairpin structures, but their expression levels were insufficient for their identification as highly reliable species-specific miRNAs.
MeJA is a plant hormone that has the potential to combat infections, salt stress, drought stress, low temperatures, and heavy metal stress. The application of MeJA can promote plant growth, induce the accumulation of active substances, and affect physiological and biochemical characteristics, such as endogenous hormone levels. In this study, transcriptome sequencing revealed that 1778 DEGs were involved in the response of A. venetum leaves to MeJA. Enrichment analysis of these DEGs revealed that they were mainly involved in biological processes, including antioxidants, plant–pathogen interactions, and flavonoid biosynthesis.
There were 24 DEGs encoding different antioxidant families in A. venetum leaves (Supplementary Table S10). Many genes encode antioxidant enzymes, such as copper/zinc SOD, ascorbic acid oxidase, glutathione peroxidase (GSH-Px), and catalase (CAT). Seven of the eleven differentially expressed SOD genes, four of the five differentially expressed GSH-Px genes, and five of the eight differentially expressed CAT genes were upregulated by MeJA treatment. These results indicate that antioxidant enzyme genes play important roles in the response of A. venetum to MeJA, possibly protecting cells from oxidative damage caused by ROS by clearing ROS.
Plant–pathogen interactions also play an important role in the MeJA response of A. venetum. In this study, 131 DEGs were involved in plant–pathogen interactions, and 63% of these genes were upregulated (Supplementary Table S10). Several pathogenic genes involved in the MeJA response, such as PR1, RPS2, and CC-NBS-LRR, were upregulated.
It is worth noting that this study identified 16 DEGs encoding key enzymes in flavonoid biosynthesis, including ANS, DFR, CHS, C4H, HCT, FLS, CCoAOMT1, F3H, and F3′H. The differential expression of these genes may lead to changes in flavonoid biosynthesis, and changes in the concentrations of these flavonoid substances may further affect the tolerance of A. venetum to abiotic stress. A related study has indicated that MeJA stimulates changes in the concentration of flavonoids in pear callus tissue [47].
In the present study, a batch of DEMs belonging to the miR156, miR164, miR399, and miR482 families were found to respond to MeJA in A. venetum. These DEMs may regulate the biosynthesis and physiological metabolism of A. venetum in response to MeJA by forming a regulatory network with DEGs identified by transcriptome sequencing.
The functional diversity of the SPL family of transcription factors allows them to regulate several essential elements of plant growth and development, such as branching [48], leaf initiation rate, blooming time [49], and vegetative phase shift [50]. It has been proven that miR156 regulates these functions by inhibiting the expression of SPL in A. thaliana [51]. Six miRNA members of the ave-MIR156 family have been identified in A. venetum, the most abundant of which is ave-miR156f. In total, 179 genes were targeted by ave-miR156f, including the SPL transcription factor genes. Furthermore, ave-miR156f was significantly upregulated following MeJA treatment. A combined analysis of small RNA sequencing and RNA sequencing data revealed a negative correlation between the expression levels of ave-miR156f and some of its predicted targets, including TRINITY_DN807_c0_g2_i15-SPL10, TRINITY_DN807_c0_g2_i26-SPL2, TRINITY_DN6812_c0_g1_i2-SPL4, and TRINITY_DN6812_c0_g1_i2-SPL9. Studies have shown that MeJA application induces the expression of SPL4, SPL5, SPL7, and SPL15 in alfalfa [52]. Our results suggest that miR156 mediates the regulation of SPL transcription factors by MeJA in A. venetum.
PHO2, which encodes the ubiquitin-binding E2 enzyme 24, regulates the degradation of PHO1 in plant membranes to maintain Pi homeostasis [53]. miR399 affects organic phosphate (Pi) homeostasis by regulating PHO2 expression. The miR399-PHO2 module regulates Pi homeostasis in Brassica napus [54] and flowering time in response to varying ambient temperatures in Arabidopsis thaliana [55]. In this study, eight miRNA members of the ave-MIR399 family were identified. Ave-miR399g was the most abundant member of the miR399 family. Up to 154 genes were predicted as targets of ave-miR399g. One of the ave-miR399g targets, TRINITY_DN4408_c0_g1_i9, encodes PHO2. The expression level of ave-miR399g was downregulated after MeJA application, whereas the PHO2 expression level displayed opposite patterns, as revealed by RNA-seq. The opposite relation was validated using qRT-PCR. Studies proposed that JA affects the Pi activation response in B. napus [56]. Our study provides new evidence for understanding the relation between the MeJA signaling pathway and Pi homeostasis in A. venetum.
Studies have shown that miR164 targets the NAC family of transcription factors, which is highly conserved in a wide range of plant species and is involved in the growth of lateral roots in A. thaliana [57], negative regulation of drought tolerance in rice [58], and the ripening of kiwifruit [59]. In this study, four miRNA members of the ave-MIR164 family were identified using short RNA sequencing. Ave-miR164c was the most abundant member of the ave-MIR164 family. Up to 157 mRNAs were predicted to be ave-miR164c targets using the psRNA target. TRINITY_DN8710_c1_g1_i3, an anave-miR164c target, encodes a transcription factor belonging to the NAC family. The expression level of NAC showed opposite expression patterns in small RNA sequencing compared with the expression level of ave-miR164c. qRT-PCR was performed to validate the inverse expression relationship between TRINITY_DN8710_c1_g1_i3 and miR164c. A related study showed that MeJA treatment induces the expression of NAC2/3 in kiwifruit [60].
The high-throughput sequencing data from this study showed that, after MeJA treatment, the expression of miRNA482 was downregulated in A. venetum leaves, whereas the expression of some miRNA482-targeted TIR-NBS-LRR genes increased. Furthermore, qRT-PCR analysis confirmed the relationship between miRNA482 and its target genes in A. venetum. Diseases and pests are the main biological stresses affecting the growth of A. venetum [3], including anthrax caused by Gloeosporium apocyni [61], various pests and diseases, including leaf spot disease caused by Phyllostachys oleifera leaf spot mold [62,63], which seriously affect the cultivation of A. venetum. Plant TIR-NBS-LRR genes play important roles in plant defense [64]. Consistent with our findings, it has been reported that the TIR-NBS-LRR defense gene is involved in regulating biological stress by targeting miR482 in alfalfa [65], tomatoes [66], and cotton [67]. These data indicate that in A. venetum, MeJA treatment can regulate the disease resistance gene TIR-NBS-LRR through miR482, thereby affecting the defense of A. venetum against pests and diseases.
Under abiotic stress conditions, ROS accumulation in plant cells leads to severe oxidative damage, ultimately resulting in cell death. Increasing evidence has shown that plant defense and stress response pathways are significantly influenced by ROS [68]. Plants have developed effective antioxidant systems, including SOD, ascorbic acid peroxidase, CAT, GSH-Px, monodehydroascorbate reductase, dehydroascorbate reductase, glutathione reductase, glutathione S-transferase, and peroxiredoxin, which are distributed in different parts of plant cells to maintain redox homeostasis [69].
MV treatment causes significant oxidative stress in plants. In this study, MV treatment resulted in the curling of A. venetum leaves, with significantly increased levels of REL and MDA. However, the tolerance of A. venetum treated with MeJA to MV-induced oxidative stress caused by MV treatment was significantly enhanced (Figure 10). Compared with untreated A. venetum leaves, the increase in ROS levels in A. venetum leaves pretreated with MeJA was smaller (Figure 11A), indicating that MeJA treatment can inhibit the excessive accumulation of ROS caused by oxidative stress. The small RNA sequencing and RNA-seq data in this study indicated that MeJA treatment led to changes in the expression levels of some miRNAs and many genes, with the expression level of miR398 being downregulated and the target gene CSD2 being upregulated. These alterations were further validated using qRT-PCR and SOD enzyme activity analyses. Similar studies showed that miR398 participated in controlling abiotic stress by targeting CSD1/CSD2 in rice [70], grapevine [71], and tomatoes [72]. Therefore, we speculate that MeJA treatment could increase the expression of CSD2 and further enhance the activity of SOD through miR398 in A. venetum, thereby enhancing the tolerance of A. venetum plants to various environmental stresses.

5. Conclusions

A. venetum is an economically important plant, and jasmonic acid is a key plant growth regulator. Understanding the MeJA response of A. venetum is important. A total of 135 conserved miRNAs and 26 species-specific miRNAs were identified using small RNA sequencing. Transcriptome analysis showed that 1778 genes were differentially expressed under MeJA treatment, of which 825 were upregulated and 953 were downregulated. Transcriptome and qRT-PCR analyses revealed a broad negative regulatory relationship between MeJA-responsive miRNAs and most of their target genes. A total of 2819 miRNA-target pairs were identified through combined analyses of RNA-seq and small RNA, and it was found that they regulate a variety of biological processes, including ROS homeostasis (miR398-CSD2), plant defense (miR482-TIR-NBS-LRR), and plant growth and development (miR156-SPL10, miR164a-5p-NAC056/NAC2). These data contribute to our understanding of the regulatory network of gene expression in the MeJA response of plants and advance our understanding of the biological functions of plant miRNAs. In the next step of our research, we will further analyze the biological functions of these MeJA-responsive miRNAs using transgenic systems in A. thaliana or A. venetum.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae10020173/s1, Table S1: Primers used in this study; Table S2: Summary of transcriptome and small RNA sequencing data; Table S3: The conserved miRNAs identified in A. venetum; Table S4: The species-specific miRNAs identified in A. venetum; Table S5: The predicted targets of the conserved miRNA in A. venetum; Table S6: The predicted targets of the species-specific miRNA in A. venetum; Table S7: Predicted cis-acting elements in the promoters of MeJA-responsive miRNAs in A. venetum; Table S8: Targets of the MeJA-responsive conserved miRNA in A. venetum; Table S9: Targets of the MeJA-responsive species-specific miRNA in A. venetum; Table S10: DEGs involved in flavonoid synthesis, ROS scavenging, and plant–pathogen interactions in A. venetum.

Author Contributions

Conceptualization, Y.Z. and F.G.; formal analysis, J.T., X.H., Q.L., T.D., H.S. and F.G.; funding acquisition, X.H., Y.Z. and F.G.; investigation, J.T., Q.L. and H.S.; supervision, Y.Z.; writing—original draft, J.T., H.S. and F.G.; writing—review and editing, F.G. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Scientific and Technological Research Projects of Colleges and Universities of Hebei Province (grant number ZD2020111), S&T Program of Hebei (grant number 22326418D), Hebei Provincial Administration of Traditional Chinese Medicine (grant number 2023355 and 2023351), the National Natural Science Foundation of China (grant numbers 31670335 and 31770363), and the Industrial Innovation Team Program of Traditional Chinese Medicine of Modern Agricultural Industry Technology System of Hebei Province (grant number HBCT2018060205).

Data Availability Statement

The raw data of transcriptome and small RNA sequencing were deposited in the GenBank Short Read Archive (SRA) database under accession number PRJNA961898.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Xie, W.; Zhang, X.; Wang, T.; Hu, J. Botany, traditional uses, phytochemistry and pharmacology of Apocynum venetum L. (Luobuma): A review. J. Ethnopharmacol. 2012, 141, 1–8. [Google Scholar] [CrossRef]
  2. Lu, C.; Zhang, W.; Peng, X.; Gu, G.; Chen, M.; Tang, Z. Development of randomly amplified polymorphic DNA-Sequence characterized amplified region marker for identification of Apocynum venetum LINN. from A. pictum SCHRENK. Biol. Pharm. Bull. 2010, 33, 522–526. [Google Scholar] [CrossRef]
  3. Thevs, N.; Zerbe, S.; Kyosev, Y.; Rozi, A.; Tang, B.; Abdusalih, N.; Novitskij, Z. Apocynum venetum L. and Apocynum pictum Schrenk (Apocynaceae) as multi-functional and multi-service plant species in central asia: A review on biology, ecology, andutilization. J. Appl. Bot. Food Qual. 2012, 85, 159–167. Available online: https://hdl.handle.net/10863/178 (accessed on 2 December 2023).
  4. Yu, X.; Zhang, W.; Zhang, Y.; Zhang, X.; Lang, D.; Zhang, X. The roles of methyl jasmonate to stress in plants. Funct. Plant Biol. 2018, 46, 197–212. [Google Scholar] [CrossRef] [PubMed]
  5. Wasternack, C.; Feussner, I. The oxylipin pathways: Biochemistry and function. Annu. Rev. Plant Biol. 2018, 69, 363–386. [Google Scholar] [CrossRef] [PubMed]
  6. Zheng, X.; Chen, Y.; Zhao, L.; Chen, Y.; Zheng, L.; Zheng, K.; Zhang, J. Tripartite interactions between jasmonic/salicylic acid pathways, western flower thrips, and thrips-transmitted tomato zonate spot virus infection in Capsicuum annuum. Arthropod-Plant Interact. 2019, 13, 289–297. [Google Scholar] [CrossRef]
  7. Sun, D.; Lu, X.; Hu, Y.; Li, W.; Hong, K.; Mo, Y.; Xie, J. Methyl jasmonate induced defense responses increase resistance to Fusarium oxysporum f. sp. cubense race 4 in banana. Sci. Hortic. 2013, 164, 484–491. [Google Scholar] [CrossRef]
  8. Karimi, N.; Ghasempour, H.R. Salicylic acid and jasmonic acid restrains nickel toxicity by ameliorating antioxidant defense system in shoots of metallicolous and non-metallicolous Alyssum inflatum Náyr. Populations. Plant Physiol. Biochem. 2019, 135, 450–459. [Google Scholar] [CrossRef]
  9. Qiu, Y.; An, K.; Sun, J.; Chen, X.; Gong, X.; Ma, L.; Wang, Y. Investigating the effect of methyl jasmonate and melatonin on resistance of Malus crabapple ‘Hong Jiu’to ozone stress. Environ. Sci. Pollut. Res. 2019, 26, 27761–27768. [Google Scholar] [CrossRef]
  10. Kasschau, K.D.; Xie, Z.; Allen, E.; Llave, C.; Chapman, E.J.; Krizan, K.A.; Carrington, J.C. P1/HC-Pro. a viral suppressor of RNA silencing, interferes with Arabidopsis development and miRNA function. Dev. Cell 2002, 4, 205–217. [Google Scholar] [CrossRef]
  11. Llave, C.; Xie, Z.; Kasschau, K.D.; Carrington, J.C. Cleavage of scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science 2002, 297, 2053–2056. [Google Scholar] [CrossRef]
  12. Song, X.; Li, Y.; Cao, X.; Qi, Y. MicroRNAs and their regulatory roles in plant-environment interactions. Annu. Rev. Plant Biol. 2019, 70, 489–525. [Google Scholar] [CrossRef]
  13. Zhu, M.; Wang, X.; Zhou, Y.; Tan, J.; Zhou, Y.; Gao, F. Small RNA sequencing revealed that miR4415, a legume-specific miRNA, was involved in the cold acclimation of Ammopiptanthus nanus by targeting an L-ascorbate oxidase gene and regulating the redox state of apoplast. Front. Genet. 2022, 13, 870446. [Google Scholar] [CrossRef]
  14. Stief, A.; Altmann, S.; Hoffmann, K.; Pant, B.D.; Scheible, W.R.; Baurle, I. Arabidopsis mir156 regulates tolerance to recurring environmental stress through spl transcription factors. Plant Cell 2014, 26, 1792. [Google Scholar] [CrossRef]
  15. Williams, L. Regulation of Arabidopsis shoot apical meristem and lateral organ formation by microRNA miR166g and its AtHD-ZIP target genes. Development 2005, 132, 3657–3668. [Google Scholar] [CrossRef]
  16. Val-Torregrosa, B.; Bundó, M.; San Segundo, B. Crosstalk between nutrient signaling pathways and immune responses in rice. Agriculture 2021, 11, 747. [Google Scholar] [CrossRef]
  17. Liao, L.; Xie, B.; Guan, P.; Jiang, N.; Cui, J. New insight into the molecular mechanism of miR482/2118 during plant resistance to pathogens. Front. Plant. Sci. 2022, 13, 1026762. [Google Scholar] [CrossRef]
  18. Sumbur, B.; Gao, F.; Liu, Q.; Feng, D.; Bing, J.; Dorjee, T.; Zhou, Y. The Characterization of R2R3-MYB Genes in Ammopiptanthus nanus uncovers that the miR858-AnaMYB87 Module mediates the accumulation of anthocyanin under osmotic stress. Biomolecules 2023, 13, 1721. [Google Scholar] [CrossRef]
  19. Sajad, S.; Dai, Q.; Yang, J.; Song, J. Identification of miRNAs involved in male fertility and pollen development in Brassica oleracea var. capitata L. by High-Throughput Sequencing. Horticulturae 2023, 9, 515. [Google Scholar] [CrossRef]
  20. Zheng, L.; Wu, W.; Gao, Y.; Wu, Y.; Xu, Y.; Zhang, G.; Zhou, Y. Integrated transcriptome, small RNA and degradome analysis provide insights into the transcriptional regulatory networks underlying cold acclimation in jojoba. Sci. Hortic. 2022, 299, 111050. [Google Scholar] [CrossRef]
  21. Lai, R.; Guan, Q.; Shen, C.; Feng, X.; Zhang, Y.; Chen, Y.; Wu, R. Integrated sRNA-seq and RNA-seq analysis reveals the regulatory roles of miRNAs in the low-temperature responses of Canarium album. Horticulturae 2022, 8, 667. [Google Scholar] [CrossRef]
  22. Cao, D.; Li, J.; Ma, L.; Liu, Y.; Huang, J.; Jin, X. Genome-Wide identification of selenium-responsive microRNAs in tea Plant (Camellia sinensis LO Kuntze). Horticulturae 2023, 9, 1278. [Google Scholar] [CrossRef]
  23. Lu, J.; Mao, X.; Xu, Y.; Liu, S.; Wang, L. MicroRNA identification and integrated network analyses for age-dependent flavonoid biosynthesis in Ginkgo biloba. Forests 2023, 14, 1706. [Google Scholar] [CrossRef]
  24. Yang, G.; Rhodes, D.; Joly, R.J. Effects of high temperature on membrane stability and chlorophyll fluorescence in glycinebetaine-deficient and glycinebetaine-containing maize lines. Funct. Plant Biol. 1996, 23, 437–443. [Google Scholar] [CrossRef]
  25. Yasar, F.; Ellialtioglu, S.; Yildiz, K. Effect of salt stress on antioxidant defense systems, lipid peroxidation, and chlorophyll content in green bean. Russ. J. Plant Physiol. 2008, 55, 782–786. [Google Scholar] [CrossRef]
  26. Zhang, X.; Wang, L.; Meng, H.; Wen, H.; Fan, Y.; Zhao, J. Maize ABP9 enhances tolerance to multiple stresses in transgenic Arabidopsis by modulating ABA signaling and cellular levels of reactive oxygen species. Plant Mol. Biol. 2022, 75, 365–378. [Google Scholar] [CrossRef]
  27. Chao, J.; Kong, Y.; Wang, Q.; Sun, Y.; Gong, D.; Lv, J.; Liu, G. MapGene2Chrom, a tool to draw gene physical map based on Perl and SVG languages. Yi Chuan Hered. 2015, 37, 91–97. [Google Scholar] [CrossRef]
  28. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 2011, 17, 10–12. [Google Scholar] [CrossRef]
  29. Kim, D.; Langmead, B.; Salzberg, S.L. HISAT: A fast spliced aligner with low memory requirements. Nat. Methods 2015, 12, 357–360. [Google Scholar] [CrossRef]
  30. Pertea, M.; Pertea, G.M.; Antonescu, C.M.; Chang, T.C.; Mendell, J.T.; Salzberg, S.L. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015, 33, 290–295. [Google Scholar] [CrossRef]
  31. Hyatt, D.; Chen, G.L.; LoCascio, P.F.; Land, M.L.; Larimer, F.W.; Hauser, L.J. Integrated nr database in protein annotation system and its localization. Nat. Commun. 2010, 6, 1–8. [Google Scholar]
  32. Apweiler, R.; Bairoch, A.; Wu, C.H.; Barker, W.C.; Boeckmann, B.; Ferro, S.; Yeh, L.S.L. UniProt: The universal protein knowledgebase. Nucleic Acids Res. 2004, 32, D115–D119. [Google Scholar] [CrossRef]
  33. Kanehisa, M.; Araki, M.; Goto, S.; Hattori, M.; Hirakawa, M.; Itoh, M.; Yamanishi, Y. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2007, 36, D480–D484. [Google Scholar] [CrossRef]
  34. Tatusov, R.L.; Galperin, M.Y.; Natale, D.A.; Koonin, E.V. The COG database: A tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000, 28, 33–36. [Google Scholar] [CrossRef] [PubMed]
  35. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Sherlock, G. Gene ontology: Tool for the unification of biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef] [PubMed]
  36. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [PubMed]
  37. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [PubMed]
  38. Friedländer, M.R.; Mackowiak, S.D.; Li, N.; Chen, W.; Rajewsky, N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 2012, 40, 37–52. [Google Scholar] [CrossRef]
  39. An, J.; Lai, J.; Sajjanhar, A.; Lehman, M.L.; Nelson, C.C. miRPlant: An integrated tool for identification of plant miRNA from RNA sequencing data. BMC Bioinform. 2014, 15, 275. [Google Scholar] [CrossRef]
  40. Kozomara, A.; Griffiths-Jones, S. miRBase: Annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014, 42, D68–D73. [Google Scholar] [CrossRef]
  41. Li, W.; Zhao, F.A.; Fang, W.; Xie, D.; Hou, J.; Yang, X.; Lv, S. Identification of early salt stress responsive proteins in seedling roots of upland cotton (Gossypium hirsutum L.) employing iTRAQ-based proteomic technique. Front. Plant Sci. 2015, 6, 732. [Google Scholar] [CrossRef]
  42. Higo, K.; Ugawa, Y.; Iwamoto, M.; Higo, H. PLACE: A database of plant cis-acting regulatory DNA elements. Nucleic Acids Res. 1998, 26, 358–359. [Google Scholar] [CrossRef]
  43. Clément, T.; Salone, V.; Rederstorff, M. Dual luciferase gene reporter assays to study miRNA function. Methods Mol Biol. 2015, 1296, 187–198. [Google Scholar]
  44. Yoo, S.D.; Cho, Y.H.; Sheen, J. Arabidopsis mesophyll protoplasts: A versatile cell system for transient gene expression analysis. Nat. Protoc. 2007, 2, 1565–1572. [Google Scholar] [CrossRef]
  45. Chavez, M.R.A.; Rosas-Cárdenas, D.F.F.; De Paoli, E.; Accerbi, M.; Rymarquis, L.A.; Mahalingam, G.; De Folter, S. Sample sequencing of vascular plants demonstrates widespread conservation and divergence of microRNAs. Nat. Commun. 2014, 5, 3722. [Google Scholar] [CrossRef]
  46. Wang, X.; Zhang, J.; Li, F.; Gu, J.; He, T.; Zhang, X.; Li, Y. MicroRNA identification based on sequence and structure alignment. Bioinformatics 2005, 21, 3610–3614. [Google Scholar] [CrossRef] [PubMed]
  47. Premathilake, A.T.; Ni, J.; Shen, J.; Bai, S.; Teng, Y. Transcriptome analysis provides new insights into the transcriptional regulation of methyl jasmonate-induced flavonoid biosynthesis in pear calli. BMC Plant Biol. 2020, 20, 388. [Google Scholar] [CrossRef]
  48. Yant, L.; Mathieu, J.; Dinh, T.T.; Ott, F.; Lanz, C.; Wollmann, H.; Schmid, M. Orchestration of the floral transition and floral development in Arabidopsis by the bifunctional transcription factor APETALA2. Plant Cell 2010, 22, 2156–2170. [Google Scholar] [CrossRef] [PubMed]
  49. Yu, N.; Cai, W.J.; Wang, S.; Shan, C.M.; Wang, L.J.; Chen, X.Y. Temporal control of trichome distribution by microRNA156-targeted SPL genes in Arabidopsis thaliana. Plant Cell 2010, 22, 2322–2335. [Google Scholar] [CrossRef] [PubMed]
  50. Xing, S.; Salinas, M.; Höhmann, S.; Berndtgen, R.; Huijser, P. miR156-targeted and nontargeted SBP-box transcription factors act in concert to secure male fertility in Arabidopsis. Plant Cell 2010, 22, 3935–3950. [Google Scholar] [CrossRef]
  51. Wang, J.W.; Park, M.Y.; Wang, L.J.; Koo, Y.; Chen, X.Y.; Weigel, D.; Poethig, R.S. miRNA control of vegetative phase change in trees. PLoS Genet. 2011, 7, e1002012. [Google Scholar] [CrossRef] [PubMed]
  52. Wang, Y.; Ruan, Q.; Zhu, X.; Wang, B.; Wei, B.; Wei, X. Identification of Alfalfa SPL gene family and expression analysis under biotic and abiotic stresses. Sci. Rep. 2023, 13, 84. [Google Scholar] [CrossRef] [PubMed]
  53. Lin, S.I.; Chiang, S.F.; Lin, W.Y.; Chen, J.W.; Tseng, C.Y.; Chiou, W.T.J. Regulatory network of microrna399 and pho2 by systemic signaling. Plant Physiol. 2008, 147, 732–746. [Google Scholar] [CrossRef] [PubMed]
  54. Du, K.; Yang, Y.; Li, J.; Wang, M.; Jiang, J.; Wu, J.; Wang, Y. Functional Analysis of Bna-miR399c-PHO2 Regulatory Module Involved in Phosphorus Stress in Brassica napus. Life 2023, 13, 310. [Google Scholar] [CrossRef] [PubMed]
  55. Kim, W.; Ahn, H.J.; Chiou, T.J.; Ahn, J.H. The role of the miR399-PHO2 module in the regulation of flowering time in response to different ambient temperatures in Arabidopsis thaliana. Mol. Cells 2011, 32, 83–88. [Google Scholar] [CrossRef]
  56. Li, Y.; Yang, X.; Li, X.; Wang, C.; Ding, G.; Xu, F.; Shi, L. Jasmonic acid participating in the systemic regulation of phosphate starvation response in Brassica napus. Plant Soil 2023. [Google Scholar] [CrossRef]
  57. Guo, H.S.; Xie, Q.; Fei, J.F.; Chua, N.H. MicroRNA directs mRNA cleavage of the transcription factor NAC1 to downregulate auxin signals for Arabidopsis lateral root development. Plant Cell 2005, 17, 1376–1386. [Google Scholar] [CrossRef]
  58. Fang, Y.; Xie, K.; Xiong, L. Conserved miR164-targeted NAC genes negatively regulate drought resistance in rice. J. Exp. Bot. 2014, 65, 2119–2135. [Google Scholar] [CrossRef]
  59. Wang, W.Q.; Wang, J.; Wu, Y.Y.; Li, D.W.; Allan, A.C.; Yin, X.R. Genome-wide analysis of coding and non-coding RNA reveals a conserved miR164-NAC regulatory pathway for fruit ripening. N. Phytol. 2020, 225, 1618–1634. [Google Scholar] [CrossRef]
  60. Wu, Y.Y.; Liu, X.F.; Fu, B.L.; Zhang, Q.Y.; Tong, Y.; Wang, J.; Yin, X.R. Methyl jasmonate enhances ethylene synthesis in kiwifruit by inducing NAC genes that activate ACS1. J. Agric. Food Chem. 2020, 68, 3267–3276. [Google Scholar] [CrossRef]
  61. Ellis, J.B.; Everhart, B.M. The North American species of Gloeosporium. J. Mycol. 1885, 1, 109–119. [Google Scholar] [CrossRef]
  62. Martin, G. The Phyllostictas of North America. J. Mycol. 1886, 2, 13–20. [Google Scholar] [CrossRef]
  63. Horst, R.K. Field Manual of Diseases on Garden and Greenhouse Flowers; Springer: Dordrecht, The Netherlands, 2013. [Google Scholar]
  64. González, V.M.; Müller, S.; Baulcombe, D. Evolution of NBS-LRR gene copies among dicot plants and its regulation by members of the miR482/2118 superfamily of miRNAs. Mol. Plant 2015, 8, 329–331. [Google Scholar] [CrossRef]
  65. Zhai, J.; Jeong, D.H.; De Paoli, E.; Park, S.; Rosen, B.D.; Li, Y.; Meyers, B.C. MicroRNAs as master regulators of the plant NB-LRR defense gene family via the production of phased, trans-acting siRNAs. Gene Dev. 2011, 25, 2540–2553. [Google Scholar] [CrossRef]
  66. Shivaprasad, P.V.; Chen, H.M.; Patel, K.; Bond, D.M.; Santos, B.A.; Baulcombe, D.C. A microRNA superfamily regulates nucleotide binding site–leucine-rich repeats and other mRNAs. Plant Cell 2012, 24, 859–874. [Google Scholar] [CrossRef]
  67. Zhu, Q.H.; Fan, L.; Liu, Y.; Xu, H.; Llewellyn, D.; Wilson, I. miR482 regulation of NBS-LRR defense genes during fungal pathogen infection in cotton. PLoS ONE 2013, 8, e84390. [Google Scholar] [CrossRef]
  68. You, J.; Chan, Z. ROS regulation during abiotic stress responses in crop plants. Front. Plant Sci. 2015, 6, 1092. [Google Scholar] [CrossRef]
  69. Dreyer, A.; Dietz, K.J. Reactive oxygen species and the redox-regulatory network in cold stress acclimation. Antioxidants 2018, 7, 169. [Google Scholar] [CrossRef]
  70. Lu, Y.; Feng, Z.; Bian, L.; Xie, H.; Liang, J. miR398 regulation in rice of the responses to abiotic and biotic stresses depends on CSD1 and CSD2 expression. Funct. Plant Biol. 2010, 38, 44–53. [Google Scholar] [CrossRef]
  71. Leng, X.; Wang, P.; Zhu, X.; Li, X.; Zheng, T.; Shangguan, L.; Fang, J. Ectopic expression of CSD1 and CSD2 targeting genes of miR398 in grapevine is associated with oxidative stress tolerance. Funct. Integr. Genomics 2017, 17, 697–710. [Google Scholar] [CrossRef]
  72. Yan, G.; Hua, Y.; Jin, H.; Huang, Q.; Zhou, G.; Xu, Y.; Zhu, Z. Sly-miR398 participates in cadmium stress acclimation by regulating antioxidant system and cadmium transport in tomato (Solanum lycopersicum). Int. J. Mol. Sci. 2023, 24, 1953. [Google Scholar] [CrossRef] [PubMed]
Horticulturae 10 00173 g001
Figure 1. Identification of miRNAs in A. venetum. Secondary structures of precursors of two species-specific miRNA for ave-miRN1 (A) and ave-miRN21 (B). The structure diagrams were generated using the UNAFold web server. 5p strands were labeled in blue, and 3p strands were labeled in red. (C) Member quantity of conserved miRNA families in A. venetum. miRNA, microRNA.
Figure 1. Identification of miRNAs in A. venetum. Secondary structures of precursors of two species-specific miRNA for ave-miRN1 (A) and ave-miRN21 (B). The structure diagrams were generated using the UNAFold web server. 5p strands were labeled in blue, and 3p strands were labeled in red. (C) Member quantity of conserved miRNA families in A. venetum. miRNA, microRNA.
Horticulturae 10 00173 g001
Horticulturae 10 00173 g002
Figure 2. Chromosomal localization of conserved and species-specific miRNAs in A. venetum. Black letters indicate conserved miRNAs, red letters indicate species-specific miRNAs with high confidence, and blue letters indicate potential species-specific miRNAs in A. venetum. miRNA, microRNA.
Figure 2. Chromosomal localization of conserved and species-specific miRNAs in A. venetum. Black letters indicate conserved miRNAs, red letters indicate species-specific miRNAs with high confidence, and blue letters indicate potential species-specific miRNAs in A. venetum. miRNA, microRNA.
Horticulturae 10 00173 g002
Horticulturae 10 00173 g003
Figure 3. GO and KEGG enrichment analysis of the targets of conserved and species-specific miRNAs in A. venetum. (A,C) Display GO and KEGG enrichment analysis for target genes of conserved miRNA in A. venetum. (B,D) Depict GO and KEGG enrichment analysis for target genes of species-specific miRNA in A. venetum. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomics; miRNA, microRNA.
Figure 3. GO and KEGG enrichment analysis of the targets of conserved and species-specific miRNAs in A. venetum. (A,C) Display GO and KEGG enrichment analysis for target genes of conserved miRNA in A. venetum. (B,D) Depict GO and KEGG enrichment analysis for target genes of species-specific miRNA in A. venetum. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomics; miRNA, microRNA.
Horticulturae 10 00173 g003
Horticulturae 10 00173 g004
Figure 4. Differential expression analysis of identified miRNAs in A. venetum under MeJA treatment. (A) Volcano map of DEMs; red indicates upregulated genes, green indicates downregulated genes, and black indicates unchanged genes. (B) The expression of conserved and species-specific DEMs of A. venetum in response to MeJA. (C) qRT-PCR verification of MeJA-responsive miRNAs of A. venetum. The Y-axis shows the relative expression levels of conserved miRNAs and species-specific miRNAs. The numerical value is expressed by the average ± SD (n = 3). miRNA, microRNA; MeJA, methyl jasmonate; DEMs, differentially expressed miRNAs.
Figure 4. Differential expression analysis of identified miRNAs in A. venetum under MeJA treatment. (A) Volcano map of DEMs; red indicates upregulated genes, green indicates downregulated genes, and black indicates unchanged genes. (B) The expression of conserved and species-specific DEMs of A. venetum in response to MeJA. (C) qRT-PCR verification of MeJA-responsive miRNAs of A. venetum. The Y-axis shows the relative expression levels of conserved miRNAs and species-specific miRNAs. The numerical value is expressed by the average ± SD (n = 3). miRNA, microRNA; MeJA, methyl jasmonate; DEMs, differentially expressed miRNAs.
Horticulturae 10 00173 g004
Horticulturae 10 00173 g005
Figure 5. Promoter analysis of MeJA-responsive miRNAs in A. venetum. The X-axis represents the stress conditions and hormones that miRNAs may be related to, the Y-axis represents the DEMs, the circle color represents the stress conditions and hormones involved, and the size of the dots represents the degree of involvement. miRNA, microRNA; MeJA, methyl jasmonate; DEMs, differentially expressed miRNAs.
Figure 5. Promoter analysis of MeJA-responsive miRNAs in A. venetum. The X-axis represents the stress conditions and hormones that miRNAs may be related to, the Y-axis represents the DEMs, the circle color represents the stress conditions and hormones involved, and the size of the dots represents the degree of involvement. miRNA, microRNA; MeJA, methyl jasmonate; DEMs, differentially expressed miRNAs.
Horticulturae 10 00173 g005
Horticulturae 10 00173 g006
Figure 6. Functional enrichment analysis of the targets of MeJA-responsive miRNAs in A. venetum. (A,C) GO and KEGG enrichment analyses of the target genes of conserved DEMs in A. venetum. (B,D) GO and KEGG enrichment analyses of the target genes of species-specific DEMs in A. venetum. miRNA, microRNA; MeJA, methyl jasmonate; DEMs, differentially expressed miRNAs; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomics.
Figure 6. Functional enrichment analysis of the targets of MeJA-responsive miRNAs in A. venetum. (A,C) GO and KEGG enrichment analyses of the target genes of conserved DEMs in A. venetum. (B,D) GO and KEGG enrichment analyses of the target genes of species-specific DEMs in A. venetum. miRNA, microRNA; MeJA, methyl jasmonate; DEMs, differentially expressed miRNAs; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomics.
Horticulturae 10 00173 g006
Horticulturae 10 00173 g007
Figure 7. Transcriptomic analysis of the response to MeJA in A. venetum. (A) Volcano map of DEGs. Red represents upregulated genes, green represents downregulated genes, and black represents unchanged genes. (B) Heatmap of the top 20 DEGs. (C) qRT-PCR verification. The Y-axis shows the relative expression level of target genes, and eIF was used as internal reference. The relative expression level is averaged in three technical replicates. The numerical value is expressed by the average ± SD (n = 3). (D) KEGG pathway enrichment analysis of the DEGs. The X-axis represents the enrichment factor, and the Y-axis represents the enriched KEGG pathway. (E) GO enrichment analysis of the DEGs. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomics; MeJA, methyl jasmonate; DEGs, differentially expressed genes.
Figure 7. Transcriptomic analysis of the response to MeJA in A. venetum. (A) Volcano map of DEGs. Red represents upregulated genes, green represents downregulated genes, and black represents unchanged genes. (B) Heatmap of the top 20 DEGs. (C) qRT-PCR verification. The Y-axis shows the relative expression level of target genes, and eIF was used as internal reference. The relative expression level is averaged in three technical replicates. The numerical value is expressed by the average ± SD (n = 3). (D) KEGG pathway enrichment analysis of the DEGs. The X-axis represents the enrichment factor, and the Y-axis represents the enriched KEGG pathway. (E) GO enrichment analysis of the DEGs. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomics; MeJA, methyl jasmonate; DEGs, differentially expressed genes.
Horticulturae 10 00173 g007
Horticulturae 10 00173 g008
Figure 8. The miRNA-mediated gene regulation network in response to MeJA in A. venetum leaves. Red square represents miRNAs, blue square represents targets, yellow square represents biological process. miRNA, microRNA; MeJA, methyl jasmonate; ROS, reactive oxygen species.
Figure 8. The miRNA-mediated gene regulation network in response to MeJA in A. venetum leaves. Red square represents miRNAs, blue square represents targets, yellow square represents biological process. miRNA, microRNA; MeJA, methyl jasmonate; ROS, reactive oxygen species.
Horticulturae 10 00173 g008
Horticulturae 10 00173 g009
Figure 9. Experimental validation of the targeting relationship between miR398 and CSD. (A) The binding site of ave-miR398a-3p on CSD predicted by psRNAtarget. (B) Vector construction for double luciferase reporter gene vector assay. (C) The ratio of LUC/REN in 62-SK+CSD and ave-miR398a-3p+CSD cells. The numerical value is expressed by mean ± SD (n = 5). t test, *** p < 0.01. CSD, Cu/Zn-superoxide dismutase; miRNA, microRNA; LUC/REN, luciferase/Renilla.
Figure 9. Experimental validation of the targeting relationship between miR398 and CSD. (A) The binding site of ave-miR398a-3p on CSD predicted by psRNAtarget. (B) Vector construction for double luciferase reporter gene vector assay. (C) The ratio of LUC/REN in 62-SK+CSD and ave-miR398a-3p+CSD cells. The numerical value is expressed by mean ± SD (n = 5). t test, *** p < 0.01. CSD, Cu/Zn-superoxide dismutase; miRNA, microRNA; LUC/REN, luciferase/Renilla.
Horticulturae 10 00173 g009
Horticulturae 10 00173 g010
Figure 10. MeJA treatment improved the tolerance of A. venetum to oxidative stress. (A) Physiological changes in the leaves of A. venetum after MeJA treatment and MV treatment. (B) MDA content in the leaves of A. venetum under MeJA treatment and MV treatment. (C) REL values in the leaves of A. venetum with MeJA treatment and MV treatment. Different letters indicate significant differences between different groups, and the significance of differences was analyzed using one-way analysis of variance and Tukey’s multiple range test (p < 0.05), n = 5. MeJA, methyl jasmonate; MDA, malondialdehyde; REL, relative electrolyte leakage; MV, methyl viologen.
Figure 10. MeJA treatment improved the tolerance of A. venetum to oxidative stress. (A) Physiological changes in the leaves of A. venetum after MeJA treatment and MV treatment. (B) MDA content in the leaves of A. venetum under MeJA treatment and MV treatment. (C) REL values in the leaves of A. venetum with MeJA treatment and MV treatment. Different letters indicate significant differences between different groups, and the significance of differences was analyzed using one-way analysis of variance and Tukey’s multiple range test (p < 0.05), n = 5. MeJA, methyl jasmonate; MDA, malondialdehyde; REL, relative electrolyte leakage; MV, methyl viologen.
Horticulturae 10 00173 g010
Horticulturae 10 00173 g011
Figure 11. Alteration in ROS accumulation and antioxidant enzyme activities of A. venetum seedling leaves under MeJA application. (A) DAB staining showed the site of H2O2 accumulation in A. venetum leaves under MeJA. The darker the brown is, the more H2O2 content accumulates. NBT staining showed the site of O2− accumulation in A. venetum leaves under MeJA. The darker the blue is, the more O2− content accumulates. (B) The enzyme activities of SOD. Each experiment was performed using three independent biological replicates. Different letters indicate significant differences between different groups, and the significance of differences was analyzed using one-way analysis of variance and Tukey’s multiple range test (p < 0.05). MeJA, methyl jasmonate; SOD, superoxide dismutase; DAB, 3,3′-diaminobenzidine; ROS, reactive oxygen species.
Figure 11. Alteration in ROS accumulation and antioxidant enzyme activities of A. venetum seedling leaves under MeJA application. (A) DAB staining showed the site of H2O2 accumulation in A. venetum leaves under MeJA. The darker the brown is, the more H2O2 content accumulates. NBT staining showed the site of O2− accumulation in A. venetum leaves under MeJA. The darker the blue is, the more O2− content accumulates. (B) The enzyme activities of SOD. Each experiment was performed using three independent biological replicates. Different letters indicate significant differences between different groups, and the significance of differences was analyzed using one-way analysis of variance and Tukey’s multiple range test (p < 0.05). MeJA, methyl jasmonate; SOD, superoxide dismutase; DAB, 3,3′-diaminobenzidine; ROS, reactive oxygen species.
Horticulturae 10 00173 g011
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Tan, J.; Han, X.; Liu, Q.; Dorjee, T.; Zhou, Y.; Sun, H.; Gao, F. Joint Analysis of Small RNA and mRNA Sequencing Unveils miRNA-Mediated Regulatory Network in Response to Methyl Jasmonate in Apocynum venetum L. Horticulturae 2024, 10, 173. https://doi.org/10.3390/horticulturae10020173

AMA Style

Tan J, Han X, Liu Q, Dorjee T, Zhou Y, Sun H, Gao F. Joint Analysis of Small RNA and mRNA Sequencing Unveils miRNA-Mediated Regulatory Network in Response to Methyl Jasmonate in Apocynum venetum L. Horticulturae. 2024; 10(2):173. https://doi.org/10.3390/horticulturae10020173

Chicago/Turabian Style

Tan, Jinhua, Xiaowei Han, Qi Liu, Tashi Dorjee, Yijun Zhou, Huigai Sun, and Fei Gao. 2024. "Joint Analysis of Small RNA and mRNA Sequencing Unveils miRNA-Mediated Regulatory Network in Response to Methyl Jasmonate in Apocynum venetum L." Horticulturae 10, no. 2: 173. https://doi.org/10.3390/horticulturae10020173

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop