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Article

Dissecting microRNA−Target Gene Pairs Involved in Rubber Biosynthesis in Eucommia ulmoides

by
Huimin Liu
1,
Jingjing Hu
2,
Hongyan Du
1,
Lu Wang
1 and
Jun Qing
1,*
1
Key Laboratory of Non-Timber Forest Germplasm Enhancement & Utilization of State Forestry and Grassland Administration, Research Institute of Non-timber Forestry, Chinese Academy of Forestry, Zhengzhou 450003, China
2
School of Information, Renmin University of China, Beijing 100872, China
*
Author to whom correspondence should be addressed.
Forests 2022, 13(10), 1601; https://doi.org/10.3390/f13101601
Submission received: 22 August 2022 / Revised: 26 September 2022 / Accepted: 27 September 2022 / Published: 30 September 2022
(This article belongs to the Section Genetics and Molecular Biology)
Browse Figures
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Abstract

:
MicroRNAs (miRNAs) play essential roles in regulating various development processes in plants. However, their role in regulating rubber biosynthesis in Eucommia ulmoides is largely unknown. Rubber is mainly distributed in the tissue covering the seed (GZ) rather than the periphery (GB) of the pericarp of E. ulmoides during accumulation in May. To investigate the roles of miRNAs in rubber biosynthesis, we conducted high-throughput small RNA sequencing using GZ and GB collected on 11 May (rapid accumulation) and 11 June (reduced accumulation). In total, 12 and 25 miRNAs were either up- or downregulated in GZ in May (GZ511) compared to GB (GB511) in May, while 27 and 38 miRNAs were either up- or downregulated in GZ in May compared to GZ in June (GZ611), respectively. Functional analyses of differentially expressed (DE−) genes targeted by DE-miRNAs revealed that miRNAs may regulate genes involved in rubber biosynthesis. For instance, when Eu-miR45 expression declined, the expression of its predicted target, small rubber particle protein 1 (EuSRPP1), increased in GZ511 vs. GB511 and GZ511 vs. GZ611, possibly resulting in higher rubber accumulation in GZ511. Additionally, we identified potential lncRNA−miRNA−mRNA networks in rubber biosynthesis. Overall, these results indicate that miRNAs play pivotal roles in regulating rubber biosynthesis via miRNA-target gene pairs and lncRNA−miRNA−mRNA networks in E. ulmoides. Our findings will enhance research on the mechanisms of rubber biosynthesis in plants.

1. Introduction

Eucommia ulmoides is a perennial tree native to China, and it belongs to the mono-species family Eucommiaceae [1]. As a traditional Chinese medicine, it has been widely cultivated and studied [2]. In recent decades, interest has grown in this species as a source of natural rubber. Natural rubber can be divided into two types according to monomer (isopentenyl diphosphate, IPP) polymerization, i.e., trans−1,4−polyisoprene (TPI) and cis−1,4−polyisoprene (CPI), which are isomers [3]. More than 2000 plant species can produce cis−polyisoprene, including Hevea brasilienses [4], which is the only commercial species producing natural rubber due to its high yield and superior properties of its rubber [5]. However, the rubber industry is facing serious challenges due to reduced acreage, fatal diseases such as tapping panel dryness, and high tapping costs [6]. E. ulmoides, as a hardy rubber tree with wide adaptability, can be cultivated in large areas, ranging 24°50′ N–41°50′ N, 76°00′ E–126°00′ E; it grows well in poor soil and suffers from few diseases or insects [7]. In addition, the rubber produced by E. ulmoides, also called Eu−rubber, has properties such as high rigidity, a low coefficient of thermal expansion/contraction, and corrosion resistance, which make it attractive [8]. Because of these advantages, E. ulmoides is thought to be an ideal supplement to H. brasiliensis.
Natural rubber is mainly synthesized through the terpenoid backbone biosynthesis pathway. A previous study [7] reported the related genes involved in rubber biosynthesis in E. ulmoides and found that the mevalonate (MVA) pathway is the main donor of IPP. However, scarce information is known about the regulation factors that play important roles in wide processes of plant development and defenses, such as non−coding RNAs [9,10]. Liu et al. [11] revealed that long non−coding RNAs (lncRNAs) might participate in regulating rubber accumulation by modulating the expression of genes related to laticifer differentiation and development, where the rubber is synthesized. Wang et al. [12] identified and characterized microRNAs (miRNAs) in leaves and fruits, but only one miRNA was predicted to be involved in rubber biosynthesis by directly targeting 1−deoxy−d−xylulose 5−phosphate synthase (DXS), a component in the 2−C−methyl−d−erythritol 4−phosphate (MEP) pathway. Ye et al. [13] identified 44 differentially expressed miRNA−mRNA pairs in the leaves collected from E. ulmoides with high and low rubber content. However, none of the miRNA−mRNA pairs were involved in Eu−rubber biosynthesis directly [13]. Thus, further studies are needed to identify possible non−coding RNAs that could be involved in Eu−rubber biosynthesis. Since Eu−rubber is mainly distributed in the central of the pericarp covering the seed and has an obvious temporal accumulation pattern [7,11], it is an efficient way to study the non−coding RNAs related to Eu−rubber biosynthesis in the pericarp.
miRNAs are endogenous non−coding RNAs that are ~22 nucleotides (nt) in length; they play essential roles in both animals and plants. They derive from single−strand RNA precursors that are 70–90 nt in length and can form hairpin structures [14]. miRNAs negatively regulate their target genes by transcriptional degradation or translational repression with a perfect or imperfect match, respectively [15,16]. miRNAs have been shown to be involved in many bioprocesses in plants, including organ development [17], disease and insect resistance [18], and secondary metabolism [19]. Additionally, miRNAs play key roles in the competing endogenous RNA (ceRNA) network, which is based on miRNA−mediated gene regulation. CeRNAs sharing the same miRNA recognition element (MRE) can regulate each other by competing for miRNA binding sites [20]. However, no information is currently available on ceRNA networks underlying rubber biosynthesis in E. ulmoides.
In this study, we conduct high−throughput small RNA sequencing using the pericarp of E. ulmoides samara during Eu−rubber fast (11 May) and slow (11 June) rubber accumulation periods. The pericarp was further divided into two parts, the periphery of the pericarp and the tissue covering the seed, where Eu−rubber is mainly distributed [11]. The objectives of this study are to dissect miRNA–mRNA pairs and lncRNA–miRNA–mRNA networks that participate in Eu−rubber biosynthesis based on lncRNAs and genes identified previously [11].

2. Materials and Methods

2.1. Plant Material and RNA Sequencing

Fruits of E. ulmoides ‘Huazhong No. 6′ were collected during fast (11 May) and slow (11 June) accumulation periods, respectively. The seed was removed and the pericarp was divided into two parts—the periphery (GB) and the tissue covering the seed (GZ)—since the seeds are free of rubber, which is mainly distributed in GZ. The plant samples were frozen in liquid nitrogen and stored at −80 °C.
Total RNA from three biological replicates of each sample was extracted using TRIzol (Invitrogen, Carlsbad, CA, USA). Sequencing libraries were constructed using the NEBNext® Multiplex Small RNA Library Prep Set for Illumina® (NEB, San Diego, CA, USA) according to the manufacturer’s instructions. The libraries were sequenced on the Illumina Hiseq X ten platform (Illumina, San Diego, CA, USA), and 50 bp single−end reads were generated. In this study, three small RNA libraries from each biological replicate were constructed and sequenced.

2.2. miRNA Identification

Clean reads were obtained by removing reads containing poly−N, reads with 5′ adapter contaminants, reads without the 3′ adapter or the insert tag containing poly A/T/C/G, and low−quality reads from the raw data. Clean reads of 18–35 nt in length were mapped to the reference genome of E. ulmoides using Bowtie v1.3.0 [21] without mismatch. For known miRNA identification, the reads were mapped to plant miRNA sequences in the miRbase 22.1 database [22] and the miRNAs reported in references [12,13], and their secondary structures were predicted by mirdeep2 [23] and srna−tools−cli. After known miRNA identification, reads originating from protein−coding genes, repeat sequences, rRNAs, tRNAs, snRNAs, and snoRNAs, according to the genome annotation of E. ulmoides and natural antisense transcripts of siRNAs that were de novo predicted, were removed. The remaining sequences were used for novel miRNA prediction. miREvo [24] and mirdeep2 [23] software were integrated to predict novel miRNA through the exploration of the secondary structure, the Dicer cleavage site, and the minimum free energy of the small RNA sequences unannotated in the former steps. Custom scripts were used to obtain the identified miRNA counts.
For small RNA sequences mapped to more than one category, the following priority rule was applied: known miRNA > rRNA > tRNA > snRNA > snoRNA > repeat > gene > NAT−siRNA > gene > novel miRNA > ta−siRNA; this was to make sure that every unique small RNA was mapped to only one annotation.

2.3. miRNA Target Prediction and Expression Analysis

The expression levels of genes and lncRNAs were obtained from our previous study [11]. Target genes of miRNA were predicted by psRNATarget with default parameters [25]. miRNA expression levels were estimated using the TPM (transcript per million) method through the following criteria [26]: Normalization formula: Normalized expression = mapped read count/Total reads × 1,000,000. Differential expression analysis was performed using the DESeq R package (1.8.3). Significantly differentially expressed miRNAs (DE−miRNAs), mRNAs (DE−mRNAs), and lncRNAs (DE−lncRNAs) were identified by p−value < 0.05.

2.4. CeRNA Network Construction

The ceRNA networks among lncRNAs, miRNAs, and mRNAs were established as suggested elsewhere [9]. Briefly, the interactions between identified lncRNAs and miRNAs were predicted using target mimics, as suggested by Meng et al. [27]. As introduced above, miRNA–mRNA pairs were predicted using psRNATarget. Afterwards, the ceRNA pairs were gathered. Noticeably, ceRNA networks were constructed according to two criteria: (1) DE−lncRNAs and DE−mRNAs should be targeted by the same miRNA; (2) the DE−lncRNAs and DE−mRNAs targeted by the same miRNA should have identical expression trends, i.e., co−upregulated or co−downregulated [20].

2.5. RT−qPCR Verification

Total RNA was extracted, as mentioned above, for RNA sequencing. The RT−qPCR for miRNAs was conducted according to the manual of TB Green® Premix Ex TaqTM II (RR820A, TaKaRa, Japan). The RT−qPCR for mRNAs and lncRNAs was carried out as suggested previously [11]. Specific primers used for RT−qPCR are listed in Table S1. Actin and GAPDH were used as reference genes (Table S1). Relative gene expression levels were calculated using the 2−ΔΔCt method [28].

2.6. Transient Co−Transformation of miRNA–mRNA Pairs

To validate the regulatory relationship between miRNAs and the target genes predicted by psRNATarget, transient co−expression assays were carried out on the leaves of Nicotiana benthamiana, as described by Li et al. [29]. In brief, the miRNA precursors were amplified using the genomic DNA extracted from E. ulmoides pericarps and specific primers (Table S1). The mRNAs were amplified using cDNA reversed from the total RNA extracted from E. ulmoides pericarps and specific primers (Table S1). The miRNA and mRNA products were cloned into the pCAMBIA2300 vector under the control of a 35S promoter. The constructs harboring target miRNA and mRNA were then transformed into Agrobacterium tumefaciens strain GV3101 by electroporation. Equal amounts of A. tumefaciens cell cultures containing miRNAs and their target genes were mixed before infiltration. The mixture was infiltrated into the leaves of N. benthamiana, as described by He et al. [30]. After 2 d, the infiltrated leaves were harvested for RT−qPCR analyses. The tobacco tubulin was used as the reference gene (Table S1).

3. Results

3.1. miRNA Identification and Target Prediction in E. ulmoides

Previous studies have revealed the spatiotemporal specificity of rubber accumulation in the samara of E. ulmoides [7,11]. To identify miRNAs that might be involved in the regulation of rubber biosynthesis in E. ulmoides, we collected the pericarps during rapid (11 May) and slow (11 June) rubber accumulation periods, respectively. The collected pericarps were divided into two parts—GB (the periphery) and GZ (covering the seed)—where rubber is mainly distributed (Figure S1).
Through RNA sequencing on the Illumina X ten platform, a total of 150,822,012 raw reads were generated, and 133,186,679 clean reads were obtained after filtering (Table S2). More than 89% of sRNAs were mapped onto the reference genome of E. ulmoides (Table S2). Through the statistic of length distribution, we found that approximately 80% of the sRNAs were 20~24 nt in length, with the 24 nt class being the highest in total abundance (35.4%), followed by the 22 nt class (17.2%) and the 21 nt class (14.9%) (Figure 1).
A total of 118 known miRNAs without mismatches were identified in E. ulmoides (Table S3). By removing the tags matching known miRNAs, rRNAs, tRNAs, snRNAs, snoRNAs, repeats, NAT−siRNAs, and genes, we identified 110 predicted novel miRNAs based on the characteristics of the hairpin structure of miRNA precursors (Table S3). In total, 228 miRNAs were identified in E. ulmoides, representing 27 miRNA families in E. ulmoides (Table S4). Among these miRNAs, the top three abundant miRNAs were miR159a, miR369a−5p, and miR369b−5p, accounting for 27.0%, 12.4%, and 11.3% of total miRNA reads, respectively.
In total, 3991 protein−coding genes were predicted to be targeted by 226 miRNAs, except for 3 miRNAs, i.e., Eu−miR74, n−Eu−miR48, and n−Eu−miR79, which had no targets. Among these 3991 target genes, 9, 11, 7, and 8 genes that are involved in MEP, MVA, rubber initiator synthesis, and rubber elongation were included, indicating that the rubber biosynthesis in E. ulmoides might be regulated by miRNAs (Table S5).

3.2. Differentially Expressed miRNAs and Target Genes

Since Eu−rubber accumulates rapidly during May and is stored in the tissue covering the seed (Figure S1), we focused on differentially expressed miRNAs (DE−miRNAs) in the comparisons of GZ511 vs. GB511 and GZ511 vs. GZ611 (Figure 2A–C).
In GZ511 vs. GB511, we identified 37 DE−miRNAs and 31 corresponding DE−target genes (Figure 2A,C, Table S6). To further understand the function of these DE−miRNAs, the corresponding A. thaliana homologs of their target genes were chosen for functional category analysis using MapMan software and agriGO [31,32]. In total, the 31 genes were assigned to 10 MapMan categories (Table S7), of which the top three categories were protein (6 genes), hormone metabolism (3 genes), and signaling (3 genes) (Figure 3). Since less than 10 entries can be mapped with GO, there were no enriched GO terms. Intriguingly, a novel miRNA, Eu−miR45, was downregulated in GZ511 vs. GB511 (Table S6). Eu−miR45 was predicted to target small rubber particle protein 1 (EuSRPP1), which is one of the essential genes involved in rubber elongation [7], and its transcript level increased in GZ511 vs. GB511 (Table S6). Hence, the downregulation of Eu−miR45 and upregulation of its target gene EuSRPP1 possibly contributed to the improved biosynthesis of rubber, leading to more Eu−rubber in GZ511 compared to GB511.
In GZ511 vs. GZ611, we identified 65 DE−miRNAs and 239 corresponding DE−target genes (Figure 2B,C, Table S8), including 10 genes involved in the rubber biosynthesis pathway, such as acetyl−CoA C−acetyltransferase 1 (EuAACT1) in the MVA pathway, EuDXS2 in the MEP pathway, and EuSRPP1, which is involved in rubber elongation [7]. We also conducted functional category analysis for the DE−target genes of DE−miRNAs. In total, 236 genes had A. thaliana homologs and were assigned to 25 MapMan categories (Table S9). The top five categories were protein (33 genes), signaling (23 genes), RNA (22 genes), transport (14 genes), and secondary metabolism (12 genes) (Figure 3, Table S9). In addition, these DE−target genes were significantly assigned to 107 GO terms related to cellular components, molecular function, and biological processes (FDR < 0.05) (Table S10). In the cellular component category, the top three terms were cell, cell part, and cytoplasm (Figure 4, Table S10). Since Eu−rubber is synthesized in latex cells [33] and Eu−rubber biosynthesis occurs during latex cell differentiation and development, we hypothesized that miRNAs play a role in Eu−rubber biosynthesis by regulating the target genes related to latex cells, where Eu−rubber is synthesized. In the molecular function category, the top three terms were binding, catalytic activity, and transferase activity (Figure 4, Table S10). In the biological process category, the top three terms were cellular process, metabolic process, and single−organism process (Figure 4, Table S10). Noticeably, some of these miRNAs, such as miR166a−3p, Eu−miR13, Eu−miR24, and miR164c−5p, were predicted to affect the expression of target genes that were possibly involved in rubber biosynthesis (Table S8). For instance, miR166a−3p was downexpressed in GZ511 vs. GZ611 and was predicted to target acetyl−CoA C−acetyltransferase 1 (EuAACT1), which is involved in the MVA pathway during rubber accumulation (Figure 5, Table S8). The transcript level of EuAACT1 was upregulated in GZ511 vs. GZ611 (Figure 5, Table S8). Therefore, the decreased expression levels of miR166a−3p and the stimulated mRNA levels of EuAACT1 might contribute to a higher biosynthesis of rubber, leading to the rapid accumulation of Eu−rubber during May. Similarly, we also found that the downexpression of Eu−miR13 was predicted to target EuDXS2, which participates in the MEP pathway during rubber biosynthesis [7]. The transcript level of EuDXS2 was increased in GZ511 vs. GZ611 (Table S8). These results suggest that the downexpression of miR166a−3p and Eu−miR13 and the upregulation of their targets, EuAACT1 and EuDXS2, are probably associated with higher Eu−rubber accumulation in the pericarps during May.
Interestingly, 20 miRNAs had identical expression trends in GZ511 vs. GB511 and in GZ511 vs. GZ611, i.e., co−upregulated (7 miRNAs) and co−downregulated (13 miRNAs) (Table S11). Correspondingly, 15 DE−target genes of these 20 miRNAs also had identical expression trends in the two comparisons above (Table S11). Eu−miR45 was downexpressed and its target gene EuSRPP1 was upregulated in both comparisons of GZ511 vs. GB511 and GZ511 vs. GZ611 (Table S11), indicating that Eu−miR45 plays an important role in regulating Eu−rubber biosynthesis. Furthermore, eight DE−miRNAs and six target genes were selected to verify the sequencing result by RT−qPCR. The expression of these miRNAs, determined by RT−qPCR, was consistent with that determined by RNA sequencing (Figure S2A–P).
To validate the predicted miRNA−target genes in this study, transient co−expression assays were employed in N. benthamiana leaves. Two pairs that are involved in Eu−rubber biosynthesis, including miR166a−3p−EuAACT1 and Eu−miR45−EuSRPP1, were selected. As expected, the expression level of EuAACT1 was significantly reduced when it was co−expressed with miR166a−3p. The transcript level of EuSRPP1 was also markedly decreased when Eu−miR45 was co−expressed in comparison with those of only the target genes EuAACT1 and EuSRPP1, which were transiently expressed in the leaves of N. benthamiana (Figure 6). These results suggest that EuAACT1 and EuSRPP1 are the target genes of miR166a−3p and Eu−miR45, respectively.

3.3. The lncRNA–miRNA–mRNA Networks

miRNAs can also act as mediators between lncRNAs and genes, in which lncRNAs and genes share common miRNA binding sites [34]. Thus, lncRNAs can function as miRNA sponges, sequester miRNAs, and limit miRNA availability to repress their targets, thereby favoring the expression of miRNA−targeted genes [35]. Therefore, we established the possible regulation of lncRNA−miRNA−mRNA networks in E. ulmoides. We mainly focused on lncRNA−miRNA−mRNA pairs involved in rubber biosynthesis.
In GZ511 vs. GB511, three lncRNAs (lnc005824T, lnc002681T, and lnc004261T) and one gene (EuSRPP1) were connected via two novel miRNAs (n−Eu−miR86 and Eu−miR45) (Figure 7, Table S12). In GZ511 vs. GZ611, 163 lncRNAs, 76 miRNAs, and 227 target genes, including 17 genes involved in rubber biosynthesis, were connected by 685 edges (Figure S3, Table S13). To further understand the gene functions in this network, we conducted GO analysis based on A. thaliana homologous gene IDs (AGIs) using agriGO [32]. In total, 207 unique homologous AthIDs were significantly assigned to 181 GO terms related to cellular components, molecular function, and biological processes (FDR < 0.05) (Tables S14 and S15). In the cellular component category, the top three terms were cell, intracellular, and cytoplasm. In the molecular function category, catalytic activity and binding were the two most enriched terms. In the biological process category, the top three terms were cellular process, single−organism process, and metabolic process. Intriguingly, the pair of lnc004261T−Eu−miR45−EuSRPP1 was found in both comparisons of GZ511 vs. GB511 and GZ511 vs. GZ611 (Tables S12 and S13).

4. Discussion

In this study, we obtained more than one hundred million sRNA reads from the pericarps of E. ulmoides using high−throughput sequencing. Of these sRNAs, the most abundant sRNAs were the 24 nt class, which is in accordance with previous reports about E. ulmoides [12,13], Liriodendron chinense [17], Zea mays [36], and Ginkgo biloba [37]. In total, we identified 228 miRNAs, including 118 known miRNAs and 110 novel miRNAs, that represent 27 miRNA families. miR159 was found to be the most abundant miRNA, accounting for 35.6% of the total miRNA reads, which is similar to the percentages in A. thaliana, Medicago truncatula, and maize [38,39,40]. miR159 is strongly conserved and has been found in all examined seed−bearing plants [41]. Moreover, three members of the miR159 family, i.e., miR159a, miR159b, and miR159c, were identified in E. ulmoides, and the expression levels of miR159a and 159b were higher than miR159c. Similar results were also found in A. thaliana [38,42]. The miR159 family has been confirmed to target R2R3 MYB genes, and the miR159−MYB pair plays a vital role in fruit development [43]. In this study, we also identified the miR159−MYB pairs. The high expression level of miR159 indicates that this miRNA family might play a role in the fruit development of E. ulmoides.
Eu−rubber is synthesized through the terpenoid backbone pathway by continuously adding the IPP unit to its isomer dimethylallyl diphosphate (DMAPP) [3]. Previous reports have revealed that the MVA pathway in the cytoplasm is the main IPP donor for Eu−rubber biosynthesis and identified the protein−coding genes involved in Eu−rubber biosynthesis [7]. In the comparison of GZ511 vs. GZ611, we identified 65 DE−miRNAs and 239 corresponding DE−target genes. Among these, at least one miRNA−target gene pair at each step of the MVA pathway was involved. For instance, the miR166a−3p−EuAACT1 and Eu−miR45−EuSRPP1 pairs participate in the MVA pathway and rubber elongation, respectively. The degradation effects of miR166a−3p on EuAACT1 and Eu−miR45 on EuSRPP1 were verified using co−expression transient assays in N. benthamiana leaves. EuAACT1 has been proven to participate in the first step of the MVA pathway, and EuSRPP1 is an important gene during Eu−rubber elongation [7]. Therefore, the downexpression of miR166a−3p and Eu−miR45 results in the upregulation of EuAACT1 and EuSRPP1, probably by contributing to the higher accumulation of Eu−rubber in GZ511 compared to GZ611. Similarly, other miRNAs, including miR164c−5p, miR164a, n−Eu−miR88, and miR396b−5p, have similar roles in Eu−rubber biosynthesis by negatively regulating the expression of target genes involved in the MVA pathway and rubber elongation.
In addition to the negative regulation of genes involved in Eu−rubber biosynthesis, we also identified several miRNAs that might be related to latex cell differentiation and development, where rubber is synthesized and stored [33]. For instance, the downregulation of Eu−miR13 increased the mRNA levels of EUC07254−RA and EUC20751−RA in the comparisons of GZ511 vs. GB511 and GZ511 vs. GZ611 (Table S11). EUC07254−RA encodes a myosin family protein that plays critical roles in cytokinesis, chemotactic migration, and morphological changes during multi−cellular development [44]. The Arabidopsis homologous of EUC20751−RA encodes a microtubule−associated protein and is essential for cell expansion during petal morphogenesis in A. thaliana [45]. Moreover, miR168a−5p was downregulated and its target gene EUC21491−RA was upregulated in the comparisons of GZ511 vs. GB511 and GZ511 vs. GZ611 (Table S11). EUC21491−RA encodes callose synthase 3 (CALS3), which is involved in callose synthesis at the forming of cell plates during cytokinesis [46]. Therefore, the decreased expression levels of Eu−miR13 and miR168a−5p, as well as elevated mRNA levels of EUC07254−RA, EUC20751−RA, and EUC21491−RA, probably accelerate latex cell division and expansion in GZ511 compared with GB511 or GZ611. In E. ulmoides, the active differentiation and development of latex cells will promote the accumulation of Eu−rubber. Thus, the differentially expressed miRNAs were also supposed to act as important regulators in Eu−rubber biosynthesis by regulating the expression of genes involved in the related processes of latex cell differentiation and development.
Although several studies have dissected transcriptomic networks underlying mRNAs and non−coding RNAs in Eu−rubber biosynthesis [11,12,13], no studies have been conducted on the regulatory networks of mRNAs, lncRNAs, and miRNAs in Eu−rubber biosynthesis. For the first time, we dissect the lncRNA−miRNA−mRNA networks involved in Eu−rubber biosynthesis. In particular, the lnc004261T−Eu−miR45−EuSRPP1 pair was found in both GZ511 vs. GB511 and GZ511 vs. GZ611. Lnc004261T and EuSRPP1 were both upregulated in both comparisons. EuSRPP1 is an important gene involved in rubber elongation [7]. Since lnc004261T can act as an eTMs for Eu−miR45, the increased expression of lnc004261T can reduce the level of Eu−miR45, leading to the upregulation of its target, EuSRPP1, and, finally, Eu−rubber accumulation in the pericarps of E. ulmoides. These results suggest that lncRNA−miRNA−mRNA networks play pivotal roles in Eu−rubber biosynthesis.

5. Conclusions

In this study, we performed small RNA sequencing of pericarps during different Eu−rubber biosynthesis stages in E. ulmoides. In total, 65 DE−miRNAs were predicted to negatively regulate the expression of 239 target genes. Functional analysis of DE−target genes suggests that DE−miRNAs probably play pivotal roles in Eu−rubber biosynthesis in two patterns. In detail, DE−miRNAs could regulate genes involved in Eu−rubber biosynthesis, including the MVA pathway and rubber elongation. For instance, the downregulation of Eu−miR45 caused the upregulation of EuSRPP1, probably resulting in the higher accumulation of Eu−rubber in GZ511 compared to GZ611 or GB511. DE−miRNAs could also regulate the expression of genes related to latex cell differentiation and development, where rubber is synthesized and stored. As an example, the downexpression of miR168a−5p might have induced the transcript level of CALS3, which probably promoted the latex cell division in GZ511 compared with that in GZ611 or GB511. Furthermore, lncRNA−miRNA−mRNA networks that are involved in Eu−rubber biosynthesis were dissected. These results suggest that miRNA plays an essential role in regulating the Eu−rubber biosynthesis of E. ulmoides through miRNA−target gene pairs and lncRNA−miRNA−mRNA networks.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f13101601/s1, Figure S1: Distribution of Eu−rubber in the pericarp of E. ulmoides (Liu et al. 2018); Figure S2: RT−qPCR validation of the expression levels of miRNAs, mRNAs, and lncRNAs; Figure S3: The lncRNA−miRNA−mRNA networks in the pericarp of E. ulmoides; Table S1: Primers used in this study; Table S2: Sequencing data statistics; Table S3: Known and novel miRNAs identified in E. ulmoides; Table S4: Family information of miRNAs identified in E. ulmoides; Table S5: Target genes of miRNAs involved in rubber biosynthesis; Table S6: DE−miRNAs and their corresponding DE−target genes (GZ511 vs. GB511); Table S7: MapMan categories of DE−target genes (GZ511 vs. GB511); Table S8: DE−miRNAs and their corresponding DE−target genes (GZ511 vs. GZ611); Table S9: MapMan categories of DE−target genes (GZ511 vs. GZ611); Table S10: GO enrichment of DE−genes targeted by DE−miRNAs (GZ511 vs. GZ611); Table S11: DE−miRNAs and their DE−target genes that had identical expression trends in GZ511 vs. GB511 and in GZ511 vs. GZ611; Table S12: LncRNA–miRNA–mRNA networks identified in GZ511 vs. GB511; Table S13: LncRNA−miRNA−mRNA networks identified in GZ511 vs. GZ611. LncRNAs and genes targeted by the same miRNA are lighted by the same color module; Table S14: 229 genes in the lncRNA−miRNA−mRNA networks of GZ511 vs. GZ611, and their homologous A. thaliana gene IDs; Table S15: GO enrichment of genes in the lncRNA−miRNA−mRNA networks (GZ511 vs. GZ611).

Author Contributions

Conceptualization, J.Q. and L.W.; methodology, H.L., J.H., and H.D.; software, H.L. and J.H.; validation, H.L. and H.D.; formal analysis, H.L.; investigation, H.L. and H.D.; resources, J.Q. and L.W.; data curation, H.L.; writing—original draft preparation, H.L.; writing—review and editing, H.L., J.Q., and L.W.; visualization, H.L., J.H., and H.D.; supervision, J.Q. and H.D.; project administration, J.Q. and L.W.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the central non–profit research institution of the Chinese Academy of Forestry (silviculture), grant number CAFYBB2017ZX001–9, and the National Key Research and Development Program of China, grant number 2017YFD0600700.

Data Availability Statement

The datasets generated and analyzed during the current study are available in the BIG Data Center (http://bigd.big.ac.cn/) under accession number CRA005037, accessed on 31 December 2022.

Acknowledgments

The authors thank Mengzhen Huang and Wanyu Xu of the Chinese Academy of Forestry for their help in the sample collection and RNA extraction.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Length distribution of sRNAs in E. ulmoides.
Figure 1. Length distribution of sRNAs in E. ulmoides.
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Figure 2. Volcano plots of up− and downregulated miRNAs in the comparisons of GZ511 vs. GB511 (A) and GZ511 vs. GZ611 (B), and heatmap of DE−miRNAs drawn based on Z−scores of log10 (TPM) (C).
Figure 2. Volcano plots of up− and downregulated miRNAs in the comparisons of GZ511 vs. GB511 (A) and GZ511 vs. GZ611 (B), and heatmap of DE−miRNAs drawn based on Z−scores of log10 (TPM) (C).
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Figure 3. Functional category of DE−target genes of DE−miRNAs during Eu−rubber biosynthesis.
Figure 3. Functional category of DE−target genes of DE−miRNAs during Eu−rubber biosynthesis.
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Figure 4. GO enrichment analysis of DE−genes targeted by DE−miRNAs in GZ511 vs. GZ611. The top 15 GO terms from each category are presented.
Figure 4. GO enrichment analysis of DE−genes targeted by DE−miRNAs in GZ511 vs. GZ611. The top 15 GO terms from each category are presented.
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Figure 5. The differentially expressed miRNA−target gene pairs involved in Eu−rubber biosynthesis. Red and blue indicate up− and downregulated miRNAs and target genes under the comparison of GZ511 vs. GZ611, respectively. Detailed information about differentially expressed target genes is presented in Table S8. AACT, acetyl−CoA C−acetyltransferase; HMGS, hydroxymethylglutaryl−CoA synthase; HMGR, hydroxymethylglutaryl−CoA reductase; MDC, mevalonate pyrophosphate decarboxylase; SRPP, small rubber particle protein; HMG−CoA, 3−hydroxy−3−methylglutaryl−CoA; MVA, mevalonate; MVAP, mevalonate−5−phosphate; MVAPP, mevalonate−5−diphosphate; IPP, isopentenyl diphosphate; DMAPP, dimethylallyl diphosphate; GPP, geranyl diphosphate; FPP, farnesyl diphosphate; GGPP, geranylgeranyl diphosphate.
Figure 5. The differentially expressed miRNA−target gene pairs involved in Eu−rubber biosynthesis. Red and blue indicate up− and downregulated miRNAs and target genes under the comparison of GZ511 vs. GZ611, respectively. Detailed information about differentially expressed target genes is presented in Table S8. AACT, acetyl−CoA C−acetyltransferase; HMGS, hydroxymethylglutaryl−CoA synthase; HMGR, hydroxymethylglutaryl−CoA reductase; MDC, mevalonate pyrophosphate decarboxylase; SRPP, small rubber particle protein; HMG−CoA, 3−hydroxy−3−methylglutaryl−CoA; MVA, mevalonate; MVAP, mevalonate−5−phosphate; MVAPP, mevalonate−5−diphosphate; IPP, isopentenyl diphosphate; DMAPP, dimethylallyl diphosphate; GPP, geranyl diphosphate; FPP, farnesyl diphosphate; GGPP, geranylgeranyl diphosphate.
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Figure 6. Validation of the predicted miRNA−target gene pairs using the transient co−expression assays in N. benthamiana leaves (A,B). The expression levels were quantified using RT−qPCR. Bars indicate means ± SE (n = 3). Different letters on the error bars indicate significant differences.
Figure 6. Validation of the predicted miRNA−target gene pairs using the transient co−expression assays in N. benthamiana leaves (A,B). The expression levels were quantified using RT−qPCR. Bars indicate means ± SE (n = 3). Different letters on the error bars indicate significant differences.
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Figure 7. The lncRNA−miRNA−mRNA networks in the pericarp of E. ulmoies during Eu−rubber biosynthesis. Triangles, round rectangles, and circular nodes represent miRNAs, lncRNAs, and mRNAs, respectively. Red and green colors indicate up− and downregulated RNAs in comparison to GZ511 vs. GB511.
Figure 7. The lncRNA−miRNA−mRNA networks in the pericarp of E. ulmoies during Eu−rubber biosynthesis. Triangles, round rectangles, and circular nodes represent miRNAs, lncRNAs, and mRNAs, respectively. Red and green colors indicate up− and downregulated RNAs in comparison to GZ511 vs. GB511.
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Liu, H.; Hu, J.; Du, H.; Wang, L.; Qing, J. Dissecting microRNA−Target Gene Pairs Involved in Rubber Biosynthesis in Eucommia ulmoides. Forests 2022, 13, 1601. https://doi.org/10.3390/f13101601

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Liu H, Hu J, Du H, Wang L, Qing J. Dissecting microRNA−Target Gene Pairs Involved in Rubber Biosynthesis in Eucommia ulmoides. Forests. 2022; 13(10):1601. https://doi.org/10.3390/f13101601

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Liu, Huimin, Jingjing Hu, Hongyan Du, Lu Wang, and Jun Qing. 2022. "Dissecting microRNA−Target Gene Pairs Involved in Rubber Biosynthesis in Eucommia ulmoides" Forests 13, no. 10: 1601. https://doi.org/10.3390/f13101601

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