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Genome-Wide Identification and Analysis of MicroRNAs Involved in Witches’-Broom Phytoplasma Response in Ziziphus jujuba

  • Fenjuan Shao,

    Affiliation State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China

  • Qian Zhang,

    Affiliation State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China

  • Hongwei Liu,

    Affiliation State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China

  • Shanfa Lu ,

    peterqdy@aliyun.com (DQ); sflu@implad.ac.cn (SL)

    Affiliation Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

  • Deyou Qiu

    peterqdy@aliyun.com (DQ); sflu@implad.ac.cn (SL)

    Affiliation State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China

Abstract

MicroRNAs (miRNAs) play an important role in responding to biotic and abiotic stresses in plants. Jujube witches’-broom a phytoplasma disease of Ziziphus jujuba is prevalent in China and is a serious problem to the industry. However, the molecular mechanism of the disease is poorly understood. In this study, genome-wide identification and analysis of microRNAs in response to witches’-broom was performed. A total of 85 conserved miRNA unique sequences belonging to 32 miRNA families and 24 novel miRNA unique sequences, including their complementary miRNA* strands were identified from small RNA libraries derived from a uninfected and witches’-broom infected Z. jujuba plant. Differentially expressed miRNAs associated with Jujube witches’-broom disease were investigated between the two libraries, and 12 up-regulated miRNAs and 10 down- regulated miRNAs identified with more than 2 fold changes. Additionally, 40 target genes of 85 conserved miRNAs and 49 target genes of 24 novel miRNAs were predicted and their putative functions assigned. Using the modified 5’-RACE method, we confirmed that SPL and MYB were cleaved by miR156 and miR159, respectively. Our results provide insight into the molecular mechanisms of witches’-broom disease in Z. jujuba.

Introduction

Zizyphus jujuba (common name Chinese Jujube) is an economically important fruit tree species in China, belonging to the family Rhamnaceae [1]. It is widely used in traditional Chinese medicine for at least 3,000 years, because its fruit contains high vitamin C content, abundant phenolic compounds, carbohydrate, minerals, cyclic AMP and other important nutrients [13]. Jujube witches’-broom (JWB) disease is prevalent in China and causes serious problems to the industry [4]. It is caused by phytoplasmas which are bacteria without cell walls that were first discovered in the phloem of plants in 1967 by Yoji Doi and co-workers [5]. Phytoplasmas are transmitted by phloem-sucking leafhoppers and Chinese Jujube plants infected with phytoplasmas display a variety of symptoms, such as small leaves, yellowing, witches’-broom, phyllody, stunting, sterile flowers and finally death after a few years of infection [6, 7]. Phytoplasmas are very destructive agricultural pathogens, and have devastating effects on over 1000 plant species worldwide [8, 9].

A previous study of Mexican lime trees infected with phytoplasma identified several candidate genes and proteins that might be involved in the interaction of Mexican lime trees with the phytoplasma [10, 11]. Although some progress has been made in understanding the regulation that is involved in plant-phytoplasma interactions [12], the molecular mechanisms involved in the JWB disease and the symptoms are poorly understood [13].

In recent years, many studies have shown that small RNAs (sRNAs) have numerous roles in the development of plants, defense against viruses and transposons, chromatin modifications, responses to biotic and abiotic stresses etc. In plants, microRNAs (miRNAs) and small interfering RNAs (siRNAs) are two major classes of small RNAs [14]. miRNAs are produced from the primary miRNA transcripts with internal stem-loop structures, whereas siRNAs are derived from dsRNAs transcripts. To regulate gene expression, the generated sRNA are loaded into RNA-induced silencing complexes (RISCs) to guide and interact with homologous RNA or DNA molecules for direct RNA cleavage, translational repression or DNA methylation [15].

High-throughput sequencing provides a comprehensive means of identifying and studying the expression of small RNAs. miRNAs play an important role in disease resistance in plants [1620], for example, a total of 87 differentially regulated miRNAs have been identified to be responsive to fungal stress in wheat [20]. However, to our best knowledge, there is no report on miRNAs associated with JWB in Z. jujuba. Understanding the molecular mechanisms of witches’-broom disease associated with miRNAs is potentially important for developing efficient methods to control the disease. With the aim of identifying miRNAs involved in JWB disease, we constructed two small RNAs libraries from the sprig leaves of uninfected wild type (ZZN) Z. jujuba plants and plants with JWB disease (ZZD). miRNAs and their targets were identified from both small RNA libraries and differentially expressed miRNAs associated with JWB disease were determined. Our results provide insight into the molecular mechanisms of JWB disease in Z. jujuba.

Materials and Methods

Plant materials

The Z. jujuba wild type (ZZN) and the infected plant (ZZD) with witches’-broom disease used in this experiment were grown in Beijing Olympic Park (116°40′7.43"E, 39°99′9.45"N). Sprig of Z. jujuba leaves were collected from 10-year-old plants with the permission granted by the administrative department of Olympic Park. For each sample, materials from three plants were pooled and stored in liquid nitrogen until use.

Small RNA library construction

Total RNAs were extracted from the wild type (ZZN) and the infected plant (ZZD) using Trizol RNA extraction kit (Life Technology, Beijing) according to the manufacturer’s instruction. Two small RNA samples were sequenced by Novogene (China) using Illumina HiSeq2500 system, and the raw reads generated by Illumina sequencing were submitted to the SRA database, Accession No. SRP090598.

Bioinformatics analysis of sequencing data

After removing the adapters and low-quantity sequences from the raw reads, the 18–30 nt clean reads were compared with Rfam database and the NCBI nucleotide database to removed the rRNA, tRNA, snRNA and snoRNA for further analyses. The remaining sequences in the ZZN and ZZD libraries at least ten reads were searched against miRBase 21.0 with a maximum of three mismatches allowed [21] to identify conserved miRNAs in Z. jujuba, and then the resulting sequences were screened for the presence of the characteristic hairpin structures using the program RNAfold [22]. The software Mireap (https://sourceforge.net/projects/mireap/) was used to predict novel miRNAs, which could be mapped to the Z. jujuba genome. The resulting secondary structures were then manually checked. Criteria described by Meyers et al were applied to annotate the novel miRNAs [23]. The reads of small RNAs were normalized to one million by the total number of small RNAs in each library for comparing the differential expression levels of the miRNAs in the ZZN and ZZD libraries.

Target gene prediction for miRNAs

Target genes prediction of the known and novel miRNAs was performed against assembled Z. jujuba unigenes using psRNATarget [24]. The maximum expectations of 3 and the target accessibility-allowed maximum energy to unpair the target site of 50 were applied. The functions of targets were annotated by blast analysis against the Nr protein database [25] using default parameters.

Quantitative RT-PCR

MicroRNAs expression levels were quantified using Poly (A) Tailing method, following the previously reported procedures [26]. In brief, the 1μg DNaseI treated total RNA was polyadenylated by Poly (A) polymerase at 37°C for 1 h in a 20-μL reaction mixture following the manufacturer’s directions for the Poly (A) Tailing Kit (Ambion). The all RNAs were reverse-transcribed with 200 U SuperScript™ III Reverse Transcriptase (Invitrogen) using poly (T) adapters. Zj5.8S rRNA was used as a control as previously described [27]. Gene-specific primers were listed in S1 Table.

Validation of target cleavage sites by 5’-RLM-RACE

The 5’-RLM-RACE experiments were carried out using the modified RNA ligase-mediated rapid amplification of 5’ cDNAs method as described [28,29], PCRs were carried out on mRNA isolated from Z. jujuba infected with witches’-broom disease using the GeneRacer 5’ primer and the nesting gene-specific primers (S2 Table). Nested PCRs were performed using the GeneRacer 5’ nested primer and the nested gene-specific primers (S2 Table).

Results

Overview of the small RNA sequences

Two small RNA libraries were constructed from the sprig leaves of Z. jujuba wild type (ZZN) and the infected plant (ZZD) with witches’-broom disease (Fig 1). Using the Illumina sequencing technology, a total of 14,171,805 and 11,483,382 raw reads were generated for ZZN and ZZD, respectively. After removing contaminant reads and filtering out the adapter sequences, 13,729,929 and 11,150,259 clean reads with lengths of 18 to 30nt were obtained for ZZN and ZZD, respectively (Table 1). In both libraries, most of total sRNA reads were 18- 24nt in size (Fig 2). The most abundant small RNAs in the both libraries were 21 nt sRNA, which were approximately 18.91% (ZZN) and 17.01% (ZZD) of the total sequence reads in ZZN and ZZD libraries, respectively. Whereas, the abundance of 24-nt sRNAs in ZZD library (9.34%) were higher than in ZZN library (7.78%). The 24-nt sRNAs were mainly comprised of siRNAs, suggesting it may play an important role in the regulation of the response to the phytoplasma infection in plants.

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Fig 1. The Ziziphus jujuba wild type (ZZN) and the infected plant (ZZD) with witches broom disease in the field.

A. ZZN; B. ZZD.

https://doi.org/10.1371/journal.pone.0166099.g001

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Fig 2. The size distribution of the small RNAs in ZZN and ZZD libraries.

https://doi.org/10.1371/journal.pone.0166099.g002

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Table 1. Statistics of small RNA sequences from ZZN and ZZD libraries.

https://doi.org/10.1371/journal.pone.0166099.t001

Identification of conserved miRNAs in Z. jujuba

To identify the conserved miRNAs in Z. jujuba, the unique sequences with at least 10 reads in the both sRNA libraries were mapped to the Z. jujuba genome [30] with no more than 2 mismatches. All the mapped sRNA was aligned with known mature plant miRNAs in miRBase 21.0 by UEA small RNA tools [31] and a maximum of three mismatches were allowed. As a result, we identified 85 unique sequences, belonging to 32 families in the both sRNA libraries generated by Illumina sequencing (Table 2).

Among the 32 identified miRNA families, a total of 18 miRNA families contained several members, and seven families including miR156, miR159, miR160, miR166, miR167, miR319 and miR396, had at least four members; 13 miRNA families, namely miR170, miR172, miR384, miR390, miR397, miR399, miR403, miR477, miR530, miR1515, miR2111, and miR2950 and miR6478, had only one member. Of these families, miR159 was the most abundant, with 142988 (ZZN) and 70170 (ZZD) reads accounting for 44.3% and 40.8% of all conserved miRNAs in both libraries, respectively (Fig 3). The second most abundant miRNA family is miR396, with 57221 (ZZN) and 40723 (ZZD) reads accounting for 17.7% and 23.7% of all conserved miRNAs in both libraries. The third most abundant miRNA family was miR166 and miR167. The other conserved miRNA families showed less abundance and each had less than 0.2% of all conserved miRNA reads. This result is significantly different with other plants, suggesting differential expression of miRNAs in Z. jujuba and indicating there is significant diversity of miRNA expression in different plant species.

Identification of novel miRNAs in Z. jujuba

We used criteria described by Meyers et al [23] to identify novel miRNAs. As a result, we identified 24 novel miRNA sequences with a characteristic stem-loop precursor (Table 3). These novel miRNAs were given names designated as ‘zju-miRn plus number’. Among these novel miRNAs, 14 miRNA had miRNA* sequences, the other 10 had no miRNA* sequences. The length of the predicted novel miRNA precursors varied from 60 to 364 nt, and the average minimum free energy (MFE) value varied from -22 to -111.8 kcal/mol. Most of the novel miRNAs were 21 nt long and had uracil (U) as their first nucleotide. The structures of 24 novel miRNA precursors are shown in S1 Fig. Most of them showed differential expression in both libraries. For instance, the mature miRNA reads varied from 0 to 12561, and the miRNA* reads varied from 0 to 8024. The reads for most of these novel miRNA*s were less than their corresponding mature miRNAs except zju-miRn15* in both libraries. To investigate whether these 24 novel miRNA sequences were conserved across plant species, we used them as query sequences to search against the plant mature miRNAs in miRBase 21.0 by Blastn [32]. The results showed that no perfect matches were found, suggesting that these novel miRNA sequences were not broadly conserved in plants.

Targets of conserved and novel miRNAs in Z. jujuba

To better understand the functions of identified miRNAs, we performed a target search of identified miRNAs against the jujube transcriptome unigenes using psRNATarget with penalty scores of 2.5 [24]. As a result, we identified a total of 150 unigenes from 65,534 assembled Z. jujuba unigenes to be targets of 32 conserved miRNA families (Table 4). Since the direction of unigenes could not be determined, we manually checked the direction of the predicted targets. Finally, we have identified 40 targets of 32 conserved miRNA families with penalty scores of 2.5.

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Table 4. The predicted conserved miRNAs targets of Z. jujuba.

https://doi.org/10.1371/journal.pone.0166099.t004

The putative functions of the predicted target genes were diverse, most of the target genes were transcription factors, disease resistant genes or the key enzyme genes involved in development, disease resistance or metabolism. Most targets of conserved miRNAs in Z. jujuba were the same to those reported miRNAs in other plant species, such as squamosa promoter binding-like protein genes targeted by miR156, transcription factor GAMYB-like gene regulated by miR159, auxin response factor gene regulated by miR160, NAC-domain protein gene, homeobox-leucine zipper protein gene, AP2 domain-containing protein gene, growth regulating factor gene, laccase gene and MYB gene targeted by miR164, miR166, miR172, miR396, miR397, and miR858, respectively (Table 4).

Using the same approach, we predicted 49 targets for 24 novel miRNA genes (Table 5). The number of predicted targets varied from 1 to 4 per miRNA. Many of the predicted targets are associated with metabolism, signal transduction and development. We found that four ubiquitin carboxyl-terminal hydrolase 5-like genes were the targets of miRn7, miRn18, miRn19 and miRn24, respectively, and two serine/threonine protein kinase genes were the targets of miRn5 and miRn14. This phenomenon that one gene can be targeted by more than one miRNAs also have been found in other plant species [27].

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Table 5. The predicted novel miRNAs targets of Z. jujuba.

https://doi.org/10.1371/journal.pone.0166099.t005

Differentially expressed miRNAs in response to witches’-broom phytoplasma

To further identify the functions of miRNAs in Z. jujuba involved in response to phytoplasma infection, we normalized the expression levels of miRNAs and compared the expression levels of the miRNAs in the ZZN and ZZD libraries. As a result, we identified 85 conserved miRNA sequences and 24 novel miRNA sequences, 12 miRNA sequences were up-regulated more than 2 fold in the infected sprig leaves, including miR156a, miR156b, miR156c, miR156d, miR156e, miR156h, miR159e, miR319a, miR395a, miR395b, zju-miRn23 and zju-miRn24. Conversely, 10 miRNA sequences were down- regulated more than 2 fold in the infected plant (S3 Table), including miR159a, miR172, miR2111, miR2950, miR399, miR477, miR858b, zju-miRn2, zju-miRn8 and zju-miRn16. Among them, the most abundant up-regulated miRNAs were miR156a, but the most abundant down- regulated miRNA was miR172. Interestingly, in miR159 family, miR159e was up-regulated in the infected sprig leaves, whereas miR159a was down-regulated. In addition, most conserved and novel miRNAs were detected in both libraries, except zju-miRn23 and zju-miRn24 which were only detected in the ZZD library. This suggests that these two novel miRNAs may be related to response to phytoplasma infection.

To validate the sequencing data and confirm the differential expression of the miRNAs, we performed poly(A) qRT-PCR on 9 miRNAs (miR156a, miR156c, miR156d, miR156h, miR159a, miR172, miR2111, miR399 and miR477) which were up-regulated or down- regulated more than 2 fold in the infected sprig leaves. The results revealed that miR156a, miR156c, miR156h and miR156d were up-regulated in the infected sprig leaves, whereas miR159a, miR172, miR2111, miR399 and miR477 were down- regulated in the infected sprig leaves. The results indicated that these 9 miRNAs had the same expression patterns compared with the sequencing data (Fig 4). These results imply that the phytoplasma responsive miRNAs in the regulation of biological processes involved in witches’-broom diseases.

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Fig 4. qRT-PCR validation of the differentially expressed miRNAs.

Fold changes of the differentially expressed miRNAs are shown. miRNAs were analyzed using the poly(T) adaptor RT-PCR method. The levels in ZZN were arbitrarily set to 1. Error bars represent the standard deviations of three technical PCR replicates.

https://doi.org/10.1371/journal.pone.0166099.g004

Experimental validation of Z. jujuba miRNAs targets

To confirm whether the five differentially expressed miRNAs (miR156, miR159, miR172, miR2111 and miR477) could cleave the predicted targets, we isolated RNAs from the sprig leaves of Z. jujuba wild type (ZZN) and the infected plant (ZZD) with witches’-broom disease, pooled together and performed the modified 5’-RNA ligase-mediated (RLM)-RACE experiment to validate the cleavage sites. The 5’-RACE products revealed that 2 SPL geners and 1 MYB gene are indeed the targets of Z. jujuba miR156 and miR159, respectively (Fig 5). This is consistent with the results from other plants [33, 34], suggesting the functional conservation of miR156 and miR159.

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Fig 5. Experimental validation of the miRNA targets.

Cleavage sites were determined by the modified 5’RNA ligase-mediated RACE. Heavy black lines represent unigenes. miRNA complementary sites with the nucleotide positions of SPL and MYB cDNAs are indicated. Vertical arrows indicate the 5’ termini of miRNA-guided cleavage products, as identified by 5’-RACE, with the frequency of clones shown.

https://doi.org/10.1371/journal.pone.0166099.g005

Discussion

In recent years, research on small RNA function and mechanism has become one of the hot spots in the life science. miRNAs as a new regulator, play important and diverse roles in multiple developmental and physiological processes, antiviral defense, responding to biotic, abiotic stresses etc. It has been indicated that miRNAs play an important role in plant-pathogen interactions, such as miR393, miR319, miR160, miR167, miR390, and miR408 [35]. A growing number of pathogen-responsive miRNAs have been identified [36]. To our best knowledge, the small RNAs of Z. jujuba have not been previously reported. In this study, a total of 85 conserved miRNA unique sequences belonging to 32 miRNA families and 24 novel miRNA unique sequences, including their complementary miRNA* strands were identified in two libraries derived from Z. jujuba wild type (ZZN) uninfected leaves and leaves infected (ZZD) with JWB disease. 40 target genes of 85 conserved miRNAs and 49 target genes of 24 novel miRNAs were predicted using computational analysis, and their functions were putatively assigned. We also identified differentially expressed miRNAs associated with JWB disease between ZZN and ZZD libraries. The targets of miR156 and miR159 were validated using the modified 5’-RACE method.

The regulatory mechanism of miRNAs involved in witches’-broom phytoplasma response is a complicated problem. Currently there are only two reported studies involving witches’-broom phytoplasma responsive miRNAs, which consist of the investigation of Mexian lime infected by Candidatus Phytoplasma aurantifolia [29] and mulberry infected by aster yellows phytoplasma [37]. Both these studies concluded that the differentially expressed miRNAs in healthy and phytoplasma infected plants involved in modulating multiple pathways such as hormonal, nutritional, and stress signaling pathways [29, 37]. They also concluded that these responsive sRNAs may work cooperatively in the response to phytoplasma infection and be responsible for some symptoms observed in the infected plants [38]. Compared to these two studies, among the 85 conserved witches’-broom phytoplasma responsive miRNAs identified in Z. jujuba, only 3 miRNA families, including miR156, miR172 and miR477, were also differentially expressed in Candidatus phytoplasma aurantifolia infected Mexican lime and aster yellows phytoplasma infected in mulberry. Therefore, the expression patterns of miRNAs responsive to the phytoplasma infection were diverse in different plants.

In this study, among the differentially expressed miRNAs, miR156 was the most up-regulated differentially miRNAs, suggesting that miR156 may play an important role in response to JWB. In both libraries, all the up-regulated miRNA sequences with a greater than 3.5 fold change were members of miR156 family. The SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL) genes were the targets of miR156. Our results showed that miR156 was up-regulated in the infected sprig leaves, meanwhile miR172 was down-regulated. A previous study showed that the overexpression of miR156b in Arabidopsis increased axillary branching [39], which is similar to the symptom of the witches’-broom disease [3840]. Furthermore, APETALA2 was regulated by miR172 through direct RNA cleavage or translational repression [36, 41]. In this study, we found the expression levels of miR172 was down-regulated, suggesting that the expression levels of APETALA2 gene was increased, which takes part in regulating flowering time and floral organ identity [41]. In addition, some SPL genes, such as AtSPL9, positively regulate the expression of miR172. This forms the miR156-AtSPL9-miR172 regulatory pathway [42, 43]. Therefore, the miR156-SPL9-miR172 regulatory pathway may be also conserved in response to phytoplasma infection. The expression changes of miR156 and miR172 might leads to the symptoms of the JWB diseases such as development of green leaf-like structures instead of flowers and sterility of flowers. MiR159 is the most abundant miRNAs in both libraries, which targets the mRNAs of MYB transcription factors. The expression level of miR159 was down-regulated in the ZZD library. It has been suggested that the overexpression of MYB33 leads to rolled leaf and shorter petioles [44, 45]. Therefore, our results suggest that miR156, miR172 and miR159 play important roles in the responses to JWB diseases, which will provide the insight to elusive the molecular mechanisms of witches’-broom disease in Z. jujuba.

Supporting Information

S1 Fig. The predicted hairpin structures of all the novel miRNAs.

https://doi.org/10.1371/journal.pone.0166099.s001

(PDF)

S2 Table. Primers used for validation of the miRNA cleavage of targets.

https://doi.org/10.1371/journal.pone.0166099.s003

(DOC)

S3 Table. The expression profiling of miRNAs between ZZN and ZZD libraries.

https://doi.org/10.1371/journal.pone.0166099.s004

(DOC)

Acknowledgments

We thank Iain Wilson for his critical reading of the manuscript. The work was supported by the National Key Research and Development Program of China (grant number 2016YFD0600104) and the Basic Research Fund of RIF (grant number RIF2014-01).

Author Contributions

  1. Conceptualization: FS SL DQ.
  2. Data curation: FS DQ.
  3. Formal analysis: FS.
  4. Funding acquisition: SL DQ.
  5. Investigation: FS DQ HL.
  6. Methodology: FS QZ HL.
  7. Project administration: SL DQ.
  8. Resources: SL DQ QZ.
  9. Software: FS.
  10. Supervision: SL DQ.
  11. Validation: FS.
  12. Visualization: FS.
  13. Writing – original draft: FS.
  14. Writing – review & editing: FS SL DQ.

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