Figures
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.
Citation: Shao F, Zhang Q, Liu H, Lu S, Qiu D (2016) Genome-Wide Identification and Analysis of MicroRNAs Involved in Witches’-Broom Phytoplasma Response in Ziziphus jujuba. PLoS ONE 11(11): e0166099. https://doi.org/10.1371/journal.pone.0166099
Editor: Turgay Unver, Dokuz Eylul Universitesi, TURKEY
Received: August 23, 2016; Accepted: October 21, 2016; Published: November 8, 2016
Copyright: © 2016 Shao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: 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).
Competing interests: The authors have declared that no competing interests exist.
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 [1–3]. 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 [16–20], 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.
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.
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].
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.
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.
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.
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.
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 [38–40]. 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
- Conceptualization: FS SL DQ.
- Data curation: FS DQ.
- Formal analysis: FS.
- Funding acquisition: SL DQ.
- Investigation: FS DQ HL.
- Methodology: FS QZ HL.
- Project administration: SL DQ.
- Resources: SL DQ QZ.
- Software: FS.
- Supervision: SL DQ.
- Validation: FS.
- Visualization: FS.
- Writing – original draft: FS.
- Writing – review & editing: FS SL DQ.
References
- 1. Li JW, Fan LP, Ding SD, Ding XL. Nutritional composition of five cultivars of Chinese jujube. Food Chem. 2007; 103: 454–460.
- 2. Zhang H, Jiang L, Ye S, Ye Y, Ren F. Systematic evaluation of antioxidantcapacities of the ethanolic extract of different tissues of jujube (Ziziphus jujuba Mill.) from China. Food Chem Toxicol. 2010; 48: 1461–1465. pmid:20230870
- 3. Fang S, Wang Z, Hu X. Hot air drying of whole fruit Chinese jujube (Zizyphus jujuba Miller): thin-layer mathematical modeling. Int J Food Sci Technol. 2009; 44: 1818–1824.
- 4. Lee JT. Investigation on jujube diseases and their severities of incidence. Res Rept RDA. 1988; 31: 155–161.
- 5. Doi Y, Teranaka M, Yora K, Asuyama H. Mycoplasma or PLT group-like microorganisms found in the phloem elements of plants infected with mulberry dwarf, potato witches’ broom, aster yellows, or Paulownia witches’ broom. Ann Phytopathol Soc Jpn. 1967; 33: 259–266.
- 6. Namba S. Molecular biological studies on phytoplasmas. J Gen Plant Pathol. 2002; 68: 257–259.
- 7. Liu XG, Liu MJ, Ning Q, Liu GN. Reverse-cleft in vitro micrografting of Ziziphus jujuba Mill Infected with jujube witches’ broom (JWB). Plant Cell Tissue Organ Cult. 2012; 108: 339e44.
- 8. Strauss E. Phytoplasma research begins to bloom. Science. 2009; 325: 388e90.
- 9. Streten C, Gibb KS. Phytoplasma diseases in sub-tropical and tropical Australia. Australas Plant Pathol. 2006; 35: 129e46.
- 10. Monavarfeshani A, Mirzaei M, Sarhadi E, Amirkhani A, Khayam NM, Haynes PA, et al. Shotgun Proteomic Analysis of the Mexican lime tree infected with “Candidatus Phytoplasma” aurantifolia. J Proteome Res. 2013; 12: 785–795. pmid:23244174
- 11. Zamharir M, Mardi M, Alavi S, Hasanzadeh N, Nekouei M, Zamanizadeh HR,et al. Identification of genes differentially expressed during interaction of Mexican lime tree infected with ‘‘Candidatus Phytoplasma aurantifolia”. BMC Microbiol. 2011; 11: 1. pmid:21194490
- 12. Blumwald E, Aharon GS, CH Lam B. Early signal transduction pathways in plant–pathogen interactions. Trends Plant Sci. 1998; 3: 342–346.
- 13. Christensen NM, Axelsen KB, Nicolaisen M, Schulz A. Phytoplasmas and their interactions with hosts. Trends Plant Sci. 2005; 10: 526–535. pmid:16226054
- 14. Brodersen P, Voinnet O. The diversity of RNA silencing pathways in plants. Trends Genet. 2006; 22: 268–280. pmid:16567016
- 15. Peters L, Meister G. Argonaute proteins: mediators of RNA silencing. Mol Cell. 2007; 26: 611–623. pmid:17560368
- 16. Jung HY, Sawayanagi T, Kakizawa S, Nishigawa H, Wei W, Oshima K, et al. ‘Candidatus Phytoplasma ziziphi’, a novel phytoplasma taxon associated with jujube witches’-broom disease. Int J Syst Evol Microbiol. 2003; 53: 1037–1041. pmid:12892123
- 17. Chen L, Ren Y, Zhang Y, Xu J, Zhang Z, Wang Y. Genome-wide profiling of novel and conserved Populus microRNAs involved in pathogen stress response by deep sequencing. Planta. 2012; 235: 873–883. pmid:22101925
- 18. Sunkar R, Li YF, Jagadeeswaran G. Functions of microRNAs in plant stress responses. Trends Plant Sci. 2012; 17: 196–203. pmid:22365280
- 19. Zhang W, Gao S, Zhou X, Chellappan P, Chen Z, Zhou X, et al. Bacteria-responsive microRNAs regulate plant innate immunity by modulating plant hormone networks. Plant Mol. Biol. 2011; 75: 93–105. pmid:21153682
- 20. Inal B, Türktaş M, Eren H, Ilhan E, Okay S, Atak M, Erayman M, Unver T. Genome-wide fungal stress responsive miRNA expression in wheat. Planta. 2014; 240(6): 1287–1298. pmid:25156489
- 21. Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ. miRBase: tools for microRNA genomics. Nucleic Acids Res. 2008; 36: 154–158.
- 22. Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 2003; 31: 3406–3415. pmid:12824337
- 23. Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, et al. Criteria for annotation of plant microRNAs. Plant Cell. 2008; 20: 3186–3190. pmid:19074682
- 24. Dai X, Zhuang Z, Zhao P. Computational analysis of miRNA targets in plants: current status and challenges. Brief Bioinform. 2011; 12: 115–121. pmid:20858738
- 25. Wilke A, Harrison T, Wilkening J, Field D, Glass EM, Kyrpides N, et al. The M5nr: a novel non-redundant database containing protein sequences and annotations from multiple sources and associated tools. BMC Bioinformatics. 2012; 13:141. pmid:22720753
- 26. Shi R, Chiang V. Facile means for quantifying microRNA expression by real-time PCR. Biotechniques. 2005; 39: 519–525. pmid:16235564
- 27. Wu B, Wang M, Ma Y, Yuan L, Lu S. High-throughput sequencing and characterization of the small RNA transcriptome reveal features of novel and conserved microRNAs in Panax ginseng. PLoS One. 2012; 7: e44385. pmid:22962612
- 28. Shao F, Lu S. Genome-wide identification, molecular cloning, expression profiling and posttranscriptional regulation analysis of the Argonaute gene family in Salvia miltiorrhiza, an emerging model medicinal plant. BMC Genomics. 2013; 14: 512. pmid:23889895
- 29. Ehya F, Monavarfeshani A, Mohseni Fard E, Karimi Farsad L, Khayam Nekouei M, Mardi M, et al. Phytoplasma-responsive microRNAs modulate hormonal, nutritional, and stress signalling pathways in Mexican lime trees. PLoS One. 2013; 8: e66372. pmid:23824690
- 30. Liu MJ, Zhao J, Cai QL, Lin GC, Wang JR. The complex jujube genome provides insights into fruit tree biology. Nat Commun. 2014; 5: 5315. pmid:25350882
- 31. Stocks MB, Moxon S, Mapleson D, Woolfenden HC, Mohorianu I, Folkes L, et al. The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets. Bioinformatics. 2012; 28: 2059–2061. pmid:22628521
- 32. Altschul S, Madden T, Schaffer A, Zhang J, Zhang Z, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997; 25: 3389–3402. pmid:9254694
- 33. Zhang L, Wu B, Zhao D, Li C, Shao F, Lu S. Genome-wide analysis and molecular dissection of the SPL gene family in Salvia miltiorrhiza. J Integr Plant Biol. 2013; 56: 38–50. pmid:24112769
- 34. Chen X. APETALA2 in Arabidopsis Flower Development. Science. 2004; 303: 2022–2025. pmid:12893888
- 35. Sunkar R, Li YF, Jagadeeswaran G. Functions of microRNAs in plant stress responses. Trends Plant Sci. 2012; 17(4): 196–203. pmid:22365280
- 36. Zhang W, Gao S, Zhou X, Chellappan P, Chen Z, Zhou X, Zhang X, Fromuth N, Coutino G, Coffey M, Jin H. Bacteria-responsive microRNAs regulate plant innate immunity by modulating plant hormone networks. Plant Mol. Biol. 2011; 75(1–2): 93–105. pmid:21153682
- 37. Gai YP, Li YQ, Guo FY, Yuan CZ, Mo YY, Zhang HL, et al. Analysis of phytoplasma-responsive sRNAs provide insight into the pathogenic mechanisms of mulberryyellow dwarf disease. Sci Rep. 2014; 4: 5378. pmid:24946736
- 38. Wei S, Gruber MY, Yu B, Gao MJ, Khachatourians GG, Hegedus DD, et al. Arabidopsis mutant sk156 reveals complex regulation of SPL15 in a miR156-controlled gene network. BMC Plant Biol. 2012;12: 169. pmid:22989211
- 39. Wei S, Yu B, Gruber MY, Khachatourians GG, Hegedus DD, Hannoufa A. Enhanced Seed Carotenoid Levels and Branching in Transgenic Brassica napus Expressing the Arabidopsis miR156b Gene. J Agric Food Chem. 2010; 58: 9572–9578. pmid:20707346
- 40. Schwab R, Palatnik JF, Riester M, Schommer C, Schmid M, Weigel D, Specific Effects of MicroRNAs on the Plant Transcriptome. Dev Cell. 2005;8: 517–527. pmid:15809034
- 41. Zhu QH, Helliwell CA. Regulation of flowering time and floral patterning by miR172. J Exp Bot. 2011; 62: 487–495. pmid:20952628
- 42. Levy A, Szwerdszarf D, Abu-Abied M, Mordehaev I, Yaniv Y, Riov J, et al. Profiling microRNAs in Eucalyptus grandis reveals no mutual relationship between alterations in miR156 and miR172 expression and adventitious root induction during development. BMC Genomics. 2014; 15: 524. pmid:24965948
- 43. Huijser P, Schmid M. The control of developmental phase transitions in plants. Development. 2011; 138: 4117–4129. pmid:21896627
- 44. Millar AA, Gubler F. The Arabidopsis CAMYB-like genes, MYB33 and MYB65 are micro RNA-regulated genes that redundantly facilitate anther development. Plant Cell. 2005; 17: 705–721. pmid:15722475
- 45. Rubio-Somoza I, Weigel D. Coordination of Flower Maturation by a Regulatory Circuit of Three MicroRNAs. PLoS Genet. 2013; 9: e1003374. pmid:23555288