Identification of miRNAs and their targets in tea (Camellia sinensis)#

Identification of miRNAs and their targets in tea ( Camellia sinensis ) # # first-author corresp ‡Corresponding Author ‡Corresponding Author †E-mail:ypluo@zju.edu.cn †E-mail:ypluo@zju.edu.cn ypluo@zju.edu.cn Institute of Tea Science, Zhejiang University, Hangzhou 310058, China Institute of Tea Science, Zhejiang University, Hangzhou 310058, China MicroRNAs (miRNAs) are endogenous small RNAs playing a crucial role in plant growth and development, as well as stress responses. Among them, some are highly evolutionally conserved in the plant kingdom, this provide a powerful strategy for identifying miRNAs in a new species. Tea ( Camellia sinensis ) is one of the most important commercial beverage crops in the world, but only a limited number of miRNAs have been identified. In the present study, a total of 14 new C. sinensis miRNAs were identified by expressed sequence tag (EST) analysis from 47 452 available C. sinensis ESTs. These miRNAs potentially target 51 mRNAs, which can act as transcription factors, and participate in stress response, transmembrane transport, and signal transduction. Analysis of gene ontology (GO), based on these targets, suggested that 37 biological processes were involved, such as oxidation-reduction process, stress response, and transport. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis inferred that the identified miRNAs took part in 13 metabolic networks. Our study will help further understanding of the essential roles of miRNAs in C. sinensis growth and development, and stress response. MicroRNA (miRNA) Camellia sinensis Tea Gene ontology Pathway Introduction 1 MicroRNAs (miRNAs) are a class of endogenous non-coding small RNAs (about 21 nucleotides (nt)), which negatively regulate the expression of genes by targeting mRNA for cleavage or translational repression in a sequence-complementary dependent manner (Bartel, 2004 2004 ; He and Hannon, 2004 2004 ). They play crucial roles in plant growth and development, including flower development (Chen, 2004 2004 ), leaf organ morphogenesis and polarity (Palatnik et al., 2003 2003 ; Juarez et al., 2004 2004 ; Mallory et al., 2004 2004 ), root development (Guo et al., 2005 2005 ; Williams et al., 2005 2005 ), and fruit ripening (Moxon et al., 2008 2008 ; Carra et al., 2009 2009 ). Additionally, plant miRNAs also respond to drought, cold, salt, and other abiotic stress, as well as biotic stress (Sunkar et al., 2012 2012 ). The first plant miRNA was discovered in Arabidopsis in 2002 by small RNAs cloning (Reinhart et al., 2002 2002 ). Subsequently, a large number of plant miRNAs were identified in a wide range of plant species. Currently, a total of 5 940 plant miRNAs from 67 species are published in the miRBase database ( http://www.mirbase.org/ http://www.mirbase.org/ , Release 19: August 2012) (Kozomara and Griffiths-Jones, 2011 2011 ). miRNA-related research is steadily growing, with researchers identifying miRNAs and studying their functions using a series of computational tools and/or experimental methods including small RNAs cloning, high-throughput sequencing, and degradome sequencing. Comparison of miRNAs in different plant species by expressed sequence tag (EST) analysis had shown that some miRNAs were highly evolutionary conserved among species (Zhang et al., 2006a 2006a ); this provided a powerful strategy for identifying miRNAs in a new species. Identification of miRNAs using EST analysis has two significant advantages (Frazier and Zhang, 2011 2011 ): (1) There is no specialized software required and it can be used to identify miRNAs in any species if they are previously registered EST sequences; (2) Since EST are derived from transcribed sequences, EST analysis also provided direct evidence for miRNA expression. In view of these advantages, EST analysis had been used to identify conserved miRNAs in Brassica napus (Xie et al., 2007 2007 ), Medicago truncatula (Zhou et al., 2008 2008 ), Lycopersicon esculentum (Yin et al., 2008 2008 ), Glycine max (Zhang et al., 2008 2008 ), citrus (Song et al., 2010 2010 ), Nicotiana tabacum (Frazier et al., 2010 2010 ), Panicum virgatum (Xie et al., 2010 2010 ), Solanum tuberosum (Xie et al., 2011 2011 ), Malus domestica (Yu et al., 2011 2011 ), strawberry (Dong et al., 2012 2012 ), etc. Tea ( Camellia sinensis ) is an important commercial beverage crop grown in different agro-climatic zones in the world. Because of its extensive secondary metabolites in leaves, including theanine, polyphenols, caffeine, and volatile oils, the tea beverage possesses many health benefits to humans (Rogers et al., 2008 2008 ; Prabu and Mandal, 2010 2010 ; Shi et al., 2011 2011 ). In addition to its health benefits and economic value, C. sinensis is also a wonderful source of experimental material to expound gene expression and regulation because of the availability of a mass of ESTs. Though numbers of miRNAs were identified from a wide range of species, there was no registered C. sinensis miRNA in miRBase ( http://www.mirbase.org http://www.mirbase.org , Release 19: August 2012). Recently, Das and Mondal ( 2010 2010 ) and Prabu and Mandal ( 2010 2010 ) identified several miRNAs from C. sinensis using computational methods, and Mohanpuria and Yadav ( 2012 2012 ) discovered six tea-specific miRNAs using a direct cloning approach. However, compared to Arabidopsis (703) or rice (708) ( http://www.mirbase.org/ http://www.mirbase.org/ , Release 19: August 2012), more miRNA genes still remain to be discovered in C. sinensis . Furthermore, little attention has been focused on the function of C. sinensis miRNAs. In this study, we aim to identify miRNAs and their potential targets in C. sinensis and study their functions. To achieve this goal, EST analysis was performed to discover miRNAs and potential targets in C. sinensis , and Blast2GO (Conesa et al., 2005 2005 ; Conesa and Götz, 2008 2008 ) was employed to further understand their functions. Methods 1 Sequence sources 2 The test sequences were obtained from the miRBase database and the National Center for Biotechnology Information (NCBI). Currently, a total of 5 940 known plant miRNAs were available in the miRBase database, and 47 452 ESTs and 154 468 mRNAs sequences were available for C. sinensis in the NCBI by October 2012. To identify more potential C. sinensis miRNAs, all of these sequences were downloaded for identifying miRNAs. Identification of potential miRNAs in C. sinensis using EST analysis 2 The prediction of potential miRNA adopted a previously reported method (Zhang et al., 2005 2005 ; Frazier et al., 2010 2010 ). There were two crucial filter conditions in EST analysis: one is the conservation of mature miRNA sequences, another is the secondary structure of the pre-miRNAs (Zhang et al., 2008 2008 ). Briefly, the mature sequences of all known plant miRNAs were used as a query for homologous search against C. sinensis EST database using BLAST+2.2.25 program (Altschul et al., 1997 1997 ). The parameters used in the BLASTn were adjusted as follows: E value cutoff of 0.01; the word size was set at seven; and all other parameters used default settings. After removing the repeated ones, the rest of the ESTs with no more than 3 nt mismatches were used for additional analysis of secondary structure, based on the following criteria (Frazier et al., 2010 2010 ) using MFOLD V3.2 (Zuker, 2003 2003 ) ( http://mfold.rit.albany.edu/?q=mfold http://mfold.rit.albany.edu/?q=mfold ): (1) pre-miRNA could fold into a typical hairpin secondary structure and the mature miRNA was located in one stem; (2) the length of the pre-miRNA was no less than 50 nt; (3) pre-miRNA had a high minimal folding free energy (MFE) and MFE index (MFEI), which was calculated by $${\rm{MFEI}} = {\rm{MFE}} \times {\rm{1}}00/\left[ {{\rm{length}} \times \left( {{\rm{G}} + {\rm{C}}} \right)\% } \right]$$ , where length is the length of RNA sequence and MFE is the negative folding free energy (−Δ G ) (Zhang et al., 2006b 2006b ); (4) the maximum number of nucleotides mismatches between the mature miRNA and its opposite miRNA * sequnence was six; and, (5) no loops or breaks in the miRNA/miRNA * duplex was allowed. Prediction of miRNA targets in C. sinensis 2 In brief, we used the potential C. sinensis miRNAs blast against the C. sinensis mRNA database to search sequences conforming to the following standards as the C. sinensis candidate target gene: (1) the maximum number of mismatched nucleotides between the mature miRNA and its potential target genes was four; (2) the maximum number of mismatched nucleotides at positions 1–9 was one; (3) no mismatches were allowed at positions 10–11; (4) more than two continuous mismatches at any position were not allowed (Xie et al., 2010 2010 ). Analysis of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway 2 To better understand the function of C. sinensis miRNAs, Blast2GO (Conesa et al., 2005 2005 ; Conesa and Götz, 2008 2008 ) was employed to investigate the predicted target genes. First, the identified miRNA targeted mRNAs were used to BLASTX against NR database with an E value of 10 −25 . Second, the best hits identified by BLASTX were further searched against the GO and KEGG databases using default settings. Results and discussion 1 Potential miRNAs in C. sinensis 2 In this study, we identified 14 potential miRNAs from a total of 47 452 available C. sinensis ESTs by homologous search. This indicates that about 0.0295% of C. sinensis ESTs contain potential miRNAs. The ratio is as high as the previously reported about 0.0277% for switchgrass (Xie et al., 2010 2010 ). The 14 new C. sinensis miRNAs belong to nine families, of which miR171, miR2911, miR5021, miR5368, and miR6483 have two members, while miR156, miR397, miR399, and miR2863 have only one member. Mature miRNAs have been observed to be located on the arm of pre-miRNA, but the located positions were found either on the 5′ arm of the stem (50%) or on the 3′ arm (50%). The length of mature miRNAs varies from 18 to 22 nt and 42.86% (6 out of 14) of them are 21 nt in length. The length of C. sinensis pre-miRNAs also varies from 85 to 201 nt with an average of (122.79±38.13) nt (Table 1 1 ). Fig. 1 1 showed predicted pre-miRNAs of miR171a in C. sinensis , and others were given in Data S1 S1 . Lowercase letters in mature sequence mean mismatch SP: start point; EP: end point; ME: match extent; PL: pre-miRNA length; MFE: minimal folding free energy; MFEI: MFE index New miRNA Query miRNA GenBank acc. No. Tissue type Arm SP EP ME Mature sequence * * E value PL A+U (%) MFE (kcal/mol) MFEI miR156 aly-miR157a-5p HS396956.1 Leaf 5′ 212 232 20/21 UUGACAGAAGAUAGAGAGCAu 1.00E−04 100 54.00 45.80 1.00 miR171a ptc-miR171k FS948108.1 Roots 3′ 273 293 20/21 GGAUUGAGCCGCGCCAAUAUu 1.00E−04 100 65.00 39.20 1.12 miR171b ptc-miR171k FS948109.1 Roots 5′ 163 143 20/21 GGAUUGAGCCGCGCCAAUAUu 1.00E−04 97 63.92 40.40 1.15 miR397 osa-miR397b CV699725.1 Leaf 5′ 99 79 21/21 UUAUUGAGUGCAGCGUUGAUG 3.00E−05 126 59.52 39.20 0.77 miR399 osa-miR399j FS958856.1 Young leaves 3′ 109 129 20/21 UGCCAAaGGAGAGUUGCCCUA 8.00E−03 103 51.46 52.80 1.06 miR2863 osa-miR2863a FS950435.1 Roots 5’ 37 57 18/21 UauaUAUUGUUGAAAUGGCUU 8.00E−03 85 64.71 21.50 0.72 miR2911a nta-miR2911 JK476023.1 Leaf 3′ 364 383 20/20 GGCCGGGGGACGGACUGGGA 1.00E−04 97 22.68 65.40 0.87 miR2911b nta-miR2911 FS953337.1 Shoot stems 3′ 177 196 20/20 GGCCGGGGGACGGACUGGGA 1.00E−04 97 23.71 69.20 0.94 miR5021a ath-miR5021 GW690847.1 Bud 3′ 256 237 18/20 aGAGAAGAAGAAGAAGAAAg 2.00E−03 195 55.90 71.90 0.84 miR5021b ath-miR5021 GE651759.1 Tender root 5′ 73 92 18/20 aGAGAAGAAGAAGAAGAAAg 2.00E−03 201 56.22 72.20 0.82 miR5368a gma-miR5368 GE653011.1 Tender root 3' 505 523 19/19 GGACAGUCUCAGGUAGACA 4.00E-04 163 42.33 76.10 0.81 miR5368b gma-miR5368 FS945766.1 Mature leaves 3′ 196 214 19/19 GGACAGUCUCAGGUAGACA 4.00E-04 144 42.36 68.50 0.83 miR6483a hbr-miR6483 HS398296.1 Leaf 5′ 253 232 21/22 UAUUGUAGAAAUUUUCgGGAUC 2.00E−03 101 62.38 29.80 0.78 miR6483b hbr-miR6483 JK714410.1 Leaf 5′ 303 282 21/22 UAUUGUAGAAAUUUUCgGGAUC 2.00E−03 110 63.64 30.00 0.75 MFE is an important parameter for RNA folding into their secondary structures. Usually, the stability of the secondary structure of an RNA sequence increases with the reduction of the MFE. The MFEI was a sufficient criterion for distinguishing miRNAs from other RNAs. Previous research also suggested that it is more likely to be a potential miRNA if the pre-miRNA met the following criteria: MFEI > 0.85 (Zhang et al., 2006b 2006b ). All predicted C. sinensis pre-miRNAs have a typical stem-loop secondary structure, pairing diversity depends on the length of precursor, and we only select the most stable one as the candidate pre-miRNA. Namely, they have a higher MFE, as well as MFEI. The MFE of new identification C. sinensis miRNAs ranges from 21.50 to 76.10 kcal/mol (1 kcal=4.184 kJ) with an average of (51.57±18.68) kcal/mol and the MFEI ranges from 0.72 to 1.15 with an average of 0.89±0.14 (Table 1 1 ). Furthermore, the expression of C. sinensis miRNAs, according to the tissue type reported for each EST in the NCBI database, may be observed in leaf, root, stem, and bud (Table 1 1 ). C. sinensis miRNA targets and their functions 2 Increasing evidences have demonstrated that most plant miRNAs bind to their target mRNA sequences with perfect or near-perfect sequence complementarity (Wang et al., 2004 2004 ; Schwab et al., 2005 2005 ). This provides a powerful strategy for discovering potential miRNA targets by comparing and aligning miRNAs with mRNAs sequences. Here, we performed more stringent criterion (Schwab et al., 2005 2005 ) to identify potential C. sinensis targets. After a set of screening criteria as described in the method, we achieved 51 target genes. Among the 51 predicted targets, 17 mRNAs encoded transcriptional factors, 14 mRNAs were stress responsive genes, and others were involved in transmembrane transport, signal transduction and transcription regulation. Unfortunately, 15 out of 51 targets’ function remain unknown (Table 2 2 ). The results imply that miRNAs may play an important role in C. sinensis growth and development, as well as environmental stress. TF: transcription factor; SR: stress response; ST: signal transduction;TMT: transmembrane transport; TR: transcriptional regulation miRNA family Accession ID for targets Target description Function miR156 KA284177, KA295488, HP757423, KA282627, KA285159, HP745756, HP751450, KA284930, KA293068, GAAC01043871, GAAC01052380 Squamosa promoter-binding-like protein TF 2 miR171 HP735040, HP713619, GAAC01007557 Gras family transcription factor TF HP757272, KA297400, GAAC01010861 Scarecrow-like protein TF 2 miR397 HP737460 Laccase precursor SR HP763272, GAAC01026665, GAAC01009301, KA285173 Laccase SR miR399 HP729908 Probable ubiquitin-conjugating enzyme e2 24-like SR 2 miR2911 KA283566 Cytochrome p450 like_tbp SR KA280075, KA285244, KA300874, KA279444, KA281442, KA287941, KA296981, KA300579, KA298382 Hypothetical protein MTR Unknown 9 miR5021 KA279939, KA291019, KA303064 60s ribosomal protein Unknown HP701326 Transcription activator glk1-like TR KA281241 Conserved hypothetical protein Unknown GAAC01052403 Probable LRR receptor-like serine threonine-protein kinase at1g14390 ST GAAC01011182 PREDICTED: uncharacterized protein LOC100266927 Unknown HP701293 Uncharacterized F-box/LRR-repeat protein C02F5.7-like Unknown HP748043 Monocopper oxidase-like protein sku5-like SR KA281010 Serine/threonine-protein phosphatase PP2A catalytic subunit ST GAAC01045495 Erd6-like transporter TMT 2 miR5368 KA283870 Metallocarboxypeptidase inhibitor SR KA279481, KA283770, KA303168, KA303031, GAAC01046756 Cell wall-associated hydrolase, partial SR miR6483 HP736555 Envelope membrane protein TMT Many miRNA targets identified by bioinformatics and/or experimental methods were transcription factors that help control plant growth and development. Here, we also found this type of targets. SQUAMOSA promoter binding protein-like (SPL) transcription factors, a class targets of miR156, play an important role in controlling flowering time, regulating plant transition from vegetative phase to reproductive phase, while overexpression of miR156 delays flowering and extends the vegetative stage (Wang et al., 2009 2009 ; Wu et al., 2009 2009 ). Furthermore, SPL is also involved in leaf development (Chen et al., 2010 2010 ) and anthocyanin biosynthesis (Gou et al., 2011 2011 ). SCARECROW-LIKE (SCL) transcription factor, miR171 target gene, was reported to act as a positive regulator in root development by integrating and maintaining a functional gibberellic acid (GA) pathway (Heo et al., 2011 2011 ). Recent studies have shown that miRNAs are also involved in plant adaptation to environmental stresses, such as cold (Zhang et al., 2009 2009 ; Thiebaut et al., 2012 2012 ), salt (Ding et al., 2009 2009 ), drought (Li et al., 2011 2011 ), and nutrient deficiency (Sunkar et al., 2007 2007 ; Zhao et al., 2012 2012 ). Interestingly, we identified 14 potential targets of miR397, miR399, miR2911, miR5021, and miR5368 that were responses to stress. Further analysis of GO suggested that miR397 and miR399 play essential roles in copper ion and phosphate starvation. To further understand the function of C. sinensis miRNAs, the predicted target mRNAs were subjected to analysis by GO and KEGG, a database for analyzing gene functions systematically (Kanehisa and Goto, 2000 2000 ), using Blast2GO. The result suggested that C. sinensis miRNAs were involved in 37 biological processes. Among them, 9 targets of miR397, miR2911, and miR5021 took part in oxidation-reduction process, 3 targets of miR397 and miR399 responded to stress, and others were related to regulation of transcription, transport, growth and development, metabolism and translation (Table 3 3 ). Pathway enrichment analysis, based on the KEGG database, demonstrates that the identified miRNAs participated in 13 metabolism networks. These networks were involved in caffeine metabolism, ascorbate and aldarate metabolism, fatty acid metabolism, T cell receptor signaling pathway, and other secondary metabolites process (Table 4 4 ). Interestingly, miR2911 was demonstrated to participate in the caffeine metabolism. Obviously, our study will help further understanding of the important regulation roles of miRNAs in C. sinensis growth and development, stress response, and likewise in research and development of low-caffeine tea. miRNA Biological process Accession ID for targets GO 397, 2911, 5021 Oxidation-reduction process HP748043; GAAC01045495; KA287941; KA283566; KA285173; GAAC01009301; HP763272; HP737460; GAAC01026665 GO:0055114 156, 171 Regulation of transcription KA284177; GAAC01007557; KA295488; KA282627; KA285159; HP735040; HP713619; HP757272; KA297400 GO:0006351; GO:0006355 399, 5021, 6483 Transport GAAC01045495; HP736555; HP729908 GO:0006817; GO:0015992; GO:0055085; GO:0008643 397, 399 Stress response HP729908; HP737460; HP729908 GO:0016036; GO:0046688; GO:0055062 397 Metabolic GAAC01009301; GAAC01026665; KA285173; HP763272; HP737460 GO:0046274; GO:0010413; GO:0009809; GO:0045492 397 Growth and development HP737460; HP763272; GAAC01026665 GO:0010228; GO:0009834; GO:0009832 5021 Translation KA279939; KA291019 GO:0006412 miRNA Accession ID for targets Target description Enzyme Pathway 397 HP737460 Laccase precursor EC:1.10.3.3 Ascorbate and aldarate metabolism GAAC01009301 Laccase EC:1.10.3.3 2 2911 KA283566 2 Cytochrome p450 like_tbp 2 EC:1.14.14.1 2 Fatty acid metabolism, caffeine metabolism, aminobenzoate de-gradation, metabolism of xeno-biotics by cytochrome P450, drug metabolism-cytochrome P450, drug metabolism-other enzymes, arachidonic acid metabolism, linoleic acid metabolism, tryptophan metabolism, steroid hormone biosynthesis, retinol metabolism KA287941 5021 KA281010 Serine/threonine-protein phosphatase PP2A catalytic subunit EC:3.1.3.16 T cell receptor signaling pathway Conclusions 1 In this study, we identified 14 new C. sinensis miRNAs by EST analysis, which belong to 9 families. 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This article does not contain any studies with human or animal subjects performed by any of the authors. 10.1631/jzus.B1300006 , 2013-01-04 2013-09-24 2013-04-01 2022-01-05 Copyright © Zhejiang University and Springer-Verlag Berlin Heidelberg 2013 2013 Journal of Zhejiang University-SCIENCE B (Biomedicine and Biotechnology) 10 14