- Research article
- Open Access
Diversity, expression and mRNA targeting abilities of Argonaute-targeting miRNAs among selected vascular plants
© Jagtap and Shivaprasad; licensee BioMed Central Ltd. 2014
Received: 25 August 2014
Accepted: 12 November 2014
Published: 2 December 2014
Micro (mi)RNAs are important regulators of plant development. Across plant lineages, Dicer-like 1 (DCL1) proteins process long ds-like structures to produce micro (mi) RNA duplexes in a stepwise manner. These miRNAs are incorporated into Argonaute (AGO) proteins and influence expression of RNAs that have sequence complementarity with miRNAs. Expression levels of AGOs are greatly regulated by plants in order to minimize unwarranted perturbations using miRNAs to target mRNAs coding for AGOs. AGOs may also have high promoter specificity-sometimes expression of AGO can be limited to just a few cells in a plant. Viral pathogens utilize various means to counter antiviral roles of AGOs including hijacking the host encoded miRNAs to target AGOs. Two host encoded miRNAs namely miR168 and miR403 that target AGOs have been described in the model plant Arabidopsis and such a mechanism is thought to be well conserved across plants because AGO sequences are well conserved.
We show that the interaction between AGO mRNAs and miRNAs is species-specific due to the diversity in sequences of two miRNAs that target AGOs, sequence diversity among corresponding target regions in AGO mRNAs and variable expression levels of these miRNAs among vascular plants. We used miRNA sequences from 68 plant species representing 31 plant families for this analysis. Sequences of miR168 and miR403 are not conserved among plant lineages, but surprisingly they differ drastically in their sequence diversity and expression levels even among closely related plants. Variation in miR168 expression among plants correlates well with secondary structures/length of loop sequences of their precursors.
Our data indicates a complex AGO targeting interaction among plant lineages due to miRNA sequence diversity and sequences of miRNA targeting regions among AGO mRNAs, thus leading to the assumption that the perturbations by viruses that use host miRNAs to target antiviral AGOs can only be species-specific. We also show that rapid evolution and likely loss of expression of miR168 isoforms in tobacco is related to the insertion of MITE-like transposons between miRNA and miRNA* sequences, a possible mechanism showing how miRNAs are lost in few plant lineages even though other close relatives have abundantly expressing miRNAs.
Plant miRNAs are indispensable for the control of wide variety of biological functions, including development, hormone responses, feedback mechanisms and biotic and abiotic stresses [1, 2]. Most of these functions are associated with ability of miRNAs in targeting mRNAs coding for transcription factors and other key genes . Nearly half of all known plant miRNAs that are highly conserved across plants target transcription factors , justifying their importance in the regulation of plant processes. The remaining half of less-conserved miRNAs regulate expression of a variety of protein coding genes involved in metabolic processes, transporters and the process of RNA silencing itself . Additionally, role of some less-conserved miRNAs in controlling disease resistance in a variety of plants has been recently reported [5–7]. The well-conserved miRNAs that are evolutionarily ancient have many copies in the genomes, sometimes up to 50 copies, largely due to genome duplications or due to the rapid evolution of their target mRNAs, or both [3, 4, 8]. The duplicated copies called ‘isoforms’ may have high similarity in their mature miRNA sequences, but the similarity is less obvious among regions beyond miRNA stem-loops [9–11]. The less conserved miRNAs usually have 1 or 2 copies of themselves with high sequence similarity throughout the length of their RNAs [3, 4, 8, 12].
miRNAs are generated in a stepwise manner from long non-coding, genome-encoded PolII transcripts. Primary miRNA transcripts of varied length must form a secondary structure that can be recognized by Dicer-like protein 1 (DCL1) and its partners. DCL1 complex cleaves the secondary structured RNA to a pre-miRNA structure having a stem with almost complete complementarity and a loop. Another processing step in the cytoplasm produces miRNA:miRNA* duplex of predominantly 21 nts with 2 nt overhangs. While miRNA* is usually degraded, miRNAs associate with Argonaute (AGO) proteins to form RNA-induced silencing complexes (RISC). Most of the plant miRNAs appear to be targeting mRNAs for degradation, typically ‘slicing’ target mRNA between position 10 and 11. There are also many reports of plant miRNA:mRNA complexes leading to translational inhibition [1, 2].
Many factors in miRNA pathway have been characterized, but there is limited information on the self-regulation of miRNA pathway itself. Three miRNAs have been reported to regulate DCL and AGO by cleaving transcripts of corresponding targets as part of a robust feedback mechanism. miR162 has been implicated in targeting DCL1 , miR168 in AGO1 mRNA [14–16] and miR403 in targeting AGO2 and AGO3 mRNAs in Arabidopsis and other related plants [17–19]. The regulation of AGOs is quite striking because miRNAs that target mRNAs of AGOs need to form RISC complexes with AGO proteins themselves.
A relatively well-known feedback mechanism involves AGO1 homeostasis that is controlled by coordinated action of miR168 [15, 20] and AGO1-derived siRNAs  on AGO1 mRNA. Vaucheret et al.  also identified an additional complexity of this interaction involving the AGO1-mediated post-transcriptional stabilization of miR168 and the co-regulated expression of AGO1 and miR168 genes in Arabidopsis. Thus, it appears that Arabidopsis has a refined feedback regulatory loop that balances AGO1 and miR168 accumulation. In addition, miR168 expression is regulated by invading viruses. Upon infection with wide range of viruses, miR168 levels go up to dramatic levels quite quickly, leading to the repression of AGO1 translation . A similar upregulation of miR403, though proposed , has not been experimentally verified. Regulation of AGOs by miR168 and miR403 has been proposed to be conserved among many plants in addition to tobacco and Arabidopsis, although an in-depth analysis is not forthcoming.
The induction of miRNAs by viruses to meddle with AGO expression indicates that pathogens use these miRNAs particularly to suppress host silencing. This implies that variation in expression levels or targeting abilities of miRNAs among plant lineages has the potential to be the basis of susceptibility or resistance against pathogens. In order to understand these relationships, we analyzed sequence diversity, copy numbers and expression levels of miR168 and miR403 among plant species for which a small RNA dataset is available. Surprisingly, our results suggest that mature sequences of miR168 can be classified into three clades. Presence of three clades is also evident after aligning precursor sequences of these miRNAs. Variation in miR168 sequences seems to correlate well with their AGO1 mRNA targeting abilities. Strikingly, tobacco (N. tabacum) has isoforms with insertion of transposon-like sequences that are likely to reduce their processing, providing a clue to the loss of miRNAs. Furthermore, when we analyzed miR168 sequences across 68 plant species representing almost all major plant families, a clade specific abundance of miR168 was observed. The maximum abundance and diversity of miR168 was among monocots. Monocots have more numbers of AGO1 members than dicots, but few of them are not readily targeted by miR168 creating functional difference. The regulation of AGO2 and AGO3 mRNAs by miR403 is specific to very few plants. miR403 is absent among monocots and many eudicot lineages. Absence of miR403 among monocots indicates an inverse relationship with that of miR168, since miR168 is highly expressed among all monocots studied. In those plants where miR403 is present, the sequences are less diverse and plants have fewer isoforms of this miRNA indicating recent evolution of miR403. Together, this analysis indicates that miR168/miR403 relationships with their targets as observed in Arabidopsis are likely to be specific only to few plant lineages and plants have evolved every shade of such regulation providing case for altered transcription factor regulations and disease resistance.
miR168 sequences from diverse plant families fall into three distinct clades
In order to verify the presence of three groups of miR168 sequences, we aligned the precursors of all miR168 sequences using ClustalW2. Phylogenetic tree derived from this alignment (Additional file 2: Figure S1) also confirms the presence of three clades of miR168 sequences. This suggests that there are sequences beyond mature miRNA sequences that also contribute towards clade-specificity. Presence of these clades and a separate clade for Solanaceae is remarkable because this indicates independent evolution of miR168 among Solanaceae members as these species are distantly related to monocots.
Monocots show higher diversification of AGO1s, usually with 4 members , something that may have been due to ancient duplications . We anticipated that presence of additional AGO1 mRNA may provide differential targeting abilities for monocot miR168 members (Additional file 3: Figure S2). Although there are 4 members of AGO1 there are only one or two distinct mature miR168 sequences. Some AGO1 members of Zea mays such as AGO1c and AGO1d are not targeted by zma miR168, but AGO1a and b are good targets (Additional file 3: Figure S2). Rice AGO1d alone has slightly higher tapir score (less optimal target due to mismatch in cleavage site or nearby), while other AGO1 members are good targets. Among the 4 AGO1 members from Brachypodium, one member (Bdi AGO1c) is clearly not a target of bdi miR168 (more than 3 mismatches in seed region). These differences among monocots might contribute to the diversity in their miRNA pathways since AGO1 is a major player in miRNA stabilization and action. We also predicted targets for few miR168 examples from each of the three clades with AGO1 mRNAs from the corresponding plants (Figure 3C). This analysis shows that targeting of AGO1 mRNAs by miR168 in monocots is slightly less intense than among dicots based on tapir score.
Secondary structures and precursor miRNA features of miR168s indicate their rapid diversification in Solanaceaeclade
Comparative abundance of miR168 among plant families
Surprisingly, abundance of miR168 was comparatively low among Arabidopsis and members of Solanaceae such as Solanum spp. and Nicotiana spp. Most abundant form of miR168 among Solanaceae was the form that is distinct from other dicots. These forms have also been reported recently in a global study using small RNA datasets from many vascular plants . Among dicots, some Astrids such as Mimulus guttatus (Lamiaceae), Lactuca sativa (Asterales) have the highest accumulation of miR168.
Consistent with the observation in Arabidopsis that floral tissues accumulate more 24 nt siRNAs than miRNAs, miR168 levels are generally low among floral samples of all plant species analyzed. Unexpectedly, rice (Oryza sativa) and sorghum (Sorghum bicolor) are some of the few species where miR168 was consistently expressed highly among both leaf and floral tissues (Additional file 7: Figure S6).
Viruses as part of their counter-defense strategy target the host AGOs by destabilizing them directly at the protein level [33–36]. Some viruses even act at a higher level by inducing degradation of mRNAs of AGO family members that are part of the host defense, namely AGO1, AGO2 and AGO3. Viral counter-defense by targeting of AGO mRNAs is through induction of miR168 as observed in N. benthamiana, A. thaliana and S. lycopersicum. After analyzing the global miR168 levels in these species it makes sense to hypothesize why viruses need to upregulate miR168 to target AGO1 mRNAs. All these species have very low levels of miR168 in uninfected tissues indicating they may have higher accumulation of AGO1 protein thereby indicating AGO1 as the most likely and potent candidate to target viruses. However, such an interaction seems unlikely for monocots (these plants act as hosts to few viruses), members of which accumulate miR168 at higher levels even without any biotic stress. By analyzing publicly available small RNA datasets we can show that miR168 induction upon virus infection of rice (a monocot) is hardly noteworthy ( Additional file 8: Figure S7). Corresponding levels of increase in miR168 levels upon viral infection for few dicots such as N. benthamiana, Arabidopsis and tomato are at much higher levels . This difference in miR168 levels upon virus infection among dicots and monocots is important because AGO1 protein levels go down dramatically upon virus infection in Arabidopsis and Nicotiana members , while in rice, the reduction in AGO1 protein level is negligible . These results suggest a functional difference in downstream activities of AGO1 among monocots and dicots that is brought about by variation in expression levels of miR168.
miR403 has low sequence diversity and are present only among selected lineages of plants
Targeting of AGO2 and AGO3 mRNAs by miR403 is restricted to few plant lineages
miR403 targets mRNAs of AGO2 and AGO3 in Arabidopsis. It has been proposed that viruses may interfere with miR403 expression in order to reduce the expression of AGO2, considered as a major antiviral AGO. When we analyzed AGO2 mRNAs from those species where miR403 accumulation could be detected, it was observed that targeting of AGO2 mRNA is very efficient in Brassicaceae (Brassica and Arabidopsis Spp.) and Vitales (Vitis vinifera, Citrus sinensis), while it is ineffective with score of excess of 10 among Fabids (Additional file 10: Figure S9A and B). It is important to note that Vitales have not only very high expression of miR403, but also have high AGO2 targeting ability compared to other plant families. We also checked targeting of AGO3 mRNAs by miR403. Such a targeting seem to be possible only among Arabidopsis Spp. (Additional file 11: Figure S10) but not among members of any other plant family. Functional significance of this relationship is not known.
AGO expression levels and susceptibility to viruses
It has been clearly shown that few AGOs in addition to being important for development by controlling transcription factors and other endogenes, are the first line of defense against incoming pathogens. Two lines of evidence are strongly in favor of this observation. Firstly, viral and other pathogen-derived siRNAs are incorporated into AGO1 and to less extent AGO2, thereby performing the role of targeting complementary mRNAs derived from the incoming pathogens themselves. Secondly, pathogens have the ability to selectively target these AGOs both at post-transcriptional as well as post-translational steps. Since AGO1 is responsible for stabilization and activity of most miRNAs, it has been well documented that miRNA levels change generally during pathogenesis, especially during virus infections, due to AGO1 targeting. Unlike most miRNAs that change marginally during viral infections, levels of miR168 changes drastically. This specific change is likely brought about by viral counter-defense proteins, but the mechanism is largely unknown. However, it has been clearly shown that this interaction is crucial for pathogenicity. Thus, absence or lower expression of miR168 in some plants (Figure 6) may indicate a higher expression of AGO1 in those species and this is where viruses might need to target AGO1 as part of their counter defense strategy. In line with this hypothesis, virus-mediated induction of miR168 has been observed among those plants where miR168 levels are generally lower in the absence of viral infections. On the other hand, higher expression of miR168 in some plant lineages might be resulting in a lower accumulation of corresponding AGOs. Indeed in leaves and roots of rice, a monocot, where miR168 levels are quite high, expression of AGO1s is comparatively at lower levels than in Arabidopsis[40, 41]. In such cases, viruses need not target AGO1 as part of their counter-defense simply because antiviral role by AGO1 may be negligible or is taken over by other AGOs. This may be the case for rice, where neither a strong induction of miR168, nor a corresponding reduction in AGO1 levels has been observed upon viral infections (Additional file 8: Figure S7, ).
On the other hand, absence of miR403 among monocots correlates well with the expression levels of AGO2. In rice, AGO2 expression is very high among all tissues unlike in Arabidopsis where AGO2 expression is largely confined to siliques and at much lower levels in leaves [40, 41]. It remains to be investigated if AGO2 indeed acts as an antiviral AGO among monocots. However, unlike in Arabidopsis where AGO2 gets induced during viral infections , there is hardly any change in AGO2 levels during Rice stripe virus and Rice dwarf virus infections in rice . This supports our view that induction and regulation of AGOs by viruses is restricted to few plant lineages.
Rapid evolution of tobacco miR168 isoforms
A case for loss of miRNAs can be argued based on the miR168 diversity in N. tabacum. The common dicot forms of miR168 in tobacco (isoforms d and e) have insertions of MITE-like transposons. A direct result of this insertion corresponds to reduced accumulation of mature miRNA forms in all tissue types. The Solanaceae-specific forms on the other hand (a, b and c), does not have MITE-like insertions and are expressed at high levels. A duplication event of miR168 in tobacco might have ended up with isoforms having two different miR168 sequences. One set (d and e) while retaining mature miR168 of dicot ancestor, attracted transposons in the loop region. Tobacco seems to be a hotbed for miR168 duplication since it already has the most diverse miR168 precursors. In addition, there are many tobacco genomic regions matching miR168 sequences present in the genome, sometimes their miR* sequences either missing or present a long distance downstream or upstream. These may represent the lost miR168 isoforms. It is possible that miR168 example that is observed in tobacco is seen in other miRNAs where some forms are lost during duplication and subsequent loss.
Transposons invite siRNAs and methylation. Invasive Transposons such as MITES can be detected and neutralized using RNA-directed DNA methylation . This may be how promoters of some miRNAs become methylated and inactive. It is possible thus that tobacco miR168 d and e isoforms may have been targets of RNA-directed DNA methylation and hence no longer express their RNAs. It will be interesting to speculate if viruses can still modulate expression of tobacco miR168d and e. Unfortunately, there are no small RNA datasets from tobacco infected with viruses to see if miR168 d and e isoforms are induced upon virus infection. However, other line of evidence suggests that these isoforms are not likely induced upon virus infections. Usually upon virus infections, not just mature miR168, but also its stem-loop structures over-accumulate . However, miR168d and e may not be induced by viruses as seen from the absence of accumulation of their precursors or pre-miRNAs . A stem-loop of miR168 d and e (they are around 200 + nts) was not seen among tobacco samples infected with viruses.
Our study indicates that intricacies of AGO targeting by miRNAs as observed in Arabidopsis is specific only among few plant lineages. Plants have evolved every shade of this regulation providing case for varying miRNA levels, thus influencing transcription factor and other activities regulated by miRNAs. The nature of this interaction may also influence disease resistance due to the way viruses use these miRNAs to manage the arms race with their host plants.
Identifying miRNA Diversity, Sequence Alignments and their Targets
The UEA small RNA analysis toolkit  was used to identify members of a given miRNA family (miRProf and miRCat) using default as well as allowing 3 mismatches. Detailed description of the tool is given in http://srna-tools.cmp.uea.ac.uk/. Sequences of miR168 and miR403 were obtained from miRBase release 20 [43, 44] and aligned using ClustalW and ClustalX2 . Previously unreported sequences of miR168 and miR403 were obtained from EST datasets after fulfilling criteria for plant miRNAs including checking for secondary structure (RNAfold, ) as well as abundance and distribution of small RNAs across the length of the precursors. List of all plants species and their families are given in Additional file 1: Table S1. Targets of miRNA were identified using two different algorithms, namely, psRNATarget algorithm  and TAPIR algorithm . To find targets of miR168 and miR403 family in the plant genomes, target AGO sequences were taken from the NCBI , Solanaceous genome Network , Refseq  as well as from NCBI GEO .
Analysis of abundance of miR168 and miR403 members were performed through miRProf analysis of published large-scale data sets derived from various plant species available through the Gene Expression Omnibus (GEO) platform [49, 50]. These libraries have been described previously [5, 6, 12, 30, 51–57]. miRNA sequences were checked to compensate for the mis annotation of miR168 type and miR403-type sequences in miRBase.
The phylogenetic tree was constructed using the MEGA 6.0 software with Neighbor Joining Method with 1000 bootstrap replications. The model used was Jukes Cantor that had the highest log-likelihood score according to the J-model Test (https://code.google.com/p/jmodeltest2/). For the J-model test the precursor alignment was given as the input in “.aln” format. It calculates for the variations in the nucleotide sequences and gives the log-likelihood scores for all the models for phylogenetic tree construction.
PVS acknowledges support from Ramanujan Fellowship (SR/S2/RJN-109/2012; Department of Science and Technology, Government of India). The PI’s lab is supported by NCBS-TIFR core funding and funds from Department of Biotechnology, Govt. of India. We thank Rahul Raj Singh and N.D. Sunitha for comments.
- Baulcombe D: RNA silencing in plants. Nature. 2004, 431: 356-363. 10.1038/nature02874.PubMedView ArticleGoogle Scholar
- Voinnet O: Origin, biogenesis, and activity of plant microRNAs. Cell. 2009, 136: 669-687. 10.1016/j.cell.2009.01.046.PubMedView ArticleGoogle Scholar
- Axtell MJ: Evolution of microRNAs and their targets: are all microRNAs biologically relevant?. Biochim Biophys Acta. 2008, 1779: 725-734. 10.1016/j.bbagrm.2008.02.007.PubMedView ArticleGoogle Scholar
- Cuperus JT, Fahlgren N, Carrington JC: Evolution and Functional Diversification of MIRNA Genes. Plant Cell. 2011, 23: 431-442. 10.1105/tpc.110.082784.PubMed CentralPubMedView ArticleGoogle Scholar
- Zhai J, Jeong D-H, De Paoli E, Park S, Rosen BD, Li Y, Gonzalez AJ, Yan Z, Kitto SL, Grusak MA, Jackson SA, Stacey G, Cook DR, Green PJ, Sherrier DJ, Meyers BC: MicroRNAs as master regulators of the plant NB-LRR defense gene family via the production of phased, trans-acting siRNAs. Genes Dev. 2011, 25: 2540-2553. 10.1101/gad.177527.111.PubMed CentralPubMedView ArticleGoogle Scholar
- Shivaprasad PV, Chen H-M, Patel K, Bond DM, Santos BACM, Baulcombe DC: A microRNA superfamily regulates nucleotide binding site-leucine-rich repeats and other mRNAs. Plant Cell. 2012, 24: 859-74. 10.1105/tpc.111.095380.PubMed CentralPubMedView ArticleGoogle Scholar
- Li F, Pignatta D, Bendix C, Brunkard JO, Cohn MM, Tung J, Sun H, Kumar P, Baker B: MicroRNA regulation of plant innate immune receptors. Proc Natl Acad Sci. 2012, 109: 1790-1795. 10.1073/pnas.1118282109.PubMed CentralPubMedView ArticleGoogle Scholar
- Taylor RS, Tarver JE, Hiscock SJ, Donoghue PCJ: Evolutionary history of plant microRNAs. Trends Plant Sci. 2014, 19: 175-182. 10.1016/j.tplants.2013.11.008.PubMedView ArticleGoogle Scholar
- Willmann MR, Poethig RS: Conservation and evolution of miRNA regulatory programs in plant development. Curr Opin Plant Biol. 2007, 10: 503-511. 10.1016/j.pbi.2007.07.004.PubMed CentralPubMedView ArticleGoogle Scholar
- Jones-Rhoades MW: Conservation and divergence in plant microRNAs. Plant Mol Biol. 2012, 80: 3-16. 10.1007/s11103-011-9829-2.PubMedView ArticleGoogle Scholar
- Felippes FF, Schneeberger K, Dezulian T, Huson DH, Weigel D: Evolution of Arabidopsis thaliana microRNAs from random sequences. RNA. 2008, 14: 2455-2459. 10.1261/rna.1149408.PubMedView ArticleGoogle Scholar
- Montes RAC, de Fátima Rosas-Cárdenas F, De Paoli E, Accerbi M, Rymarquis LA, Mahalingam G, Marsch-Martínez N, Meyers BC, Green PJ, de Folter S: Sample sequencing of vascular plants demonstrates widespread conservation and divergence of microRNAs. Nat Commun. 2014, 5: 3722-View ArticleGoogle Scholar
- Xie Z, Kasschau KD, Carrington JC: Negative feedback regulation of Dicer-Like1 in Arabidopsis by microRNA-guided mRNA degradation. Curr Biol. 2003, 13: 784-789. 10.1016/S0960-9822(03)00281-1.PubMedView ArticleGoogle Scholar
- Vaucheret H: Plant ARGONAUTES. Trends Plant Sci. 2008, 13: 350-358. 10.1016/j.tplants.2008.04.007.PubMedView ArticleGoogle Scholar
- Vaucheret H, Vazquez F, Crete P, Bartel DP: The action of ARGONAUTE1 in the miRNA pathway and its regulation by the miRNA pathway are crucial for plant development. Genes Dev. 2004, 18: 1187-1197. 10.1101/gad.1201404.PubMed CentralPubMedView ArticleGoogle Scholar
- Várallyay E, Válóczi A, Agyi A, Burgyán J, Havelda Z: Plant virus-mediated induction of miR168 is associated with repression of ARGONAUTE1 accumulation. EMBO J. 2010, 29: 3507-3519. 10.1038/emboj.2010.215.PubMed CentralPubMedView ArticleGoogle Scholar
- Harvey JJW, Lewsey MG, Patel K, Westwood J, Heimstadt S, Carr JP, Baulcombe DC: An Antiviral Defense Role of AGO2 in Plants. PLoS One. 2011, 6:Google Scholar
- McMorran JP, Allen TC: Maintenance, symptoms and distribution of potato viruses X, S, Y, A, M and leafroll in potato tissue culture plantlets. Am PotatoJ. 1983, 60: 839-848. 10.1007/BF02853973.View ArticleGoogle Scholar
- Allen E, Xie Z, Gustafson AM, Carrington JC: microRNA-Directed Phasing during Trans-Acting siRNA Biogenesis in Plants. Cell. 2005, 121: 207-221. 10.1016/j.cell.2005.04.004.PubMedView ArticleGoogle Scholar
- Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP: Prediction of plant microRNA targets. Cell. 2002, 110: 513-520. 10.1016/S0092-8674(02)00863-2.PubMedView ArticleGoogle Scholar
- Mallory AC, Vaucheret H: Functions of micro-RNAs and related small RNAs in plants. Nat Genet Suppl. 2006, 38: S31-10.1038/ng1791.View ArticleGoogle Scholar
- Vaucheret H, Mallory AC, Bartel DP: AGO1 Homeostasis entails coexpression of MIR168 and AGO1 and preferential stabilization of miR168 by AGO1. Mol Cell. 2006, 22: 129-136. 10.1016/j.molcel.2006.03.011.PubMed CentralPubMedView ArticleGoogle Scholar
- Allen E, Xie Z, Gustafson AM, Sung G-H, Spatafora JW, Carrington JC: Evolution of microRNA genes by inverted duplication of target gene sequences in Arabidopsis thaliana. Nat Genet. 2004, 36: 1282-1290. 10.1038/ng1478.PubMedView ArticleGoogle Scholar
- Vazquez F, Blevins T, Ailhas J, Boller T, Meins F: Evolution of Arabidopsis MIR genes generates novel microRNA classes. Nucleic Acids Res. 2008, 36: 6429-6438. 10.1093/nar/gkn670.PubMed CentralPubMedView ArticleGoogle Scholar
- Dai XB, Zhao PX: psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 2011, 39: W155-W159. 10.1093/nar/gkr319.PubMed CentralPubMedView ArticleGoogle Scholar
- Bonnet E, He Y, Billiau K, Van de Peer Y: TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics. 2010, 26: 1566-1568. 10.1093/bioinformatics/btq233.PubMedView ArticleGoogle Scholar
- Srivastava PK, Moturu TR, Pandey P, Baldwin IT, Pandey SP: Comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction. BMC G. 2014, 15: 348-10.1186/1471-2164-15-348.View ArticleGoogle Scholar
- Tang H, Bowers JE, Wang X, Paterson AH: Angiosperm genome comparisons reveal early polyploidy in the monocot lineage. Proc Natl Acad Sci U S A. 2010, 107: 472-477. 10.1073/pnas.0908007107.PubMed CentralPubMedView ArticleGoogle Scholar
- Colaiacovo M, Lamontanara A, Bernardo L, Alberici R, Crosatti C, Giusti L, Cattivelli L, Faccioli P: On the complexity of miRNA-mediated regulation in plants: novel insights into the genomic organization of plant miRNAs. Biology Direct. 2007, 7: 15-View ArticleGoogle Scholar
- Song L, Axtell MJ, Fedoroff NV: RNA Secondary Structural Determinants of miRNA Precursor Processing in Arabidopsis. Curr Biol. 2010, 20: 37-41. 10.1016/j.cub.2009.10.076.PubMedView ArticleGoogle Scholar
- Piriyapongsa J, Mariño-Ramírez L, Jordan IK: Origin and evolution of human microRNAs from transposable elements. Genetics. 2007, 176: 1323-1337.PubMed CentralPubMedView ArticleGoogle Scholar
- Moxon S, Schwach F, Dalmay T, MacLean D, Studholme DJ, Moulton V: A toolkit for analysing large-scale plant small RNA datasets. Bioinformatics. 2008, 24: 2252-2253. 10.1093/bioinformatics/btn428.PubMedView ArticleGoogle Scholar
- Baumberger N, Tsai C-H, Lie M, Havecker E, Ziegler-Graff V, Baulcombe DC: The Polerovirus Silencing Suppressor P0 Targets ARGONAUTE Proteins for Degradation. Curr Biol. 2007, 17: 1609-1614. 10.1016/j.cub.2007.08.039.PubMedView ArticleGoogle Scholar
- Moissiard G, Voinnet O: Viral suppression of RNA silencing in plants. Mol Plant Pathol. 2004, 5: 71-82. 10.1111/j.1364-3703.2004.00207.x.PubMedView ArticleGoogle Scholar
- Chapman EJ, Prokhnevsky AI, Gopinath K, Dolja V, Carrington JC: Viral RNA silencing suppressors inhibit the microRNA pathway at an intermediate step. Genes Dev. 2004, 18: 1179-1186. 10.1101/gad.1201204.PubMed CentralPubMedView ArticleGoogle Scholar
- Azevedo J, Garcia D, Pontier D, Ohnesorge S, Yu A, Garcia S, Braun L, Bergdoll M, Hakimi MA, Lagrange T, Voinnet O: Argonaute quenching and global changes in Dicer homeostasis caused by a pathogen-encoded GW repeat protein. Genes Dev. 2010, 24: 904-915. 10.1101/gad.1908710.PubMed CentralPubMedView ArticleGoogle Scholar
- Du P, Wu J, Zhang J, Zhao S, Zheng H, Gao G, Wei L, Li Y: Viral infection induces expression of novel phased microRNAs from conserved cellular microRNA precursors. PLoS Pathog. 2011, 7: e1002176-10.1371/journal.ppat.1002176.PubMed CentralPubMedView ArticleGoogle Scholar
- Satoh K, Shimizu T, Kondoh H, Hiraguri A, Sasaya T, Choi IR, Omura T, Kikuchi S: Relationship between symptoms and gene expression induced by the infection of three strains of Rice dwarf virus. PLoS One. 2011, 6: e18094-10.1371/journal.pone.0018094.PubMed CentralPubMedView ArticleGoogle Scholar
- Sunkar R, Jagadeeswaran G: In silico identification of conserved microRNAs in large number of diverse plant species. BMC Plant Biol. 2008, 8: 37-10.1186/1471-2229-8-37.PubMed CentralPubMedView ArticleGoogle Scholar
- Yang Y, Zhong J, YDan O, Yao J: The integrative expression and co-expression analysis of the AGO gene family in rice. Gene. 2013, 528: 221-235. 10.1016/j.gene.2013.07.002.PubMedView ArticleGoogle Scholar
- Kapoor M, Arora R, Lama T, Nijhawan A, Khurana JP, Tyagi AK, Kapoor S: Genome-wide identification, organization and phylogenetic analysis of Dicer-like, Argonaute and RNA-dependent RNA Polymerase gene families and their expression analysis during reproductive development and stress in rice. BMC Genomics. 2008, 9: 451-10.1186/1471-2164-9-451.PubMed CentralPubMedView ArticleGoogle Scholar
- Marí-Ordóñez A, Marchais A, Etcheverry M, Martin A, Colot V, Voinnet O: Reconstructing de novo silencing of an active plant retrotransposon. Nat Genet. 2013, 45: 1029-39. 10.1038/ng.2703.PubMedView ArticleGoogle Scholar
- Kozomara A, Griffiths-Jones S: miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011, 39: D152-D157. 10.1093/nar/gkq1027.PubMed CentralPubMedView ArticleGoogle Scholar
- Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ: miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 2006, 34: D140-D144. 10.1093/nar/gkj112.PubMed CentralPubMedView ArticleGoogle Scholar
- Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG: Clustal W and clustal X version 2.0. Bioinformatics. 2007, 23: 2947-2948. 10.1093/bioinformatics/btm404.PubMedView ArticleGoogle Scholar
- Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL: NCBI BLAST: a better web interface. Nucleic Acids Res. 2008, 36: W5-9-10.1093/nar/gkn235.PubMedView ArticleGoogle Scholar
- Mueller LA, Mills AA, Skwarecki B, Buels RM, Menda N, Tanksley SD: The SGN comparative map viewer. Bioinformatics. 2008, 24: 422-423. 10.1093/bioinformatics/btm597.PubMedView ArticleGoogle Scholar
- Pruitt KD, Tatusova T, Maglott DR: NCBI reference sequences (RefSeq): A curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2007, 35: D61-65-View ArticleGoogle Scholar
- Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Edgar R: NCBI GEO: Mining tens of millions of expression profiles - Database and tools update. Nucleic Acids Res. 2007, 35: D76-765. 10.1093/nar/gkl648.View ArticleGoogle Scholar
- Edgar R, Domrachev M, Lash AE: Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002, 30: 207-210. 10.1093/nar/30.1.207.PubMed CentralPubMedView ArticleGoogle Scholar
- Pilcher RLR, Moxon S, Pakseresht N, Moulton V, Manning K, Seymour G, Dalmay T: Identification of novel small RNAs in tomato (Solanum lycopersicum). Planta. 2007, doi:10.100Google Scholar
- Havecker ER, Wallbridge LM, Hardcastle TJ, Bush MS, Kelly KA, Dunn RM, Schwach F, Doonan JH, Baulcombe DC: The Arabidopsis RNA-Directed DNA Methylation Argonautes Functionally Diverge Based on Their Expression and Interaction with Target Loci. Plant Cell. 2010, 22: 321-334. 10.1105/tpc.109.072199.PubMed CentralPubMedView ArticleGoogle Scholar
- Ma ZR, Coruh C, Axtell MJ: Arabidopsis lyrata Small RNAs: Transient MIRNA and Small Interfering RNA Loci within the Arabidopsis Genus. Plant Cell. 2010, 22: 1090-1103. 10.1105/tpc.110.073882.PubMed CentralPubMedView ArticleGoogle Scholar
- Molnar A, Melnyk CW, Bassett A, Hardcastle TJ, Dunn R, Baulcombe DC: Small silencing RNAs in plants are mobile and direct epigenetic modification in recipient cells. Science. 2010, 328: 872-875. 10.1126/science.1187959.PubMedView ArticleGoogle Scholar
- Wang C, Wang XC, Kibet NK, Song CN, Zhang CQ, Li XY, Han J, Fang JG: Deep sequencing of grapevine flower and berry short RNA library for discovery of novel microRNAs and validation of precise sequences of grapevine microRNAs deposited in miRBase. Physiol Plant. 2011, 143: 64-81. 10.1111/j.1399-3054.2011.01481.x.PubMedView ArticleGoogle Scholar
- Shivaprasad PV, Dunn RM, Santos BA, Bassett A, Baulcombe DC: Extraordinary transgressive phenotypes of hybrid tomato are influenced by epigenetics and small silencing RNAs. EMBO J. 2012, 31: 257-266. 10.1038/emboj.2011.458.PubMed CentralPubMedView ArticleGoogle Scholar
- Song X, Li P, Zhai J, Zhou M, Ma L, Liu B, Jeong DH, Nakano M, Cao S, Liu C, Chu C, Wang XJ, Green PJ, Meyers BC, Cao X: Roles of DCL4 and DCL3b in rice phased small RNA biogenesis. Plant J. 2011, 69: 462-474.PubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.