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First published online February 27, 2008; 10.1104/pp.108.116582 Plant Physiology 146:1974-1982 (2008) © 2008 American Society of Plant Biologists Sequence Variation of MicroRNAs and Their Binding Sites in Arabidopsis1,[W]Department of Biology and Center for Genomics and Systems Biology, New York University, New York, New York 10003 (I.M.E., M.D.P.); and Department of Genetics, North Carolina State University, Raleigh, North Carolina 27695 (I.M.E.)
Major differences exist between plants and animals both in the extent of microRNA (miRNA)-based gene regulation and the sequence complementarity requirements for miRNA-messenger RNA pairing. Whether these differences affect how these sites evolve at the molecular level is unknown. To determine the extent of sequence variation at miRNAs and their targets in a plant species, we resequenced 16 miRNA families (66 miRNAs in total) and all 52 of the characterized binding sites for these miRNAs in the plant model Arabidopsis (Arabidopsis thaliana), accounting for around 50% of the known miRNAs and binding sites in this species. As has been shown previously in humans, we find that both miRNAs and their target binding sites have very low nucleotide variation and divergence compared to their flanking sequences in Arabidopsis, indicating strong purifying selection on these sites in this species. Sequence data flanking the mature miRNAs, however, exhibit normal levels of polymorphism for the accessions in this study and, in some cases, nonneutral evolution or subtle effects on predicted pre-miRNA secondary structure, suggesting that there is raw material for the differential function of miRNA alleles. Overall, our results show that despite differences in the architecture of miRNA-based regulation, miRNAs and their targets are similarly constrained in both plants and animals.
Changes in gene regulation have long been thought to be important to evolutionary diversification (King and Wilson, 1975
MicroRNAs (miRNAs) are small RNAs approximately 21 nucleotides long with complementarity to specific regions in messenger RNAs (mRNAs) and are important posttranscriptional regulators of gene expression in eukaryotes (Carrington and Ambros, 2003
The number of miRNAs per eukaryotic genome varies by species. For instance, miRBase presently lists 114, 117, and 326 miRNA genes in Arabidopsis (Arabidopsis thaliana), Caenorhabditis elegans, and humans, respectively (Griffiths-Jones, 2004
The total number of genes targeted by miRNAs is also highly variable and genome specific. Only 1% of all protein-coding genes appear to be miRNA targets in Arabidopsis (Rhoades et al., 2002
Differences in miRNA function also exist between plants and animals. In animals, the complementarity between the first six to eight bases of a target to a miRNA are most important to binding (Rajewsky, 2006
The extent to which miRNAs contribute to phenotypic evolution is unclear, but evidence suggests they could play an important role. Although essential miRNA-target site interactions have been conserved for >400 million years in plants and animals, e.g. miR165/166 and Class III HD-ZIP (homeodomain Leu zipper) genes in land plants (Floyd and Bowman, 2004
Little is known about the microevolution of miRNA-target site interactions, though a few studies have documented functional polymorphisms at these sites. A single nucleotide polymorphism (SNP) that results in a de novo miRNA binding site has been shown to underlie a quantitative trait locus for muscularity in sheep (Clop et al., 2006
Genome-wide surveys of miRNA and miRNA binding site polymorphism have only been conducted in humans. These studies have shown levels of polymorphism at miRNAs and their targets are lower than at coding or neutral regions; the mutations at these sites exhibit a general signature of purifying selection (Chen and Rajewsky, 2006 Predictions can be made about the expected level of miRNA and miRNA binding site sequence variation in plants relative to humans based on the functional differences between plant and animal miRNAs that are described above. Plant miRNAs typically have fewer mRNA targets and more miRNA family members than animal miRNAs, which may lead to reduced constraint on and higher sequence diversity in miRNA sequences in plants. However, as most plant miRNAs perform important functions in development and physiology, and spatiotemporal functional differences may exist among plant miRNA family members making each independently essential, constraint on plant miRNAs may parallel that observed in humans. As for miRNA binding sites, constraint is likely to be strong across the entire miRNA binding site in plants due to the importance of the entire binding site in miRNA-mRNA pairing. Additionally, plant miRNA binding sites may experience additional constraint due to the presence of these sites largely in coding exons in plants. We assess the levels and patterns of nucleotide polymorphism in miRNAs and their binding sites in the model plant Arabidopsis by resequencing more than half of the characterized miRNAs and binding targets in this species from 24 diverse accessions. We find significantly reduced genetic variation at these sites relative to flanking sequence, with only four SNPs and an insertion/deletion (indel) present in our sample. However, we do find substantial variation flanking miRNAs both within Arabidopsis and between it, and the closely related out-group Arabidopsis lyrata. Interestingly, four miRNAs exhibit nonneutral patterns of molecular variation, and numerous SNPs are predicted to have subtle effects on pre-miRNA secondary structure. Our results suggest that mutations within mature miRNAs and their binding sites do not contribute substantially to gene expression and phenotypic variation in this model plant species, but that ample variation flanks mature miRNAs that could contribute to the evolutionary diversification of these key regulatory genes.
SNPs and Nucleotide Divergence in Arabidopsis miRNAs
We investigated the sequence variation of 66 miRNAs belonging to 16 miRNA families, as well as 52 mRNA binding site targets that represented all the validated targets for these miRNAs (Table I
). On average, we resequenced four miRNAs per family and three target sites per miRNA family in a set of 24 accessions. These miRNAs were selected because: (1) their interactions with mRNA targets have been functionally characterized, and/or (2) they target transcripts of genes with known roles in development. Altogether, these comprise over 55% of the presently described miRNAs and 40% of the validated binding sites in Arabidopsis, based on data in Jones-Rhoades et al. (2006)
For each miRNA, we sequenced on average 489 bp, with approximately 133 bp of pre-miRNA (based on pre-miRNA predictions in miRBase), as well as about 180 and 176 bp of upstream and downstream flanking sequence, respectively. The average level of SNP per site ( ; Watterson, 1975 = 0.0055 ± 0.0002 and K = 0.085 ± 0.005 as assessed using 1,213 previously resequenced genome-wide loci (Wilcoxon rank sum test; P < 0.0001 for both polymorphism and divergence).
We also estimated levels of nucleotide diversity for the sequences flanking the miRNAs, including the pre-miRNAs and the upstream and downstream flanking sequence. Nucleotide polymorphism levels at these sites are substantially higher than those observed in the miRNAs themselves, with a mean = 0.0025 ± 0.0003 for the pre-miRNA, and mean = 0.0051 ± 0.0006 and 0.0054 ± 0.0006 for the upstream and downstream flanking sequences, respectively (Fig. 2
). Although no indel polymorphisms were observed in the mature miRNA sequences, numerous indels were detected in the pre-miRNAs and flanking sites (0.7 per kilobase pair at pre-miRNAs, 1.7 per kilobase pair for upstream sequence, and 2 per kilobase pair for downstream flanking sequence). Levels of nucleotide divergence are also higher at these sites, with mean K = 0.052 ± 0.007 for pre-miRNA, 0.11 ± 0.014 for upstream sequence, and 0.2 ± 0.026 at downstream sites (Fig. 2). The dramatically reduced intraspecific polymorphism and interspecific divergence at mature miRNAs, and to a lesser extent pre-miRNAs, suggests that purifying selection is the predominant evolutionary force that acts on miRNAs in Arabidopsis.
Levels and Patterns of Nucleotide Polymorphism and Divergence in miRNA Target Binding Sites
We also estimated polymorphism and divergence at the target binding sites of the miRNAs we examined (Table I). In all cases, these sites had been previously validated as the target sites of specific miRNAs (Jones-Rhoades et al., 2006 Like their cognate miRNAs, we also observe significantly low polymorphism levels at the miRNA binding sites relative to background polymorphism, with mean nucleotide diversity equal to 0.0005 ± 0.0003 (Wilcoxon rank sum test; P < 0.0001). Only two binding sites of the 52 we studied—in the AUXIN SIGNALING F-BOX1 (AFB1) and TARGET OF EAT3 (TOE3) genes—are polymorphic (Fig. 1). The AFB1 binding site, which is targeted by miR393, has a single SNP segregating at 12% frequency (in the Edi-0, Ga-0, and Ll-0 accessions). The AFB1 minor allele converts a miRNA-mRNA match position to a mismatch position relative to the major allele (Fig. 1). TOE3 is targeted by miR172 and this binding site has a 7-bp deletion and an SNP that cosegregate at 4% frequency in our sample (found in the Gy-0 accession). The TOE3 binding site deletion, however, is partially recovered in the mRNA due to upstream sequence similarity, resulting in only a single base-pair deletion and a SNP in the mature transcript (Fig. 1). Although the low-frequency TOE3 polymorphisms are derived mutations, the derived mutation at AFB1 is the common SNP allele. Nucleotide divergence at target binding sites is K = 0.003 ± 0.002, which is significantly lower than the genome-wide average (Wilcoxon rank sum test; P < 0.0001). Only one binding site—in AUXIN RESPONSE FACTOR10 (ARF10), which is targeted by miR160—exhibits a fixed sequence difference between species. This substitution occurs at a mismatch position in the miRNA-mRNA pairing sequence (Fig. 3 ).
Levels of nucleotide variation were also reduced at miRNA binding sites relative to their flanking sequences (mean = 0.0028 ± 0.0005 and 0.0033 ± 0.0005 for upstream and downstream flanking sequences, respectively; see Fig. 4
). These flanking nucleotide diversity values are low in comparison to data surrounding mature miRNAs, and are likely due to the location of many of these binding sites in coding exons. To correct for this, we also calculated silent site nucleotide diversity ( silent) for miRNA binding sites and their flanking sequences. These estimates ( silent = 0.0015 ± 0.0007, 0.0069 ± 0.0026, and 0.0053 ± 0.0009 for miRNA binding sites, upstream sequence, and downstream sequence, respectively) are higher than those for uncorrected nucleotide diversity estimates. The relative levels of variation across the site classes remain similar to uncorrected values, however, because nucleotide diversity at the binding sites is still much lower than at flanking sites. Additionally, divergence was much lower at binding sites than at upstream (K = 0.062 ± 0.005) or downstream (K = 0.067 ± 0.001) sites (Fig. 4).
Summary Statistics of the Nucleotide Site-Frequency Spectrum
Although miRNAs and their target binding sites have little variation, we observe normal levels of sequence variation in regions flanking miRNAs. Selection on these polymorphisms or those linked to them could generate nonneutral patterns of linked sequence variation. To examine this possibility, we calculated Tajima's D (Tajima, 1989
Secondary Structure Predictions of Pre-miRNA Haplotypes Using Biologically Relevant Temperatures
To evaluate the possible impacts of SNPs on pre-miRNA secondary structure, we computationally predicted the secondary structure and Gibbs free energy ( Of the 66 miRNAs we looked at overall, only 35 had SNPs segregating in their predicted pre-miRNAs; 62 total SNPs were identified across these pre-miRNAs. Using the predicted pre-miRNA secondary structure for the haplotype of the Columbia (Col-0) accession of Arabidopsis for each miRNA, we determined the structural context of each SNP within its respective pre-miRNA. The vast majority of the SNPs were located in double-stranded stem regions—40 in the general stem and seven in the miRNA or miRNA* (Fig. 6 ). Of the remaining 15 SNPs, nine were located in the primary loop at the top of the pre-miRNA stem-loop molecule and the remaining six were in secondary loops occurring along the stem of the molecule (Fig. 6).
We predicted pre-miRNA secondary structure at both 5°C and 20°C, which represents a sampling of the temperature extremes Arabidopsis might be expected to experience during its lifecycle. Of the pre-miRNA SNPs, 33 (53%) were predicted to alter pre-miRNA secondary structure at both temperatures relative to the Col-0 pre-miRNA allele (Fig. 6). All predicted secondary structure changes were subtle (i.e. addition or subtraction of small loops along the stem; two nucleotide enlargement or shrinking of primary or secondary stem loops) and appeared to maintain the general integrity of the pre-miRNA stem-loop molecule. SNPs disrupting secondary structure occurred in all structural contexts of pre-miRNAs (Fig. 6). For 26 SNPs (42% of all pre-miRNA SNPs), pre-miRNA secondary structure was entirely maintained across pre-miRNA alleles. Ten of these SNPs had no structural effect because they occurred within loops. The other 16 SNPs that did not affect secondary structure were all located along the pre-miRNA stem and fell into one of five classes (SNP counts in parentheses): (1) occurring within mismatch positions (two SNPs), (2) creating a nondisruptive mismatch from a match (seven SNPs), (3) creating a match from a nondisruptive mismatch (one SNP), (4) a purine transition (A G) with the pairing base a U (three SNPs), and (5) a pyrimidine transition (C U) with the pairing base a G (three SNPs). Three SNPs (5% of all SNPs) had predicted structural effects at 5°C, but not at 20°C. These SNPs occur in a loop in miR156d, at an A G with U pairing site (class 4) in miR157c, and at a C U with G pairing site (class 5) in miR164a.
To more quantitatively assess the effects of SNPs on pre-miRNA stability, we next measured
Posttranscriptional regulation of gene expression is a common phenomenon across eukaryotes, but the extent to which variability in this process contributes to diversity in gene expression and phenotype is unclear (Chen and Rajewsky, 2007
MiRNAs in the model plant Arabidopsis have been implicated in several developmental processes, including flowering time (Aukerman and Sakai, 2003
Overall, our results support that, like in humans, the predominant force acting on Arabidopsis miRNAs and their targets is purifying selection. Despite the presence of more copies of each mature miRNA sequence in the Arabidopsis genome than in the human genome and the smaller number of mRNA targets per miRNA in plants, plant miRNAs exhibit very strong purifying selection comparable to that observed in humans (Saunders et al., 2007
The degree of purifying selection on miRNAs and their target binding sites can be assessed by comparing levels of variation at miRNAs and their targets to levels of amino-acid-changing variation in protein-coding genes. The mean level of nonsynonymous polymorphism ( The strong sequence constraint of miRNAs and their binding sites suggest that evolutionary changes in these sequences are unlikely to be major contributors to natural variation in Arabidopsis. We have, however, identified a small number of rare miRNA and target site polymorphisms that may have functional effects, and have shown that substantial flanking variation exists both within Arabidopsis and between it and A. lyrata. Overall, our results imply that the roles of miRNA-target interactions in plant function are essential and are subject to strong purifying selection, but that variation flanking these sites could contribute to regulatory diversity at these genes and their downstream targets.
Empirical and computational approaches have shown that pre-miRNA secondary structure is important to the processing and maturation of miRNAs (Zeng et al., 2005
Of note is that most detected pre-miRNA polymorphisms appear to have a destabilizing effect on RNA secondary structure because the majority of the studied loci have nonzero MiRNAs comprise a key class of regulatory loci in eukaryotic systems, and we are beginning to understand the evolutionary forces that govern the diversification of these genes. Our work suggests that despite fundamental differences in miRNA-based regulation, miRNAs and their targets are similarly constrained in both plants and animals. The possibility of variation in cis-regulation or processing of miRNAs in Arabidopsis and other species merits further attention, though documenting such functional variation, if it exists, will be technically challenging due to the presence of multiple copies of many mature miRNAs. We have shown, however, that the raw material for such variation does exist in Arabidopsis and that it may be responsive to temperature, laying the groundwork for future experiments focused on potential molecular functional variation at miRNAs in Arabidopsis.
PCR and DNA Sequencing
miRNAs and binding targets were chosen as a subset of those listed in Jones-Rhoades et al. (2006)
Sequences were initially aligned and edited using the Phred and Phrap programs (Codon Code) and BioLign version 2.09.1 (Tom Hall, Ibis Therapeutics). Additional manual alignment and polymorphism identification were conducted in BioEdit version 7.0.5 (Tom Hall, Ibis Therapeutics). Reported summary statistics were calculated in either Microsoft Excel, DnaSP version 4.1.0 (Rozas et al., 2003
The program mfold v2.3 was used to predict the pre-miRNA secondary structure and the Sequence data from this article can be found in the GenBank/EMBL data libraries under accession numbers EU549868 to EU551085 (miRNAs) and EU548273 to EU549692 (binding sites).
The following materials are available in the online version of this article.
We thank Daisuke Saisho and members of the Purugganan laboratory for assistance with this project and manuscript. We also thank Kevin Chen for reading a draft of this manuscript. Received January 20, 2008; accepted February 19, 2008; published February 27, 2008.
1 This work was supported by a U.S. Department of Education Graduate Assistance in Areas of National Need Fellowship and a National Science Foundation Graduate Research Fellowship (to I.M.E.), and by grants from the National Science Foundation Frontiers in Integrated Biological Research and Plant Genome Research Programs and the U.S. Department of Defense (to M.D.P.). The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Ian M. Ehrenreich (ehrenreich{at}ncsu.edu).
[W] The online version of this article contains Web-only data. www.plantphysiol.org/cgi/doi/10.1104/pp.108.116582 * Corresponding author; e-mail ehrenreich{at}ncsu.edu.
Abelson JF, Kwan KY, O'Roak BJ, Baek DY, Stillman AA, Morgan TM, Mathews CA, Pauls DL, Rasin MR, Gunel M, et al (2005) Sequence variants in SLITRK1 are associated with Tourette's syndrome. Science 310: 317–320 Achard P, Herr A, Baulcombe DC, Harberd NP (2004) Modulation of floral development by a gibberellin-regulated microRNA. Development 131: 3357–3365 Aukerman MJ, Sakai H (2003) Regulation of flowering time and floral organ identity by a microRNA and its APETALA2-like target genes. Plant Cell 15: 2730–2741 Axtell MJ, Bartel DP (2005) Antiquity of microRNAs and their targets in land plants. Plant Cell 17: 1658–1673 Bonnet E, Wuyts J, Rouze P, Van de Peer Y (2004) Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativa identifies important target genes. Proc Natl Acad Sci USA 101: 11511–11516 Carrington JC, Ambros V (2003) Role of microRNAs in plant and animal development. Science 301: 336–338 Chamary JV, Hurst LD (2005) Evidence for selection on synonymous mutations affecting stability of mRNA secondary structure in mammals. Genome Biol 6: R75[CrossRef][Medline] Chen K, Rajewsky N (2006) Natural selection on human microRNA binding sites inferred from SNP data. Nat Genet 38: 1452–1456[CrossRef][Web of Science][Medline] Chen K, Rajewsky N (2007) The evolution of gene regulation by transcription factors and microRNAs. Nat Rev Genet 8: 93–103[Web of Science][Medline] Clop A, Marcq F, Takeda H, Pirottin D, Tordoir X, Bibe B, Bouix J, Caiment F, Elsen JM, Eychenne F, et al (2006) A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep. Nat Genet 38: 813–818[CrossRef][Web of Science][Medline] Emery JF, Floyd SK, Alvarez J, Eshed Y, Hawker NP, Izhaki A, Baum SF, Bowman JL (2003) Radial patterning of Arabidopsis shoots by class III HD-ZIP and KANADI genes. Curr Biol 13: 1768–1774[CrossRef][Web of Science][Medline] Enard W, Khaitovich P, Klose J, Zollner S, Heissig F, Giavalisco P, Nieselt-Struwe K, Muchmore E, Varki A, Ravid R, et al (2002) Intra- and interspecific variation in primate gene expression patterns. Science 296: 340–343 Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM, Cumbie JS, Givan SA, Law TF, Grant SR, Dangl JL, et al (2007) High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PLoS ONE 2: e219[CrossRef][Medline] Fay JC, Wu CI (2000) Hitchhiking under positive Darwinian selection. Genetics 155: 1405–1413 Floyd SK, Bowman JL (2004) Gene regulation: ancient microRNA target sequences in plants. Nature 428: 485–486[CrossRef][Medline] Gottwein E, Cai X, Cullen BR (2006) A novel assay for viral microRNA function identifies a single nucleotide polymorphism that affects Drosha processing. J Virol 80: 5321–5326 Griffiths-Jones S (2004) The microRNA Registry. Nucleic Acids Res 32: D109–111 Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34: D140–144 Grun D, Wang YL, Langenberger D, Gunsalus KC, Rajewsky N (2005) microRNA target predictions across seven Drosophila species and comparison to mammalian targets. PLoS Comput Biol 1: e13[Medline] Jin W, Riley RM, Wolfinger RD, White KP, Passador-Gurgel G, Gibson G (2001) The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat Genet 29: 389–395[CrossRef][Web of Science][Medline] Jones-Rhoades MW, Bartel DP (2004) Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell 14: 787–799[CrossRef][Web of Science][Medline] Jones-Rhoades MW, Bartel DP, Bartel B (2006) MicroRNAS and their regulatory roles in plants. Annu Rev Plant Biol 57: 19–53[CrossRef][Medline] Katz L, Burge CB (2003) Widespread selection for local RNA secondary structure in coding regions of bacterial genes. Genome Res 13: 2042–2051 King MC, Wilson AC (1975) Evolution at two levels in humans and chimpanzees. Science 188: 107–116 Kirby DA, Muse SV, Stephan W (1995) Maintenance of pre-mRNA secondary structure by epistatic selection. Proc Natl Acad Sci USA 92: 9047–9051 Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, et al (2005) Combinatorial microRNA target predictions. Nat Genet 37: 495–500[CrossRef][Web of Science][Medline] Lall S, Grun D, Krek A, Chen K, Wang YL, Dewey CN, Sood P, Colombo T, Bray N, Macmenamin P, et al (2006) A genome-wide map of conserved microRNA targets in C. elegans. Curr Biol 16: 460–471[CrossRef][Web of Science][Medline] Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120: 15–20[CrossRef][Web of Science][Medline] Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB (2003) Prediction of mammalian microRNA targets. Cell 115: 787–798[CrossRef][Web of Science][Medline] Li A, Mao L (2007) Evolution of plant microRNA gene families. Cell Res 17: 212–218[Web of Science][Medline] Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, Spielman RS, Cheung VG (2004) Genetic analysis of genome-wide variation in human gene expression. Nature 430: 743–747[CrossRef][Medline] Nikovics K, Blein T, Peaucelle A, Ishida T, Morin H, Aida M, Laufs P (2006) The balance between the MIR164A and CUC2 genes controls leaf margin serration in Arabidopsis. Plant Cell 18: 2929–2945 Nordborg M, Hu TT, Ishino Y, Jhaveri J, Toomajian C, Zheng H, Bakker E, Calabrese P, Gladstone J, Goyal R, et al (2005) The pattern of polymorphism in Arabidopsis thaliana. PLoS Biol 3: e196[CrossRef][Medline] Oleksiak MF, Churchill GA, Crawford DL (2002) Variation in gene expression within and among natural populations. Nat Genet 32: 261–266[CrossRef][Web of Science][Medline] Oleksiak MF, Roach JL, Crawford DL (2005) Natural variation in cardiac metabolism and gene expression in Fundulus heteroclitus. Nat Genet 37: 67–72[Web of Science][Medline] Olsen KM, Caicedo AL, Polato N, McClung A, McCouch S, Purugganan MD (2006) Selection under domestication: evidence for a sweep in the rice waxy genomic region. Genetics 173: 975–983 Pasquinelli AE, Reinhart BJ, Slack F, Martindale MQ, Kuroda MI, Maller B, Hayward DC, Ball EE, Degnan B, Muller P, et al (2000) Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA. Nature 408: 86–89[CrossRef][Medline] Rajewsky N (2006) microRNA target predictions in animals. Nat Genet (Suppl) 38: S8–S13[CrossRef] Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP (2002) Prediction of plant microRNA targets. Cell 110: 513–520[CrossRef][Web of Science][Medline] Rifkin SA, Kim J, White KP (2003) Evolution of gene expression in the Drosophila melanogaster subgroup. Nat Genet 33: 138–144[CrossRef][Web of Science][Medline] Ritchie W, Legendre M, Gautheret D (2007) RNA stem-loops: to be or not to be cleaved by RNAse III. RNA 13: 457–462 Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19: 2496–2497 Rozen S, Skaletsky H (2000) Primer3 on the www for general users and for biologist programmers. In S Krawetz, S Misener, eds, Bioinformatics Methods and Protocols: Methods for Molecular Biology. Humana Press, Totowa, NJ, pp 365–386 Saunders MA, Liang H, Li WH (2007) Human polymorphism at microRNAs and microRNA target sites. Proc Natl Acad Sci USA 104: 3300–3305 Schmid KJ, Ramos-Onsins S, Ringys-Beckstein H, Weisshaar B, Mitchell-Olds T (2005) A multilocus sequence survey in Arabidopsis thaliana reveals a genome-wide departure from a neutral model of DNA sequence polymorphism. Genetics 169: 1601–1615 Schwab R, Ossowski S, Riester M, Warthmann N, Weigel D (2006) Highly specific gene silencing by artificial microRNAs in Arabidopsis. Plant Cell 18: 1121–1133 Schwab R, Palatnik JF, Riester M, Schommer C, Schmid M, Weigel D (2005) Specific effects of microRNAs on the plant transcriptome. Dev Cell 8: 517–527[CrossRef][Web of Science][Medline] Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123: 585–595 Vilella AJ, Blanco-Garcia A, Hutter S, Rozas J (2005) VariScan: analysis of evolutionary patterns from large-scale DNA sequence polymorphism data. Bioinformatics 21: 2791–2793 Walter AE, Turner DH, Kim J, Lyttle MH, Muller P, Mathews DH, Zuker M (1994) Coaxial stacking of helixes enhances binding of oligoribonucleotides and improves predictions of RNA folding. Proc Natl Acad Sci USA 91: 9218–9222 Watterson GA (1975) On the number of segregating sites in genetical models without recombination. Theor Popul Biol 7: 256–276[CrossRef][Web of Science][Medline] Whitney AR, Diehn M, Popper SJ, Alizadeh AA, Boldrick JC, Relman DA, Brown PO (2003) Individuality and variation in gene expression patterns in human blood. Proc Natl Acad Sci USA 100: 1896–1901 Wu G, Poethig RS (2006) Temporal regulation of shoot development in Arabidopsis thaliana by miR156 and its target SPL3. Development 133: 3539–3547 Zeng Y, Yi R, Cullen BR (2005) Recognition and cleavage of primary microRNA precursors by the nuclear processing enzyme Drosha. EMBO J 24: 138–148[CrossRef][Web of Science][Medline] Zhang B, Wang Q, Pan X (2007) MicroRNAs and their regulatory roles in animals and plants. J Cell Physiol 210: 279–289[CrossRef][Web of Science][Medline] Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31: 3406–3415 This article has been cited by other articles:
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