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• Arabidopsis Root miR390 tas3, arf Root development Montgomery et al. (2008), Marin et al. (2010), Yoon et al. (2010)
• Arabidopsis Root, leaf, flower, seed miR164 nac1, cuc2 Lateral root emergence, leaf morphology, petal development regulation, floral meristem activity, seed development Mallory et al. (2004), Laufs et al. (2004), Guo et al. (2005), Nikovics et al. (2006), Jung et al. (2009) Arabidopsis, rice, barley Root, seed miR160 arf10, arf16
• Lateral root initiation, seed development Mallory et al. (2005), Sorin et al. (2005), Xue et al. (2009), Kantar et al. (2010), Nodine and Bartel ( 2010) Arabidopsis, rice, barley, opium poppy Root, flower miR171 scl6
• Root and flower development Xue et al. (2009), Kantar et al. (2010), Unver et al. (2010b) Arabidopsis Leaf, vascular system, flower, seed miR165/166 hd-zip III gene family, phb, phv
• Leaf development and morphology, meristem, seed development Mallory et al. (2004), Kim et al. (2005), Williams et al. (2005), Zhang et al. (2006b) Antirrhinum majus, Arabidopsis Leaf, seed, flower miR159 cin, tcp, gamyb
• Leaf morphogenesis, seed development and germination, flowering time regulation, reproductive development Palatnik et al. (2003), Chen (2005), Allen et al. ( 2007), Jung et al. (2009) Arabidopsis, rice, poplar Leaf, flower, seed miR156 and miR157 sbp box
• Leaf morphogenesis, phase transition, flowering time regulation, seed development Rhoades et al. (2002), Wu and Poethig (2006), Gandikota et al. (2007), Wang et al. (2008), Nodine and Bartel (2010), Zhao et al. (2010), Wang et al. (2011a), Kim et al. (2012) Arabidopsis Leaf miR396 grf Leaf development
• Liu et al. (2009), Rodriguez et al. (2010) Peanut Root and leaf miR3508 ppo
• Root and leaf development Chi et al. (2011) Arabidopsis, rice, maize Flower miR172 toe1, toe2, toe3, ids1, gloy15
• Flowering time, vegetative phase change Aukerman and Sakai (2003), Lauter et al. (2005), Chuck et al. (2007), Yang et al. (2007) Opium poppy Flower miR169 cbf-b/nf-ya Flowering time Unver et al. (2010b) Arabidopsis, rice Flower, root, seed miR167 arf6, arf8
• Root elongation, gynoecium and stamen development, seed development Gutierrez et al. (2009), Jung et al.
• (2009), Xue et al. (2009), Vidal et al. (2010) Arabidopsis, rice Flower miR444 mads-box Flower development Li et al. (2010) Rice Seed miR397 and miR528 ao Seed development Xue et al. (2009)
• Arabidopsis, tomato Seed, leaf miR319 tcp4, lanceolate Seed development, leaf development and morphology Palatnik et al. (2003), JonesRhoades et al. (2006), Efroni et al. (2008), Nodine and Bartel ( 2010 ), Shleizer-Burko et al. (2011) Soybean Seed miR1530 tkt Seed development Song et al. (2011)
• Table Common miRNA related with stress response in plants. Plant Stress miRNA Target genes and proteins References Arabidopsis, barley, rice, Populus Drought, salt, cold, fungal pathogen miR156 SBP family TFs Liu et al. (2008), Lu et al. (2008), Kantar et al. (2010), Zhou et al. (2010), Li et al. (2011), Xin et al. (2011), Arabidopsis, bean Drought, ABA, salt, bacterial pathogen miR159 MYB33 and MYB101, MYB33 and MYB65 TFs Reyes and Chua (2007); Frazier et al. (2011), Alonso-Peral et al. (2012)
• Populus, maize, rice Drought, salt miR162 dcl1 Zhou et al. (2010), Li et al. (2011a)
• Populus Mechanical stress miR164 NAC TFs Lu et al. (2005) Arabidopsis, barley, soybean, wheat, maize
• Liu et al. (2008), Zhou et al. (2008), Lv et al. (2010), Ding et al. (2009), Kantar et al. (2010), Xin et al. (2011), Li et al. (2011b), Zhang et al. (2011a) Arabidopsis, maize, rice
• Drought, salt, cold, nutrient deprivation, bacterial pathogen miR167 ARF6 and ARF8 TFs Liu et al. (2008), Li et al. (2010), Lv et al. (2010), Zhou et al.
• (2010), Frazier et al. (2011), Zhang et al. (2011a), Sunkar et al. (2012), Arabidopsis, rice, Populus, wheat
• Drought, salt, cold, heat miR168 ago1 Liu et al. (2008), Lu et al. (2008), Zhou et al. (2010), Xin et al. (2011) Arabidopsis, rice Drought, salt, cold miR169
• NF subunit Y, CCAAT-BOX Binding Factors Zhao et al. (2007), Zhang et al. (2009), Li et al. (2010), Frazier et al. (2011) Arabidopsis, Populus, barley, rice
• Drought, mechanical, salt, cold miR171 SCL TFs Reyes et al. (2007), Liu et al. (2008), Kantar et al. (2010), Lv et al. (2010), Frazier et al. (2011) Arabidopsis, Populus, barley, rice Cold, drought miR172 AP2 TF
• Liu et al. (2008), Zhang et al. (2009), Frazier et al. (2011), Xin et al. (2011) Arabidopsis, rice
• Salt, drought, cold, bacterial pathogen miR319 TCP family TFs Liu et al. (2008), Lv et al. (2010), Zhang et al. (2011a) Arabidopsis, Populus
• Cold, bacterial pathogen, drought miR390, miR476 GLUTAMATE RECEPTOR proteins Liu et al. (2008), Lu et al. (2008), Lv et al. (2010), Zhang et al. (2011a) Arabidopsis, rice, wheat
• Salt, heat, cold, ABA, drought, nutrient deprivation, bacterial and fungal pathogen miR393 F-BOX protein, TRANSPORT INHIBITOR RESPONSE1 protein, tir1, afb2, and afb3 genes Navarro et al. (2006), Reyes et al. (2007), Zhao et al. (2007), Liu et al. (2008), Arenas-Huertero et al. (2009), Li et al.
• (2010), Frazier et al. (2011), Xin et al. (2011), Sunkar et al. (2012) Arabidopsis, rice
• Nutrient deprivation, drought miR395 aps Bartel (2004), Rhoades and Bartel (2004), Zhou et al. (2010) Arabidopsis, barley Drought, salt, cold miR396 GRF family TFs
• Liu et al. (2008), Kantar et al. (2010), Chi et al. (2011), Frazier et al. (2011) Arabidopsis, rice, soybean, Brachypodium Cold, ABA, salt miR397b LACCASEs
• Sunkar and Zhu (2004), Zhao et al. (2007), Liu et al. (2008), Zhang et al. (2009), Zhang et al. (2009) Arabidopsis
• Nutrient deprivation, oxidative stress, bacterial pathogen miR398 csd1, csd2, ccs1, cox5b.1 Sunkar et al. (2006, 2012), Abdel-Ghany et al. (2008), Gifford et al. (2008), Trindade et al. (2010), (Li et al. 2010a), Li et al. (2011c), Zhang et al. (2011a), Zhu et al. (2011) Arabidopsis
• Nutrient deprivation miR399 ubc Lu and Huang (2008) Arabidopsis Cold, ABA, salt miR402 DML3, ARGONAUTE 2
• Sunkar and Zhu (2004), Zhou et al. (2008) Populus, barley
• Mechanical stress, drought miR408 PLANTACYANIN Lu et al. (2005), Kantar et al.
• (2010), Trindade et al. (2010) Populus Cold miR474 PPRs Lu et al. (2008) Rice Cadmium stress miR166 Homeodomain-leucine Zipper (HD-Zip) TFs Ding et al. (2011) Rice Aluminum stress miR528 F-BOX/LRR-MAX2 Lima et al. (2011) Arabidopsis Bacterial miR825
• REMORINA, ZF, homeobox Li et al. (2010a). Arabidopsis Drought, ABA miR2118 Unknown gene
• Arenas-Huertero et al. (2009) hormone forms the lateral root development through transcription factors of the auxin response factor (ARF) family (Moreno-Risueno et al. 2010). Several miRNAs connect with auxin signaling (Rubio-Somoza et al. 2009): for lateral root initiation, miR164 targeting nac1 (Mallory et al. 2004; Guo et al. 2005) and miR160 targeting arf10/ arf16/arf17 play regulatory roles (Xue et al. 2009), while miR390 targeting tas3-arf genes (Marin et al. 2010; Yoon et al. 2010), miR167 targeting arf8, and miR393 targeting afb3 (Vidal et al. 2010) provide proper root elongation.
• Arabidopsis miR164 targets nac1 gene transcript, which transduces auxin signals for lateral root emergence. In loss-of-function miR164 mutants, nac1 mRNA level was found to be accumulated and resulted in more lateral roots. Conversely, miR164 overexpressor Arabidopsis showed decreased lateral root emergence with suppressed nac1 mRNA level (Guo et al. 2005). Another miRNA is miR160, functioning in root development and growth. The arf10, arf16, and arf17 mRNAs are targets of miR160 and their expression levels increase in loss-of-function miR160
• Arabidopsis. Through miR160 suppression, several developmental defects including rooting formation were observed (Mallory et al. 2005). Additionally, miR160resistant plants cause root tip defects (Wang et al. 2005).
• The miR167 targets arf6 and arf8. The arf6 induces miR160 to repress arf17. In contrast, arf17 may activate miR167 to coordinate arf6 and arf8 expression and root development (Table 1). Therefore, miR160 and miR167 targets have opposite roles in auxin regulation (Gutierrez et al. 2009). Leaf development
• Leaf morphogenesis and development are also regulated by miRNAs (Palatnik et al. 2003). Studies have identified some miRNAs that are related to leaf development such as miR396 (Liu et al. 2009; Rodriguez et al. 2010), miR319
• (Schommer et al. 2008), miR164a (Nikovics et al. 2006), and miR156 (Wang et al. 2008). The Arabidopsis miRNA, miR396, has been found to be a regulator of plant-specific transcription factor (growth regulating factor) genes
• (Jones-Rhoades and Bartel 2004). Smaller leaf size occurred upon overexpression of miR396 in Arabidopsis (Liu et al. 2009), and the miR396-resistant grf2 provided bigger leaf size as compared to the wild type (Rodriguez et al. 2010).
• The miR396 antagonizes the expression of grf2 in the distal part of the leaf, attenuating cell proliferation in developing leaves by down-regulation of GRF activity. Its expression is also found at low level in meristem to regulate cell proliferation and size (Rodriguez et al. 2010). The miR319, also called miRJAW in Arabidopsis, regulates tcp genes, which are plant-specific transcription factors involved in leaf development (Palatnik et al. 2003; Schommer et al. 2008). The tcp4 mRNA is targeted to be cleaved by miR319, and expression of miR319-resistant tcp4 in Arabidopsis resulted in abnormal leaf morphology (Palatnik et al. 2003;
• Efroni et al. 2008). Moreover, overexpression of miR319 in tomato produced super-compound leaves (Ori et al. 2007). The tomato tcp homolog lanceolate gene expression correlated with diverse type of leaf shapes (ShleizerBurko et al. 2011). Interestingly, the lanceolate escaped from miR319 regulation via differential expression level.
• Therefore, stage-specific expression of miR319 or a repressor version of lanceolate resulted in different leaf shapes (Shleizer-Burko et al. 2011). The cincinnata (cin) gene from snapdragon (Antirrhinum majus) encodes a member of the TCP family of transcription factors, required for the differential regulation of cell division during leaf morphogenesis to form a flat leaf (Nath et al. 2003). Mutation in the cin gene resulted in morphological changes (Crawford et al. 2004). The Arabidopsis genome contains at least 2 regions with the potential to produce miRJAW, as well as several potential precursors for a family of 3 almost identical miRNAs (miR159a–c) that are related to miRJAW (Palatnik et al. 2003). miR165/166 and miR159/JAW are essential for controlling the pattern and development of leaves by direct regulation of 2 classes of transcription factor genes (hd-zip and tcp) (Zhang et al. 2006a). In addition, miR156a and miR157a, located on chromosome 2 and chromosome 1, respectively, target mRNA coding for the squamosa promoter-binding protein (Sbp) box, which is involved in leaf morphogenesis
• (Table 1) (Zhao et al. 2010). The miR396 targets GRF transcription factors required for coordination of cell division and differentiation during leaf development in Arabidopsis (Chi et al. 2011). In peanut, a legume-specific miRNA, miR3508, targets polyphenol oxidase (ppo) genes in the roots and leaves. PPO is localized on the thylakoids of chloroplasts and in vesicles or other bodies in nongreen plastid types, and catalyzes the oxygen-dependent oxidation of phenols to quinones (Chi et al. 2011).
• Vascular development Vascular development is initiated by the formation of provascular cells that subsequently develop into procambium, from which both conducting tissues are eventually differentiated (Jung et al. 2008; Donner et al. 2009).
• A subset of class III homeodomain-leucine zipper (HD-ZIP III) transcription factors play a role in vascular development. In Arabidopsis, the hd-zip III gene family includes 5 members: athb15, athb8, phavoluta (phv), phabulosa (phb), and revoluta (rev), which are regulated by miR165 and miR1 The athb15 and athb8 are predominantly expressed in vascular tissue, suggesting that they may have some role in vascular development. The athb15 mRNA is cleaved in standard wheat germ extracts and in Arabidopsis, and its cleavage is mediated by miR166 in Nicotiana benthamiana cells. Overexpression of miR166a resulted in decreasing athb15 mRNA levels and caused accelerated vascular cell differentiation from cambial/procambial cells, and consequently produced an altered vascular system with expanded xylem tissue and an interfascicular region. The miR166/165 complementary sequence is highly conserved in mRNAs of athb15 and its gene homologs from various plant species. It is, therefore, likely that miR166-mediated hd-zip III gene repression is conserved in all vascular plants (Kim et al. 2005; Zhang et al. 2006a). Flower development
• The genes required for proper flower development and timing are regulated by miRNAs. Gain-of-function and loss-of-function analyses indicated that 2 of the ap2like target genes normally act as floral repressors, which are regulated by miR172. Early flowering and disrupted floral organ identity phenotypes were obtained in miR172 overexpressing plants (Zhu et al. 2010). Several ap2-like genes such as target of eat1 (toe1), toe2, and toe3 genes in
• Arabidopsis, and indeterminate spikelet1 (ids1) and gloy15 in Zea mays are also regulated by miR172 (Lauter et al. 2005). The ap2 gene mutants result in the same morphology and improper flowering time (Aukerman and Sakai 2003;
• Chen 2004). The loss-of-function toe1-1 mutation results in slightly early flowering and the toe1-1 toe2-1 double mutant flowers much earlier than the wild type. On the other hand, overexpression of toe1 (toe1-1D) leads to delayed flowering, while overexpression of miR172 from the 35S promoter causes early flowering, and overcomes the late flowering phenotype of toe1-1D (Yang et al. 2007). The role of miR164 in flowering was determined by loss-of-function allele (Guo et al. 2005). The early extra petals1 (Eep1) phenotype, caused by a transposon insertion of miR164c, resulted in flowers with extra petals in Arabidopsis. The transcription factor
• CUC1 and CUC2 accumulation upon miR164c mutation led to flower development defects (Baker et al., 2005).
• The roles of miR165/166 in floral structure architecture were also discovered. The miR165/166-overproducing Arabidopsis plants have floral development defects the same as men1 and jba-1D mutants (Williams et al. 2005; Jung et al. 2007). Auxin signals are found to be closely related to floral organogenesis. The miR167 targets arf6 and arf8, which play a role in gynoecium and stamen development and fertility. Overexpression of miR167 causes defects in floral organ development (Wu et al. 2006). In opium poppy, miR169b and miR169n target CCAAT-binding transcription factor (Cbf-b/Nf-ya) regulating flowering time, and miR171 targets a plant-specific scarecrow-like transcription factor 6 (SCL6) regulating floral development (Unver et al. 2010b). Phase transition
• In plants, the timing of phase transition between the vegetative phase and the reproductive phase is tightly controlled. Regulation and control of the phase change are both dependent on endogene expression and environmental signals. Genetic studies have discovered positive and negative regulators of phase transition control. A group of genes encoding squamosa promoter-binding protein-like (SPL) transcription factors, such as SPL3, SPL4, and SPL5 responsible for initiation of flowering, are negatively regulated by miR156 (Jones-Rhoades et al. 2002; Wu and Poethig 2006; Gandikota et al. 2007; Wang et al. 2008). Mutations of the genes related to miRNA biogenesis and transport result in altered juvenile-to-adult vegetative phase change and vegetative-to-reproductive phase change. Overexpression of the miR156a gene causes late flowering and delays in vegetative phase change in Arabidopsis (Wu and Poethig 2006; Shikata et al. 2009), rice (Xie et al. 2005), and poplar (Wang et al. 2011a). On the other hand, overexpression of miR156-resistant spl3/4/5 genes results in early flowering (Kim et al. 2012).
• The endogenous level of miR156 is temporally regulated, which is very high in the early juvenile vegetative phase but decreases rapidly before the onset of the adult juvenile phase (Wu and Poethig 2006). miR156 also targets spl9 and spl15 genes responsible for shoot maturation (Kantar et al. 2010). Additionally, it has been detected that SPL13 represses the phase transition in the miR156-resistant version of spl13 (rspl13) in Arabidopsis (Martin et al. 2010). The transition from juvenile to adult leaf identity is also controlled by miR172 targeting the apetala2 class of transcription factors (Chen 2004). The maize mutant glossy15, miR172-target ap2 gene mutant (Lauter et al. 2005), shows the characteristics of adult leaf cells in the juvenile phase. The glossy15 mRNA is accumulated in juvenile leaves and decreased in mature leaves. On the other hand, the level of miR172 became detectable only when leaves started showing adult characteristics and gradually increased subsequently (Lauter et al. 2005; Chuck et al. 2007). Seed development
• Seed development in plants initiates with tissue differentiation at early stages, and maturation programs provide seed desiccation, dispersal, and germination in later phases. A number of transcription factors and genes are involved in regular seed development and maturation programs requiring transcriptional, post-transcriptional, and post-translational regulations. Therefore, miRNAbased transcriptional regulation is also critical for normal seed development. Plants with loss-of-function in miRNA biogenesis and function generate acute embryonic defects and lethality. Several studies indicated the roles of miRNA in embryogenesis and seed development (Wu et al. 2006;
• Yang et al. 2006; Allen et al. 2007; Bowman and Floyd 2008;
• Nodine and Bartel 2010; Willmann et al. 2011). The genes related to miRNA biogenesis are found to be responsible for regular seed development, e.g. dcl1-15 mutants mature earlier (Willmann et al. 2011). The 2 genes, lec2 (Leafycotyledon2) and fus3 (Fusca3), responsible for seed maturation were detected as increased in dcl1-15 mutants.
• It has been observed that Dcl1 represses fus3 and lec2 in the embryo during early embryogenesis. On the other hand, double mutant phenotypic analyses showed that lec2-1 and dcl1-15 as well as fus3-3 and dcl1-15 double mutants reduced the dcl1-15 phenotypes. Therefore, LEC2 and FUS3 are essential for the early maturation phenotype of dcl1-15. The SE and HYL1 proteins are required for miRNA processing (Laubinger et al. 2008). It has been detected that either se or hyl1 mutations in Arabidopsis have elevated levels of pri-miRNA, reduced levels of miRNA, and abnormal embryo development (Yang et al. 2006). The miR168 targets ago1 mRNA (Jones-Rhoades et al. 2002), which is essential for miRNA biogenesis and appropriate embryo development. The miR168 resistant ago1 mutants, accumulating the ago1 mRNA, present a phenotype similar to that of dcl1, hen1, and hyl1 mutants (Vaucheret et al. 2004). Another study related to miRNA regulation of embryo development in plants showed that the dcl1 mutant
• Arabidopsis overexpresses ~50 miRNA targets. Of those, 9 genes encoding transcription factors were up-regulated around the 8-cell-embryo stage in this mutant. These genes are predicted to be the targets of miR156, miR159, miR160, miR166, miR319, or miR824. An additional 6 targets of miR168, miR393, miR400, or miR778 were up-regulated at the globular stage. Therefore, the miRNA regulation is essential for proper embryo patterning (Nodine and Bartel 2010). Auxin plays crucial roles during seed development.
• Its level and regulation of auxin-responsive genes are important for pattern formation during embryogenesis (Bowman and Floyd 2008). The mutation of arf2 causes increased seed size and weight in Arabidopsis (Xue et al. 2009). The miR164 targets 5 members of Nac (No apical meristem; Ataf1/2; and Cup-shaped cotyledon2)-domain transcription factors important for suitable patterning in early embryogenesis. The miR164-resistant cuc1 results in alterations in embryonic development (Mallory et al. 2004). The seed size and seed development are affected by the miRNA159/miR319 family. The mir159ab double mutant seeds have reduced size and irregular shape because of gamyb gene deregulation (Allen et al. 2007). The myb33 and myb101 mRNAs regulating seed germination are suppressed by miR159 activity. Overexpression of miR159 results in hyposensitivity to abscisic acid (ABA) during seed germination, which is also observed in the myb33 and myb101 mutants (Jung et al. 2009). Overexpression of miR166g targeting HD-ZIP transcription factors results in seedling arrest (Williams et al. 2005) in Arabidopsis.
• Stress responsive microRNAs in plants Plants are exposed to serious biotic and abiotic stresses such as drought, salinity, alkalinity, cold, pathogen infections, and diseases, which are the predominant cause of decreased crop yields. Plants use adaptive responses operating at the transcriptional, post-transcriptional, translational, and post-translational levels to cope with these environmental challenges (Sunkar 2012). As a post-transcriptional gene regulator, a number of miRNAs (Table 2) play roles in multiple stress responses in plants. There is much evidence showing the direct link between miRNA regulation and stress response in plants. Expression of plant miRNAs has been detected as up- and down-regulated levels upon treatment of diverse stress conditions. Since some of the genes related to stress response are post-transcriptionally regulated by miRNAs, the NFYA5 transcription factor, which promotes drought resistance in Arabidopsis (Li et al. 2008), is found to be regulated by miR169 (Li et al. 2008;
• Trindade et al. 2010). Another differentially expressed miRNA upon stress is miR528, which targets copper ion binding protein genes, and its expression has been found to be increased in glyphosate (an herbicide) inoculated tolerant festuca plant leaves (Unver et al. 2010a). Although many studies have been conducted on the functions of miRNAs on stress regulation in plants, we discuss some of the stress conditions and regulation of miRNAs here. Drought stress
• Drought is a major limitation for plant development and productivity. Several genomics studies including expression level measurements and transgenic approaches have been applied to better investigate drought tolerance mechanism in plants. To date, many genes related to water deficiency tolerance were identified (Ni et al. 2009).
• Additionally, a number of studies examining miRNA regulation on drought tolerance in plants have obtained valuable information. For example, miR167, miR168, miR171, and miR396 were found to be drought stress responsive miRNAs in Arabidopsis (Liu et al. 2008). Moreover, miR159-regulated myb33 and myb101 were identified as important genes playing roles in response to ABA accumulation under drought stress (Reyes and Chua 2007). The miR169 targets the Nfya5 transcription factor, and is down-regulated upon water deficiency (Li et al. 2008). Overexpression of a miR169-resistant nfya5 transgene significantly improves drought tolerance by promoting stomatal closure under drought stress (Li et al. 2008). The miR169 also targets 8 NF transcription factor
• Y subunit mRNAs in rice (Li et al. 2010b). Trindade et al. (2010) reported that the levels of miR398 and miR408 are increased in Medicago truncatula plants upon water deficiency and then cause down-regulation of their respective targets, cox5b and plantacyanin, suggesting that these miRNAs play a role in regulating M. truncatula responses to drought stress. Some of the barley miRNAs, such as miR156, miR166, miR171, and miR408, were observed as differentially expressed upon dehydration (Kantar et al. 2010). The expression of miR159.2, miR1514, miR2118, and miR2119 was induced in Phaseolus vulgaris by abiotic stress, especially drought and ABA treatment
• (Arenas-Huertero et al. 2009). Moreover, expression of miR102, miR156, miR162, miR167, and miR473 was upregulated under drought-influenced conditions in poplar
• (Li et al. 2011a) (Table 2). Salt stress
• Salt stress is another important constraint for plants. It negatively affects plant growth and productivity all over the world. To date, several studies have been performed to measure and detect the differential expression level of plant miRNA upon salt treatment. In an expression-based study, Liu et al. (2008) reported that several miRNA, such as miR396, miR168, miR167, miR165, miR319, miR159, miR394, miR156, miR393, miR171, miR158, and miR169, responded to salt treatment (Liu et al. 2008). miR396 is a salt responsive plant miRNA targeting growth regulating factor (GRF) transcription factors. Overexpression of miR396 in rice and Arabidopsis results in reduced salt and alkali stress tolerance compared to that of wild-type plants
• (Chi et al. 2011). In a recent study, expression level of miR398, targeting 2 Cu/Zn superoxide dismutases (CSD1 and CSD2), was differentiated in response to salt stress
• (Jagadeeswaran et al. 2009). In addition, miR395 regulates the asp1 gene for sulfur accumulation and allocation
• (Liang et al. 2010). Furthermore, miR530, miR1445, miR1446, miR1447, and miR171 were down-regulated, whereas miR482.2 and miR1450 were up-regulated during salt stress in poplar (Lu et al. 2008). Nutrient deficiency
• Nutrient availability is an important abiotic stress factor for plant yield and productivity. To cope with nutrient deprivation, plants use several metabolic, physiological, and molecular mechanisms. Transcriptional regulation upon nutrient limitation in plants via miRNA-mediated gene expression adjustment has been reported for several element deficiencies, such as phosphate (Pant et al. 2008;
• Hsieh et al. 2009), sulfate (Rausch et al. 2005), and copper
• (Yamasaki et al. 2007; Abdel-Ghany and Pilon 2008).
• Several miRNAs, found to be differentially expressed upon phosphate deprivation, are reported as miR156, miR169, miR395, miR398, miR778, miR827 miR828, and miR2111
• (Sunkar et al. 2012). In addition, miR395 plays a role in sulfate metabolism, being complementary to mRNA of
• ATP sulfurylase (APS) proteins. Expression of miR395 was induced by low external sulfate concentrations (Jones-Rhoades and Bartel 2004). Moreover, in response to low Cu 2+ availability, miR398 is induced, leading to decreased levels of csd transcripts to save the Cu 2+ ions for plastocyanin (Shukla et al. 2008), and other miRNAs
• (miR397, miR408, and miR857) were detected as copper responsive (Yamasaki et al. 2007). To adopt nitrogen availability, the miR393/Afb3 and miR167/Arf8 modules are implicated in regulating root system architecture in plants (Vidal et al. 2010). In M. truncatula, miR169a targets hap2-1 encoding a subunit of hetero-trimeric CCAATBOX-BINDING transcription factor complex to the nodule meristematic zone. Nodule development is arrested by the overexpression of miR169a or suppression of hap2-1, resulting in a deficient nitrogen-fixation phenotype (Combier et al. 2006). Cold stress
• Cold stress or low temperature is another challenge for plant growth and productivity. It has been shown that expression levels of miRNA are also affected by low temperature in several plants. Lv et al. (2010) used a ricespecific miRNA microarray chip and found that 15 miRNA families are differentially regulated by cold stress. In their study, response of miR171 family members to cold stress was observed, and they found that the miR171 family members are differently regulated. While the expression of pri-miR171a/e/f/i is down-regulated, that of pri-miR171c/ d/h is up-regulated. In other studies, expression levels of miR165/166, miR169, miR172, miR393, miR396, miR397, miR402, and miR408 were detected as increased, and that of miR398 was measured as decreased in cold stress applied Arabidopsis plants (Sunkar and Zhu 2004; Zhou et al. 2008). In Brachypodium, a total of 25 miRNAs, including a few novel ones, were measured as differential expressed upon cold treatment (Zhang et al. 2009). The miR319 was detected as decreased in both roots and shoots, although strong induction was observed in plantlets in sugarcane
• (Thiebaut et al. 2012). Additionally, miR2118 was observed as induced under cold stress in beans (Arenas-Huertero et al. 2009). Oxidative stress
• Elevated reactive oxygen species (ROS) including hydrogen peroxide (H 2 O 2 ) and free radicals are found in plant cells under biotic and abiotic stress conditions. The enzymatic scavenging mechanism of oxidative stress response is composed of superoxide dismutases (SODs), peroxidases, and catalases to detoxify the ROS (Shukla et al. 2008). The expression level of miR398 was found to be decreased by oxidative stress since it targets copper/ zinc superoxide dismutases (Cu/Zn-SODs), cytosolic csd1, and chloroplast localized csd2, thereby causing an increase in the accumulation of CSD1 and CSD2 in
• Arabidopsis (Sunkar et al. 2006) and rice (Li et al. 2010b). miR169, miR397, miR528, miR1425, miR827, miR319a.2, and miR408-5p were observed as H 2 O 2 responsive and differently expressed in rice seedlings (Li et al. 2010b). Deep sequencing showed that the expression levels of miR169, miR397, miR827, and miR1425 were increased while that of miR528 was decreased by H 2 O 2 treatments (Li et al. 2011c).
• Response to biotic stresses Biotic factors such as bacteria, viruses, fungi, and insects affect plant growth and productivity. Being sessile organisms plants respond to diseases via their physiologic and molecular mechanisms. In several studies, the roles of small RNA in disease resistance responses were revealed (Navarro et al. 2006; Fahlgren et al. 2007; Jin 2008; KatiyarAgarwal and Jin 2010; Li et al. 2010a; Zhang et al. 2011a, 2011b; Zhou et al. 2012). miR393 is the first reported responsive miRNA upon bacterial inoculation in plants
• (Navarro et al. 2006). Bacterial elicitor flg22 results in the induction of miR393 expression level to suppress auxin signaling. This miRNA has been also measured as 10-fold increased when Arabidopsis leaves were inoculated with nonpathogenic Pseudomonas syringae pv. tomato (Pst)
• DC3000 hrcC mutant, defective in TTSS (Fahlgren et al. 2007; Zhang et al. 2011b). Additionally, expression levels of miR160 and miR167 were discovered to be increased in the same nonpathogenic inoculation (Fahlgren et al. 2007). Zhang et al. (2011a) performed a high throughput small RNA deep sequencing experiment using 3 different inoculations including Pst DC3000 hrcC (nonpathogenic), Pst DC3000 EV (virulent), and Pst DC3000 avrRpt2
• (avirulent), and they identified 15, 27, and 20 differentially expressed miRNA families respectively in Arabidopsis (Zhang et al. 2011a). miR398 was found to be suppressed upon oxidative stress treatment via bacterial pathogen infection when Arabidopsis plants were inoculated with
• Pst avirulent strains (Pst DC3000 carrying avrRpm1 and avrRpt2), but not with the virulent strain (Jagadeeswaran et al. 2009). miR393* also plays a critical role in plant antibacterial response by targeting and suppressing expression of a Golgi-localized Snare protein, MEMB12.
• Inhibition of the expression of memb12 leads to increased exocytosis of pathogenesis-related protein PR1; consequently, it prevents pathogen growth (Bednarek et al. 2010). Expression level measurement of miRNAs was also studied in fungal pathogen inoculation, e.g., nonprotein coding (npc)-RNA molecules were measured in powdery mildew infected wheat (Xin et al. 2010), and a total of 125 putative wheat stress responsive long npc-RNAs were identified. Some of the predicted npc-RNAs such as miR675, miR167, and miR2004 corresponding to miRNAs were found to be fungal-stress responsive.
• Methods for miRNA detection and measurement Understanding the miRNA-mediated gene regulation is largely dependent on the availability of innovative strategies and methodological approaches for accurate detection of miRNA expression levels in specific tissues. Identification of differentially expressed miRNA genes in cell transcriptome directly reflects the dynamic cell behavior under changing conditions. The miRNA and target mRNA expression level measurement presents valuable information about the miRNA’s functions. So far, numerous methodologies have been developed for rapid, sensitive, specific, and genome-wide detection of miRNAs. These methods fall under 4 categories: direct cloning, realtime quantitative PCR, high-throughput deep-sequencing, and hybridization-based methods including northern blotting, in situ hybridization, and miRNA-microarray methods. Each method has its own advantages and drawbacks, such as direct cloning and next-generation sequencing technologies with high sensitivity, which are used in both the discovery and confirmation of miRNAs, whereas qRT-PCR and microarray are used only for expression patterning. Differentially expressed miRNAs obtained from genome-wide miRNA expression profiling methods such as microarray or deep-sequencing generally require more validation done with real-time quantitative PCR studies. Despite the progress made in developing methods for the quantification of miRNAs, rapid and highly sensitive methods are still needed for overcoming known obstacles of miRNAs, including short-length, low abundance, and the presence of miRNA families whose members have roughly the same sequence compositions and represent similar expression patterns. Below, we will briefly summarize some of these methods routinely used for measuring miRNA levels. High-throughput sequencing of miRNAs The emergence of next-generation high-throughput cDNA and direct-RNA sequencing techniques has revolutionized whole-transcriptome analysis at an unprecedented depth, accuracy, and resolution. Newgeneration sequencing (NGS) technologies have been successfully applied in a variety of areas, covering de novo genome sequencing (Velasco et al. 2010; Vogel et al. 2010), genome re-sequencing (Ashelford et al. 2011)
• (DNA-Seq), transcriptomics (Wei et al. 2011; Hansey et al. 2012; Mutasa-Gottgens et al. 2012) (RNA-Seq), and epigenetic modification, such as DNA methylation or DNA–protein interactions (Chip-Seq) (Kaufmann et al. 2010), and recently they have been extensively used in genome-wide identification and quantification of known and novel miRNAs and other noncoding small RNAs in a single instrument run. Currently, there are several commercially available NGS platforms including Illumina
• Solexa sequencing, Roche 454 GS FLX, Applied Biosystems SOLiD, Helicos HeliScope, Ion Torrent PGM–Applied Biosystems, and single molecule real-time sequencing (SMRT)–Pacific Bioscience (the last 3 sequencers are called third-generation DNA sequencing instruments). When compared with previous sequencing technologies, third-generation sequencing technologies offer significant advantages in terms of simplified library construction, small amounts of starting material, and longer read lengths. However, more importantly, these technologies do not require the conversion of RNA into cDNA or ligation/preamplification steps. Therefore, they can be effectively used for direct sequencing of RNA without the need for cDNA conversion process causing the cDNA synthesis-based artifacts and pre-amplification experiments leading to biases and errors (Schadt et al. 2010). Each NGS platform was comparatively differentiated from each other in terms of template preparation, read length, run time, sequencing chemistry, depth of coverage, raw accuracy, and cost per run (Metzker 2010; Egan et al. 2012). Nowadays, 3 major deep sequencing platforms, ABI/Solid, Roche 454
• Pyrosequencer, and especially Illumina’s miRNA-Seq, account for the vast majority of small RNA sequencing all over the world. The deep sequencing approach can easily eliminate some technical challenges and obstacles sourced from intrinsic properties of miRNAs, such as small read size, low-abundance, instability, and contamination with other RNA fragments. In addition to providing comprehensive information about the miRNA transcriptome on a genome-wide scale (miRNAome), the NGS technologies also allow for the large-scale identification of cells (Judson et al. 2009; Fehniger et al. 2010; Wei et al. 2011), tissue
• (Mica et al. 2010; An et al. 2011; Chi et al. 2011; GonzalezIbeas et al. 2011), stage (Song et al. 2010; Zhang et al. 2012), condition (Zhang et al. 2009; Du et al. 2011; Li et al. 2011), and species-specific miRNAs (Jones-Rhoades et al. 2006; Zhang et al. 2006a; Voinnet et al. 2009). In recent years, NGS has been applied to determine the populations of variants of known miRNAs (isomiRs) that are mainly generated from alternative cleavage of Dicer Like-1
• (DCL1) during biogenesis, and they can have 5´ and/or 3´ cleavage variations, insertions, and deletions (LelandaisBrière et al. 2009). One intriguing application area of
• NGS technologies in miRNA research is “degradome sequencing”, a next-generation sequencing method integrated with modified 5′ RACE (rapid amplification of cDNA ends) in order to identify miRNA-directed mRNA cleavage sites (Addo-Quaye et al. 2008; German et al. 2008;
• Meng et al. 2010). This method has been widely used to identify the genome-wide analysis of miRNA-mediated cleavages in plants; hence, detailed functional information could be obtained about patterns of RNA degradation
• (Pantaleo et al. 2010; Zhou et al. 2010; Mao et al. 2012).
• Moreover, deep sequencing allows us to determine the miRNAs whose expression profiles could be differentiated under a variety of stress conditions including drought (Barrera-Figueroa et al. 2011; Wang et al. 2011b), cold
• (Zhang et al. 2009), phosphate deficiency (Hsieh et al. 2009), sulfate deficiency (Huang et al. 2010), and fungal infection (Xin et al. 2011).
• MicroRNA profiling using microarrays Microarray technology is one of the most powerful and versatile high-throughput tools. This technique has been used successfully to measure genome-wide coding and/ or small noncoding gene expression changes in a single experiment. Unlike other nucleic acid hybridization methods, it is a genome-wide hybridization method that is currently used in various areas of molecular biology including (i) characterization and determination of differentially expressed genes on a genomic scale, (ii) global interrogation of genomic structural variations by using array-comparative genomic hybridization (array based-CGH), (iii) revealing and measuring both DNA polymorphism and dosage changes among individuals by using single-nucleotide polymorphism (SNP) array, (iv) detecting epigenetic modifications, such as DNA methylation status, genome-wide protein– DNA interactions, and chromatin modifications using ChIP-chip array, and (v) profiling the genome-wide miRNA expression pattern by using miRNA-microarray (Davison et al. 2006; Liu et al. 2008; Yin et al. 2008). A number of different commercially available miRNA array platforms (Agilent Technologies miRNA profiling system, Illumina MicroRNA Expression Profiling BeadChips arrays, Affymetrix’s GeneChip miRNA Array, µParaflo Microfluidic Array Technology, etc.) (Chen et al. 2012; D’Andrade and Fulmer-Smentek 2012; Dee and Getts 2012; Zhou et al. 2012) have been developed to date, but there are some technical differences in these available platforms including probe design, probe immobilization chemistry, slide formats, sample labeling, signal detection chemistries, and cost, although the general procedures of a miRNA-microarray experiment (cDNA preparation, sample labeling, array construction, hybridization, fluorescent detection, and data analysis) are somewhat similar. The probe design has been an integral component of the microarray experiment and an appropriate probe should match some criteria, such as high specificity, affinity, and consistent melting temperature (Tm) with other probes. However, miRNA-microarray probe design is quietly challenging because of the short length, low abundance, and a wide range of melting temperatures (between 45 and 74 °C) of mature miRNAs as well as different miRNAs belonging to same family sharing similar nucleotide sequences (Yin et al. 2008). In order to overcome this obstacle, as with other hybridization-based methods, recently developed locked nucleic acid (LNA)modified capture probes are widely used to normalize effectively melting temperatures on slides, and it also enables sequence discrimination with single nucleotide resolution (Castoldi et al. 2006, 2007). Although miRNAmicroarray technology allows researchers to provide pivotal information about genome-wide noncoding gene expression profiling in parallel as well as being a relatively cheap technique on a per gene basis, it has some timeconsuming processes to solve, namely quality assessment, data analysis, background correction and normalization, and appropriate statistical methods as well as mature miRNA innate characteristic as mentioned above. In plants, miRNA-microarray technology has been extensively used in numerous studies for understanding the functional roles of miRNAs in different organs (Dongdong et al. 2009; Amiteye et al. 2011; Peng 2012), and under variable growth conditions like biotic (Guo et al. 2011) and abiotic stresses, such as drought, cold, and heavy metals (Liu et al. 2008; Ding et al. 2009; De-Kang et al. 2010; Ding et al. 2011; Unver et al. 2010a; Li et al. 2011).
• Quantitative real-time PCR (qRT-PCR) With its high level of sensitivity, specificity, accuracy, and practical use, quantitative real-time PCR (qRT-PCR) has been considered the gold standard for gene expression measurements; hence, it has been extensively used in simultaneous measurement of gene expression patterns of miRNAs (Varkonyi-Gasic et al. 2007; Schmittgen et al. 2008; Unver et al. 2009, 2010a, 2010b; Bin et al. 2011). This method allows us to perform accurate and efficient quantification of miRNA by using as little as 25 pg of total RNA. The method also enables direct and rapid quantification of miRNA from a single cell without
• RNA isolation or any further downstream processing (Chen et al. 2005). Nevertheless, there are significant limitations that hamper the broader use and applicability of qRT-PCR. These limitations are mostly sourced from the nature of miRNA: (i) mature miRNAs are short (average miRNA is 19-24 nucleotides in length), (ii) GC-content of mature miRNA sequences can be heterogeneous in quality, creating a gap between melting points (Tm) of each miRNA, (iii) reverse transcription of mature miRNAs is generally difficult due to the lack of distinctive characters like poly-A tail, and (iv) to distinguish between miRNAs in the same family that differ in only one base could be difficult (Benes and Castoldi 2010; Balcells et al. 2011). In general, there are 2 common qRT-PCR methods: SYBRGreen-based miRNA RT-qPCR assays and Stem-loop RTbased TaqMan, which are differentiated from each other in terms of chemical reaction. The SYBR-based assays use fluorescent double-stranded DNA binding dye, which can intercalate into strands of amplification products, and measuring the increase in fluorescence during PCR cycles monitors detection of amplified miRNAs. However, the detection of expression level of any miRNA by using
• SYBR Green assay presents several disadvantages because dye can bind to any double-stranded DNA regardless of amplicon or nonspecific cDNAs; thus, it may generate false positive signals. However, the SYBR-based assay is widely used for detection of the expression profile of well-known miRNAs because of its cost per sample, sensitivity, and no requirement for probes (Raymond et al. 2005; VarkonyiGasic et al. 2007; Sharbati-Tehrani et al. 2008). Unlike SYBR-based qRT-PCR methods, the stem-loop RT-based
• TaqMan method uses a target-specific fluorogenic probe that enables the rapid detection and quantification of desired miRNAs (Figure 2) (Chen et al. 2005; Mestdagh
• Capturing of specific miRNA Stem-Loop RT reaction A) TaqMan based Real -Time PCR B) SYBR Green Real-Time PCR Figure 2. A schematic illustration of TaqMan probe and SYBR Green real-time PCR assay for quantification of mature miRNA (Varkonyi-Gasic et al. 2007; Wang et al. 2010). et al. 2008). Chen et al. (2005) developed an unusual and mature miRNA-specific stem-loop RT primer that can easily hybridize in a sequence-specific manner with its target mature miRNA. It was also reported that the stemloop RT primers used in the reverse-transcription step are considerably better when compared with conventional ones. The use of miRNA gene-specific TaqMan probes with mature miRNA-specific stem-loop RT primer increases the sensitivity and specificity of the methods; therefore, stem-loop RT based TaqMan is now considered the gold standard among the miRNA detection methods (Mestdagh et al. 2008; Schmittgen et al. 2008; Becker et al. 2010).
• In situ hybridization In situ hybridization (ISH) has emerged as a powerful technique that combines molecular biological techniques with histological and cytological approaches for detection of specific nucleic acid sequences in samples at the cellular, tissue, and even whole organism levels (Valoczi et al. 2004;
• Kloosterman et al. 2006). Among the other hybridizationbased methods, only in situ hybridization has the potential to accurately measure the “spatial” and “temporal” expression patterns of miRNAs and their targets within fixed tissues and cells or even cellular compartments.
• Contrary to the conventional hybridization methods that require multiple steps including: (i) the isolation of total or small RNAs, (ii) gel electrophoresis for sorting of RNAs based on size and charge, (iii) transferring small RNA samples to a sheet of special membrane, nitrocellulose in general (blotting step), and (iv) detecting the small RNAs with a hybridization probe complementary to part of or the entire target RNA sequence, in this method, we can directly hybridize mature miRNAs with synthetic RNA probes (riboprobes) in order to obtain more information about the localization and relative expression levels of miRNAs of interest without any further processing steps. One of the most important considerations in the miRNA ISH process is developing and designing special and highaffinity binding of the probes that can easily hybridize with mature miRNAs because of the short sequences of mature miRNAs and the longer precursor of miRNAs (pre-miRNAs) having the same sequences as mature ones. Recently, the development of locked nucleic acid (LNA) oligonucleotide probes, which have a high degree of complementary with the miRNA, has paved the way for efficient detection of animal and plant miRNAs when compared with conventional RNA probes (Valoczi et al. 2004; Vester and Wengel 2004). It has been emphasized that the LNA-modified probe shows a strong ability to bind to mature miRNAs rather than pri- or pre-miRNAs, subsequently resulting in detection of high-level mature miRNAs. Another advantage of it is that LNA-modified probes and conventional antisense riboprobes (for target) can be used collaboratively to detect both a mature miRNA and its target or desired mRNA simultaneously
• (Sweetman et al. 2008; Sweetman 2011). Moreover, as mentioned above, this technique has been widely and successfully applied to cultured cells (Deo et al. 2006; Thompson et al. 2007; Pearson et al. 2009), tissue sections
• (Nelson et al. 2006; Wulczyn et al. 2007), and formalinfixed and paraffin-embedded tissues (Nuovo et al., 2009) as well as whole mounts (Wienholds et al. 2005; Ason et al. 2006; Kloosterman et al. 2006). Kinder and Timmermans
• (2006) utilized miRNA in situ hybridization in order to elucidate the role of miRNAs in the developmental process of Arabidopsis and maize; they also gave a comprehensive protocol about the in situ hybridization technique for plants (Juarez et al. 2004; Kidner and Martienssen 2004;
• Kidner and Timmermans 2006). Additionally, Várallyay and Havelda (2011) described a step-by-step plant miRNA-ISH protocol for A. thaliana and N. benthamiana by using highly sensitive LNA-modified oligonucleotide probes; in particular, they touch upon almost every aspect of protocols (Várallyay and Havelda 2011). In conclusion, miRNA-ISH supplied by LNA-oligonucleotide probes enables the spatial and temporal expression patterns of miRNA with high sensitivity cells, tissues, or organs belonging to both animals and plants. Northern blotting
• Northern blotting is a hybridization-based technique that can be used to detect expression levels of miRNAs of interest, indicating the relative amounts of target miRNAs in the total RNA pool. The technique consists of 3 steps: (i) the separation of RNA samples using denaturing polyacrylamide gel electrophoresis (PAGE) according to their size, (ii) transferring the RNAs to solid nylon membranes, and (iii) hybridization of RNAs with a radioactive probe that is complementary to all or part of the RNA sequence, and samples are then exposed to X-rays to obtain information. By using this method, we can easily determine the size of miRNAs and validate computationally predicted miRNAs; the technique also allows us to compare the multiple samples in one run. However, this technique has some drawbacks, such as requirement of large amounts (5–25 mg for each sample) and high-quality RNA samples, and having a considerably time-consuming protocol (Pall and Hamilton 2008; López-Gomollón 2011). It was previously reported not to be suitable for clinical studies to detect and measure the expression level of hundreds of miRNAs. Valoczi et al. (2004) made some alteration in northern blotting by using modified oligonucleotides using locked nucleic acid (LNA), which increases the method’s sensitivity for the detection of mature miRNAs by at least 10 times
• (Valoczi et al. 2004; Varallyay et al. 2008). Koscianska et al. (2011) used a novel high-resolution northern-blotting technique for detecting endogenous and exogenous RNAs and compared the result with data obtained from miRNA deep sequencing. In conclusion, using the high resolution northern blotting instead of conventional methods enables analysis of endogenous and exogenous RNAs in the range of 20-70 nt and it also helps in detecting the length heterogeneity analysis of miRNAs and their precursors (Koscianska et al. 2011).
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