Plant Biology ISSN 1435-8603

REVIEW ARTICLE

MicroRNAs in fruit trees: discovery, diversity and future research directions M. C. Solofoharivelo1, A. P. van der Walt2,3, D. Stephan1, J. T. Burger1 & S. L. Murray2,4 1 2 3 4

Vitis Lab, Department of Genetics, Stellenbosch University, Matieland, South Africa Centre for Proteomic and Genomic Research, Observatory, Cape Town, South Africa Central Analytical Facilities, DNA Sequencing Unit, Stellenbosch University, Matieland, South Africa Department of Molecular and Cell Biology, University of Cape Town, Rondebosch, South Africa

Keywords Apple; application; citrus; fruit trees; grapevine; miRNAs; peach. Correspondence S. L. Murray, Centre for Proteomic and Genomic Research, P.O. Box 81, Observatory, 7935 Cape Town, South Africa. E-mail: [email protected] Editor A. Weber Received: 24 October 2013; Accepted: 14 December 2013

ABSTRACT Since the first description of microRNAs (miRNAs) 20 years ago, the number of miRNAs identified in different eukaryotic organisms has exploded, largely due to the recent advances in DNA sequencing technologies. Functional studies, mostly from model species, have revealed that miRNAs are major post-transcriptional regulators of gene expression in eukaryotes. In plants, they are implicated in fundamental biological processes, from plant development and morphogenesis, to regulation of plant pathogen and abiotic stress responses. Although a substantial number of miRNAs have been identified in fruit trees to date, their functions remain largely uncharacterised. The present review aims to summarise the progress made in miRNA research in fruit trees, focusing specifically on the economically important species Prunus persica, Malus domestica, Citrus spp, and Vitis vinifera. We also discuss future miRNA research prospects in these plants and highlight potential applications of miRNAs in the on-going improvement of fruit trees.

doi:10.1111/plb.12153

INTRODUCTION Discovered 20 years ago in Caenorhabidtis elegans, microRNAs (miRNAs) have emerged as major key players in post-transcriptional regulation of gene expression in diverse living organisms. These tiny RNAs have been demonstrated to regulate fundamental biological processes in plants, including plant development, morphogenesis, fruit development and plant responses to abiotic and biotic stresses (Jones-Rhoades et al. 2006; Voinnet 2009; Khraiwesh et al. 2011). miRNAs are a class of small non-coding RNAs, 19- to 24-mer in length, that are initially transcribed as longer-structured RNAs, with characteristic hairpins (Bartel 2004; Jones-Rhoades et al. 2006; Voinnet 2009). In plants, these structures are cleaved by Dicer-like (DCL) proteins to produce a short complementary miRNA– miRNA* duplex that exits the nucleus into the cytoplasm. The leading miRNAs are next incorporated into the RNA-induced silencing complex (RISC) and serve as guides to recognise complementary mRNAs (so-called miRNA targets) to block translation or to target them for degradation (Bartel 2004; Voinnet 2009). With the recent sequencing of fruit tree genomes (Jaillon et al. 2007; Velasco et al. 2007, 2010; International Peach Genome Initiative et al. 2013), the identification of new miRNAs in economically important fruit trees (primarily Citrus spp, Malus domestica, Prunus persica and Vitis vinifera) has begun to emerge. This review focuses on the progress made in fruit tree miRNA research in recent years. Readers are referred to complementary reviews of miRNAs in trees (Sun et al. 2011)

and in the fleshy fruit model plant, tomato (Dalmay 2010), which broadly cover trees and fruits, respectively, and therefore fall outside the scope of our review. First, we briefly summarise the methods used to identify miRNAs in fruit trees. Second, we focus on the extent of miRNA sequence diversity in fruit trees currently listed in miRBase (Kozomara & Griffiths-Jones 2011), highlighting the conserved and non-conserved fruit tree miRNAs compared to model plant species. We go on to review miRNAs identified in fruit trees to date. Finally, we address the future research directions and applications of miRNAs in woody fruit biotechnology. Fruit trees such as apple (M. domestica), peach (P. persica), citrus (Citrus spp.) and grapevine (V. vinifera) are among the most economically important fruit crops in the world (Hanke & Flachowsky 2010). Understanding how miRNAs function in the development of woody fruit species, as well as their roles in mediating stress responses, could provide new insights for improving fruit trees and grapevines. IDENTIFICATION OF MIRNAS IN FRUIT TREES Plant MIR genes were initially identified in the model species Arabidopsis thaliana (Reinhart et al. 2002; Rhoades et al. 2002; Sunkar & Zhu 2004) and Oryza sativa (Jones-Rhoades & Bartel 2004; Sunkar et al. 2005) using a combination of computational prediction tools and experimental approaches. Computational prediction tools used the characteristic features of miRNA precursors and the high sequence homology between conserved mature miRNA sequences in various species with

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

1

MicroRNAs in fruit trees

Solofoharivelo, Walt, Stephan, Burger & Murray

available genome sequences. Experimental approaches included direct cloning followed by low depth sequencing of small RNA species, small RNA blots and reverse transcription quantitative PCR (RT-qPCR). In recent years, these methods have been overtaken by small RNA sequencing, using next-generation DNA sequencing technologies (NGS). Indeed, the application of NGS has considerably advanced miRNA discovery from several non-model plants. To date, there are more than 7000 predicted and/or experimentally validated plant precursor and mature miRNA sequences from 72 different species registered in the most recent version of the miRNA repository database, miRBase version 20 (http://mirbase.org/), released in June 2013 (Griffiths-Jones 2010; Kozomara & Griffiths-Jones 2011). Plant species range from the single cell alga Chlamydomonas reinhardii to higher flowering plants, including several fruit trees. Plant miRNAs are also hosted in other databases, such as the plant miRNA database (http://bioinformatics.cau.edu.cn/ PMRD/; Zhang et al. 2009). In the past 3 years, small RNA sequencing by NGS has been widely used to identify and characterise miRNAs from grapevine (Mica et al. 2010; Pantaleo et al. 2010; Wang et al. 2011b, 2012), several citrus species (Song et al. 2010b; Xu et al. 2010; Zhang et al. 2012a), apple (Xia et al. 2012), peach (Barakat et al. 2012; Eldem et al. 2012; Zhu et al. 2012) and papaya (Aryal et al. 2012; Liang et al. 2013). It is important to mention that the large amount of sequence data generated by NGS requires substantial computational prediction tools to both analyse and characterise small RNA populations and to predict novel miRNAs and their targets. For further details, excellent reviews are available on tools for small RNA sequencing data analysis (Dai & Zhao 2011; McCormick et al. 2011). Although current miRNA prediction methods generally rely on the use of small RNA sequencing data combined with available genome sequences, we would like to highlight that a large number of MIR genes in fruit trees were identified using homology search-based prediction tools such as miRFinder (Bonnet et al. 2004a,b), MirCheck (Jones-Rhoades & Bartel 2004) and MicroHARVESTER (Dezulian et al. 2006). Velasco et al. (2007) identified 143 putative miRNA genes belonging to 28 plant miRNA families in the genome of V. vinifera cv. ‘Pinot noir’. Expressed sequence tagged (EST) sequences were used to predict miRNAs in different citrus species (Song et al. 2009, 2010a,b), apple (Yu et al. 2011) and peach (Zhang et al. 2012b). One drawback of homology search-based tools is that they can only identify conserved miRNAs based on known miRNA sequences. Other in silico prediction tools, such as FindMiRNA, do not rely on a cross-species comparison but use the rigid pairing of plant miRNAs with their putative targets (Adai et al. 2005; Mendes et al. 2009). Thousands of putative miRNA genes were predicted in the grapevine genome using this approach (Lazzari et al. 2009); however these data remain to be validated experimentally. CONSERVED AND NON-CONSERVED MIRNAS IN FRUIT TREES Based on their sequence homology and detection across different plant lineages, plant miRNA families are often classified as highly conserved, non-conserved and species-specific (Cuperus et al. 2011; Jones-Rhoades 2012). Cross-species comparison of miRNA families identified in different plant species has 2

revealed that certain miRNA families are highly conserved across different plant lineages. A recent review on the origin and evolution of plant miRNAs identified eight core miRNA families that were present in the ancestors of all land plants, namely MIR156, MIR159/MIR319, MIR160, MIR166, MIR171, MIR408, MIR390 and MIR395. In comparison, most miRNA families appeared to have arisen recently, comprising lineagespecific or even species-specific miRNAs (Cuperus et al. 2011). In order to extend this analysis to fruit tree miRNAs, we extracted miRNAs registered in miRBase version 20 (Kozomara & Griffiths-Jones 2011; Table S1) and compared miRNAs from P. persica (peach), M. domestica (apple), Citrus spp. (Citrus) and V. vinifera (grapevine) with miRNA families identified in the model plants A. thaliana, O. sativa and Populus trichocarpa (Fig. 1). Twenty-two miRNA families were detected in both the model species and at least three out of the four fruit tree species analysed (Fig. 1). These constitute highly conserved MIR families in all flowering plants, as identified previously (Cuperus et al. 2011). Three miRNA families (MIR403, MIR828 and MIR2111) were detected only in eudicotyledons, as previously reported (Cuperus et al. 2011). The non-conserved MIR535 family was ubiquitously found in fruit trees; however this family was not detected in Arabidopsis and poplar. This miRNA was detected in rice and was also reported to be present in moss (Axtell et al. 2007). Another three miRNA families (MIR477, MIR482 and MIR3627) appeared to be highly conserved between the fruit trees analysed here and the model tree, poplar (Fig. 1). However these miRNAs were also listed in miRBase 20 as present in other non-woody plant species, suggesting that they are not woody plant-specific miRNAs (Kozomara & Griffiths-Jones 2011). Several other non-conserved miRNA families were identified in fruit trees, such as MIR858 present in apple, peach and Arabidopsis. Out of the large number of fruit tree-specific miRNA families listed in miRBase 20, only four (MIR1511, MIR5225, MIR7122 and MIR7125) have been detected in more than one fruit tree species (apple and peach) so far. Furthermore, these miRNAs are not found in the fruit plant tomato (http://mirbase.org/). These four appeared to represent Rosaceae-specific miRNAs, as shown in Fig. 1. A vast number of fruit tree-specific miRNAs are unique and represent recently evolved novel miRNAs, possibly with a specific function. POTENTIAL MIRNA FUNCTION IN FRUIT TREES Functional studies of miRNAs in fruit trees and grapevine are rare or non-existent thus far. A key step in unlocking miRNA function is to identify its putative targets. Several robust computational prediction tools have been developed to identify miRNA targets in plants. These include tools such as psRNATarget (Dai & Zhao 2011), UEA sRNA tools (Stocks et al. 2012) and Target-Align (Xie & Zhang 2010), to cite a few. These particular tools were tailored to predict miRNA targets in plants based on specific plant miRNA–target pairing (Ding et al. 2012). Experimental approaches such as Northern blot and RT-qPCR were used to validate and quantify the expression of predicted miRNA targets. In addition, the precise miRNA-cleaved target products can be further confirmed experimentally using a modified 5′-RACE technique called degradome sequencing (Llave et al. 2011). Degradome sequencing combines specialised library preparation with

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

Solofoharivelo, Walt, Stephan, Burger & Murray

MicroRNAs in fruit trees

Fig. 1. Conserved and non-conserved MIR families in fruit trees and grapevine compared to the model species (Arabidopsis, Oryza and Populus). miRNA families from Arabidopsis thaliana (Arabidopsis), Populus trichocarpa (Populus), Prunus persica (Prunus), Malus domestica (Malus), Vitis vinifera (Vitis), Citrus spp. (Citrus) and Oryza sativa (Oryza) were extracted from miRBase version 20 (released June 2013; http://www.mirbase.org/). Only miRNA families present in one or more plant species are represented in the figure. Shaded box represents annotation of MIR family in miRBase; opened box denotes absence of MIR family in the particular species.

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

3

MicroRNAs in fruit trees

Solofoharivelo, Walt, Stephan, Burger & Murray

high-throughput RNA sequencing and specific bioinformatic tools, in order to identify the products of miRNA-directed mRNA target cleavage through sequencing the 5′-ends of uncapped RNAs (German et al. 2008, 2009). This technique has been used to verify many of the previously predicted and validated targets of miRNAs in plants, demonstrating its value as an efficient strategy to identify miRNA targets on a large scale. This method was successfully applied to identify and

validate targets of miRNAs in citrus (Song et al. 2010b; Zhang et al. 2012a), apple (Xia et al. 2012), grapevine (Pantaleo et al. 2010) and peach (Zhu et al. 2012). In Table 1, we list experimentally validated targets of several highly conserved and nonconserved miRNAs from M. domestica, P. persica, V. vinifera and Citrus spp. Identified targets of the 22 conserved miRNAs provided in Fig. 1 indicate that in many cases the miRNA target genes have the same developmental function in the fruit

Table 1. List of experimentally validated miRNA targets of conserved and non-conserved miRNA families in fruit trees. miRNAs

target description

fruit tree species detected

references

miR156 miR159

squamosa-promoter binding-like proteins (SPLs) MYB transcription factor SAUR family protein esterase/lipase/thioesterase family protein auxin response factors (ARFs) dicer-like protein Sec14p-like phosphatidylinositol transfer protein unknown expressed protein NAC domain proteins HD-ZIPII transcription factor auxin response factors (ARFs) Argaunote protein nuclear factor Y (NFY) HAP2 transcription factor GRAS-family transcription factor (scarecrow-like) AP2-domain containing transcription factor ethylene-responsive transcription factor (RAP) TCP family transcription factor NADPH-dependent FMN and FAD containing, MYB-transcription factor GDP-D mannose 3′, 5′-epimerase ankyrin repeat protein family leucine-rich repeat protein kinase family, nucleic acid binding, OB-fold like protein MdTAS3-1, MdTAS3-2, PpeTAS3 auxin-signalling F-box protein methyltransferase superfamily protein F-box transcription factor NAC domain proteins sulphate transmembrane transporter bifunctonal 3′-phosphoadenosine 5-phosphosulphate synthase heat shock protein, granulin repeat cysteine protease family protein, nucleoside triphosphate hydrolase growth regulating factor (GRF) TIR-NB LRR resistance protein, replication factor C subunit 1 Ice1 transcription factor GDP-D mannose 3′, 5′-epimerase, acyl-coA N-acyltransferase superfamily laccase copper/zinc superoxide dismutase rubredoxin-like superfamily protein isocitrate dehydrogenase (NAD) RNA binding family protein copper ion binding protein, cyclin D3 major latex protein glutamate receptor 2.7 disease resistance protein phosphatidylinositolglycan-related protein tetratricopeptide repeat (TPR)-containing protein thiamine pyrophosphate ubiquitin-like superfamily protein lateral root primordium protein-related transitional endoplasmic reticulum

Vvi, Pt, Mdo, Ppe Vvi, Mdo, Ppe Vvi Pt Vvi, Pt, Mdo, Ppe Vvi Pt Mdo Vvi, Pt, Mdo, Ppe Vvi, Pt, Mdo, Ppe Vvi, Pt, Mdo, Ppe Vvi, Mdo, Ppe Pt, Ppe Vvi Vvi, Pt, Mdo Vvi, Pt, Mdo Mdo Vvi, Pt, Mdo Vvi Pt, Mdo Vvi Pt Mdo, Ppe Vvi, Mdo, Ppe Pt Mdo Pt Ppe Mdo Pt Mdo, Ppe Mdo Vvi Pt Ppe Pt, Mdo Pt Mdo Pt Ppe Vvi Pt Pt Vvi Pt Pt Pt Pt Vvi

1, 2, 3, 4 1, 3, 4 1 2 1, 2, 3, 4 4 2 3 1, 2, 3, 4 1, 2, 3, 4 1, 2, 3, 4 1, 3, 4 2, 4 1 1, 2, 3 1, 2, 3 3 1, 2, 3 1 2, 3 1 2 3, 4 1, 3, 4 2 3 2 4 3 2 3, 4 3 1 2 4 2, 3 2 3 2 4 1 2 2 1 2 2 2 2 1

miR160 miR162

miR164 miR166 miR167 miR168 miR169 miR171 miR172 miR319

miR390

miR393 miR394 miR395

miR396

miR397

miR398 miR399 miR408 miR827 miR472 miR473 miR477

miR479

4

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

Solofoharivelo, Walt, Stephan, Burger & Murray

MicroRNAs in fruit trees

Table 1. Continued. miRNAs

target description

fruit tree species detected

references

miR482

cytochrome p450 HOPZ-activated resistance 1 alpha/beta-hydrolase superfamily protein lactoylglutathione lyase family protein squamosa-promoter binding protein, DNA primase large subunit, splicing factor cysteine protease MYB transcription factor pentatricopeptide repeat-containing MYB transcription factor r2r3-like protein oligopeptide transporter OPT family MATE efflux family protein, anthocyanin regulatory C1 protein 3-ketoacyl-CoA thiolase transducin family protein amino acid transporter plant protein of unknown function late embryogenesis abundant (LEA) protein family transmembrane proteins 14C

Vvi Pt Pt Pt Vvi Mdo Vvi, Mdo, Ppe Vvi Vvi, Mdo, Ppe Vvi Mdo Ppe Pt Mdo Pt Pt Pt

1 2 2 2 1 3 1, 3, 4 1 1, 3, 4 1 3 4 2 3 2 2 2

miR530 miR535 miR828 miR858

miR1515 miR3627 miR3951 miR3954

All targets were compiled from published degradome sequencing for each respective pecies. Predicted targets were not included in this list. 1; Vitis vinifera (Vvi; Pantaleo et al. 2010). 2; Poncirus trifoliata (Pt; Syn Citrus trifoliata; Zhang et al. 2012a). 3; Malus domestica (Mdo; Xia et al. 2012). 4; Prunus persica (Ppe; Zhu et al. 2012).

tree species (Table 1). Non-conserved miRNAs target a wide range of genes involved in various biological processes. For example, miR858 has multiple targets in V. vinifera, M. domestica and P. persica (Table 1). Targets for many species-specific miRNAs have not been reported and therefore the role of these miRNAs remains unclear. A major goal therefore is the identification of target mRNAs for these novel species-specific miRNAs using available target prediction tools and further analysis of the degradome datasets. Below we separately discuss the current status of miRNAs in peach, apple, grapevine, citrus and other fruit tree species. miRNAs in peach Peach is one of the most important fruit trees crops worldwide. Peach has a relatively small genome of 250 Mb and is genetically well characterised. A high-quality draft of the peach genome has recently been published (International Peach Genome Initiative et al. 2013). Besides its economic importance, peach has emerged as a model species for Rosaceae and for fruit trees in general. To date, there are 180 miRNA precursor and 214 mature peach miRNA sequences listed in miRBase 20. Peach miRNAs were initially identified computationally using the large publicly available peach EST database (Zhang et al. 2012b). Several highly conserved miRNA families were differentially expressed in different peach tissues, including leaves, flowers and fruits, at various developmental stages (Zhang et al. 2012b). Small RNA sequencing confirmed that these highly conserved miRNAs were abundantly expressed, albeit at different levels, in diverse peach tissues such as roots, leaves, flowers and mixed fruits, suggesting an active role of these miRNAs during peach developmental processes (Zhu et al. 2012). Notably, the targets of these conserved miRNAs were transcription factors involved in developmental processes, e.g.

squamosa-promoter binding-like proteins (SPLs) for miR156, auxin response factors (ARFs) for miR160 and NAC-domain containing proteins for miR164 (Table 1; Zhu et al. 2012). Non-conserved miRNAs, such as miR828, miR858 and miR3627, were expressed at lower levels compared to highly conserved miRNAs in all tissues, except for miR535, which was abundantly expressed in peach root tissues (Zhu et al. 2012). Several peach-specific novel and candidate miRNAs were also identified in this study (Zhu et al. 2012). Interestingly, expression patterns of the precursors and mature sequences of several of these novel peach-specific miRNAs indicated that transcription and processing of these MIR families could be uncoupled, suggesting specific regulation of these unique miRNA families in peach. Targets of peach-specific novel miRNAs were identified through degradome analysis, and included several NBSLRR class disease resistance proteins, pentatricopeptide repeat (PPR) containing proteins, a protein kinase family protein and a zinc finger protein. This indicates that miRNAs are actively involved in stress responses in peach (Zhu et al. 2012). Several studies have reported on miRNAs responsive to abiotic stresses in peach. Recently, Barakat et al. (2012) performed small RNA sequencing and found that several miRNAs were responsive to chilling in peach. These included highly conserved miRNAs (miR156, miR164, miR172, miR393 and miR396) and nonconserved miRNAs (miR414 and miR2275) that were induced in winter buds as compared to young leaf tissues. Drought has been reported to severely hamper peach fruit development and production. Eldem et al. (2012) identified miRNAs that responded to drought treatment in root and leaf tissues of peach. Several miRNAs showed a significant expression change in drought-treated compared to control peach plants. Highly conserved miR160, miR165/166 and miR167 were downregulated in both root and leaf tissues, whereas miR395 was found to be exclusively down-regulated in root tissues but not

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

5

MicroRNAs in fruit trees

Solofoharivelo, Walt, Stephan, Burger & Murray

in leaves. Other miRNA families (miR169, miR396, miR397, miR398 and miR408) showed a significant reduction in root tissues, while their expression did not change in leaves in response to exposure to water deficit treatment (Eldem et al. 2012). miRNAs in apple There are 206 apple pre-miRNAs and 207 mature miRNAs listed in miRBase 20. These include highly conserved miRNA families and a large number of apple-specific miRNAs (Xia et al. 2012). Profiling of miR156, miR159, miR160, miR167 and miR172 consistently showed different levels of expression in several apple tissues, including mature leaves, roots, flower buds and fruits harvested at various developmental stages (Gleave et al. 2008; Varkonyi-Gasic et al. 2010). Furthermore, NGS data showed that miR156 was highly abundant in apple root tissues, whereas the number of small RNA reads representing miR165/miR166 and miR167 families was higher in leaf tissues (Xia et al. 2012). These miRNAs families were predicted to target several members of SPLs for miR156 and ARFs for miR167, as reported in other plant species (Sun 2011). Cleavage of these targets was later confirmed by degradome sequencing (Table 1; Xia et al. 2012), suggesting their importance in apple developmental processes. Several non-conserved miRNA families, such as miR477, miR482, miR828, miR845 and miR535, were also differentially expressed in diverse apple tissues (Xia et al. 2012). Interestingly, the apple miR159, miR828 and miR858 families were reported to target a total of 81 MYB transcription factors (Xia et al. 2012). While the MYB genes targeted by miR159 were functionally associated with anther and pollen development, the miR828-targeted MYB genes were reported to be involved in the anthocyanin biosynthesis pathway. The miR858 family was found to target the largest MYB families that are linked to several biological processes: from plant development to stress responses and secondary metabolism pathways. MYB transcription factors targeted by members of the miR828 family were also found to produce phased short interfering RNAs (phasiRNAs) that, in turn, could potentially influence the expression of hundreds of other genes (Xia et al. 2012). Newly identified apple-specific miRNA families were reported to target a wide range of genes associated with developmental processes, signalling pathways and defence responses (Xia et al. 2012). miRNAs in grapevine Grapevine is one of the oldest known domesticated fruitproducing crops. It is mainly cultivated for wine production (wine grapes) and for human consumption (table grapes, juice and raisins). More importantly, the genome of V. vinifera was the first fruit crop to be sequenced. Two high-quality draft genome sequences from V. vinifera cv. ‘Pinot noir’ (clones PN40024 and ENTAV115) were released in 2007, facilitating the rapid discovery of miRNA genes (Jaillon et al. 2007; Velasco et al. 2007). To date, there are 163 grapevine miRNA precursor and 186 mature miRNA sequences registered in miRBase 20, which represent 47 different miRNA families. However, more grapevine miRNAs have been identified in the literature. Highly conserved miRNAs were found to be differentially expressed in different grapevine tissues, including leaf, 6

inflorescence, tendril, root and berry, suggesting that miRNAs play important roles during grapevine development (Mica et al. 2010; Pantaleo et al. 2010). For example, expression of miR397a, miR398a and miR408 was 100 times higher in roots than in leaves or in inflorescences (Mica et al. 2010). Conserved grapevine and fruit miRNAs target similar proteins (Table 1; Pantaleo et al. 2010; Sun 2011; Sunkar et al. 2012). One key aspect of wine grape cultivation is berry development and maturation, as this can have a large impact on wine quality. Several miRNAs were differentially expressed during different phases of berry development, including members of the miR171, miR172, miR395, miR396, miR319 and miR535 conserved families (Mica et al. 2010), as well as numerous grapevine-specific miRNAs (Pantaleo et al. 2010). Novel and candidate grapevine-specific miRNAs were found to target a diverse functional group of proteins that includes proline-rich and leucine-rich repeat proteins and elongation factors (Carra et al. 2009; Pantaleo et al. 2010). Recent studies have revealed the diversity of miRNAs from wine and table grapes. When comparing mature miRNA sequences detected in the table grape ‘Summer Black’ with identified miRNAs from the wine grape ‘Pinot noir’, it was shown that among the 130 identified ‘Summer Black’ miRNAs only 68 had a complete wine grape match with ‘Pinot Noir’ (Wang et al. 2011a,b). The remaining miRNA sequences differed by one, two or three mismatches, suggesting some evolutionary divergence between these two grape genotypes. In addition to previously identified grapevine miRNAs, 80 novel and candidate ‘Summer Black’ miRNAs were also detected and validated using RT-qPCR. The newly identified miRNAs were predicted to target various genes involved in plant development, glucose metabolism and anthocyanin metabolism (Wang et al. 2011a,b). This recent surge in miRNA description and characterisation in different grapevine species attests to the ongoing efforts to discover more putative miRNA genes in this important fruit crop. As further miRNAs are identified, it will be very interesting to look at the conservation and divergence of miRNA genes from different grapevine species and to characterise their functions in the different grapevine cultivars. As a perennial plant, grapevine is exposed to a multitude of adverse environmental conditions. A recent study from Alabi et al. (2012) identified several highly conserved miRNAs (miR156, miR162, miR166 and miR167) that showed differential expression in grapevine leaf-roll disease-infected plants. However, further studies are required to ascertain the functions of these miRNAs in the etiology of this complex disease. miRNAs in citrus The miRBase 20 contains a total of 79 citrus miRNA sequences from four different species: C. clementine (5), C. reticulata (4), C. sinensis (64) and C. trifoliata (6). These miRNAs represent 40 different miRNA families that are highly conserved as well as citrus-specific. Additional citrus miRNAs have been described in the literature (Song et al. 2010b; Xu et al. 2010), but are not currently listed in this version of miRBase. Expression analysis in leaves, stems and roots revealed distinct profiles for several miRNA families in citrus, suggesting their roles in citrus development. For example, Zhang et al. (2012a) recently demonstrated that expression of the miR156 family was down-regulated and the miR172 family was up-regulated

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

Solofoharivelo, Walt, Stephan, Burger & Murray

during juvenile to adult phase change in C. trifoliata, which is consistent with the function of these conserved miRNAs in other plant species during phase change (Poethig 2009, 2010; Huijser & Schmid 2011). Similarly, these miRNAs target homologues of well-characterised miRNA targets from model plant species, including SPLs for miR156 and AP2-like genes for miR172 (Table 1; Xu et al. 2010; Song et al. 2010b; Wu et al. 2011; Zhang et al. 2012a). Putative targets of other citrus miRNAs include transcription factors and several putative disease resistance genes (Song et al. 2010b; Xu et al. 2010). Several of these miRNAs were also reported as differentially expressed between wild-type sweet orange and a red-flesh mutant (Xu et al. 2010). Interestingly, results suggest that several miRNAs are involved in regulation of the carotenoid pathway. Predicted targets of novel and candidate citrus-specific miRNAs include several transcription factors, a translation elongation factor and a eukaryotic translation initiation factor. Additionally, several miRNAs were predicted to target a class of genes belonging to the NBS-LRR resistance gene families (Zhang et al. 2012a). miRNAs in other fruit trees A limited number of miRNAs are reported for other fruit trees and these will be briefly discussed here. Aryal et al. (2012) identified 60 miRNAs expressed in leaf and flower tissues from the tropical fruit tree Carica papaya (papaya). These include conserved miRNAs representing 24 known plant miRNA families and several papaya-specific miRNAs. These authors also uncovered several miRNAs (conserved and non-conserved) that were specifically expressed in papaya leaf tissues infected with Papaya ringspot virus (PRSV). A recent in-depth analysis of the small RNA population from leaf and flower tissues of papaya identified known plant miRNA families and several novel and candidate papaya miRNAs (Liang et al. 2013). The majority of the predicted targets for the conserved miRNA families were found to be evolutionarily related to targets found in other plant species (Sun 2011; Liang et al. 2013). The novel papaya miRNAs were predicted to target a wide range of genes, including an ethylene receptor protein homologous to an Arabidopsis ethylene response 1 (ETR1) gene, suggesting the involvement of this miRNA in regulating fruit development and ripening (Liang et al. 2013); however this remains to be validated. MIR genes from another important tropical fruit tree, Theobroma cacao, were also recently reported (Argout et al. 2011). Computational prediction tools identified 83 putative miRNAs distributed into 25 known plant miRNA families in the genome of T. cacao (Argout et al. 2011). Interestingly, predicted targets of these potential miRNAs represent a larger number of transcription factors compared to other plant species, suggesting that miRNAs might play crucial roles in regulating gene expression in T. cacao. miRNAs from these fruit trees are listed in miRBase version 20 (Kozomara & GriffithsJones 2011). As miRNAs are investigated in a wider range of fruit tree species, it is highly likely that many more conserved and novel/candidate miRNAs will be identified. ELUCIDATING THE ROLE OF MIRNAS IN FRUIT TREES: CHALLENGES AND FUTURE RESEARCH DIRECTIONS Recent studies have identified fruit tree miRNAs and their targets in numerous species (Pantaleo et al. 2010; Xia et al. 2012;

MicroRNAs in fruit trees

Zhang et al. 2012a; Zhu et al. 2012). The next major objective in fruit tree miRNA research is the elucidation of miRNA and miRNA target functions. Several methods have been successfully developed and applied to ascertain miRNA functions in the model plant species Arabidopsis and rice (Allen & Millar 2012) but have not yet been applied to fruit trees. These methods include the classical genetic approaches to generate loss-offunction or gain-of-function miRNA gene mutant lines (Allen & Millar 2012) or the overexpression of miRNA genes under the constitutive 35S promoter or plant tissue-specific promoters (Chen et al. 2010; Schwab et al. 2010). These approaches are followed by the subsequent characterisation of the resulting phenotypes due to either loss or gain of function of the targeted miRNAs. Alternatively, artificial miRNA constructs or target mimicry can be used to create miRNA loss-of-function lines. Artificial miRNA (amiRNA) constructs have been widely used to down-regulate genes of interest (Eamens et al. 2008). In an artificial miRNA precursor construct, the native miRNA/ miRNA* duplex is replaced by the amiRNA/amiRNA* sequence which is complementary to the targeted gene (Schwab et al. 2010). This approach has been successfully adapted to silence miRNA family members simultaneously in Arabidopsis (Eamens et al. 2011). Furthermore, in a recent report, evidence of miRNA processing from amiRNA constructs based on the pre-miR319a from Arabidopsis was reported in grapevine somatic embryos (Jelly et al. 2012). This indicates that existing amiRNA constructs from other plant species can have applications in fruit trees. The second strategy mirrors the effect of miRNA target mimicry, initially reported to regulate the expression of miR399 in Arabidopsis (Franco-Zorrilla et al. 2007). Target mimics display a complementary miRNA binding site; however base modifications at positions 11–13 prevent the proper cleavage of the target mimics. miRNAs are thus sequestered by the target mimics, resulting in de-regulation of the ‘true’ miRNA targets (Franco-Zorrilla et al. 2007; Todesco et al. 2010). This method has been used to down-regulate the expression of several miRNA families in Arabidopsis (Todesco et al. 2010) and has recently been extended to make use of short tandem target mimics (STTMs) (Tang et al. 2012; Yan et al. 2012). Short tandem target mimics consist of two short sequences resembling a miRNA binding site. When expressed in plants, STTMs bind to targeted miRNAs, subsequently leading to their degradation. Similar genetic approaches have also been applied to miRNA targets in order to validate the importance of the miRNA–target pairing in producing the phenotypes observed (Allen & Millar 2012). The miRNA resistant strategy overexpresses modified miRNA targets in planta so that the miRNA binding site is mutated without altering the protein sequence. As miRNA–target recognition is based on highly complementary sequences, the miRNA cannot bind efficiently, resulting in accumulation of the miRNA target product (Palatnik et al. 2003). The development and application of all these techniques is crucial in understanding the precise roles that miRNAs play in diverse biological processes in plants. Nonetheless, application of these methods remains challenging for fruit trees. First and foremost, these methods require the development of efficient transformation methods. Although protocols for plant transformation have been developed for fruit trees in recent years, the generation of genetically modified plants in these species can still be a challenging and time consuming process (Gambino &

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

7

MicroRNAs in fruit trees

Solofoharivelo, Walt, Stephan, Burger & Murray

Gribaudo 2012). Another obstacle is overcoming the long juvenile vegetative phase to the adult reproductive phase (Gambino & Gribaudo 2012). It might be possible to extend some of these techniques to fruit trees by using short generation mutant plants, such as the grapevine ‘microvine’ system (Chaib et al. 2010). Alternatively, transient transformation methods or the use of virus vectors to introduce the gene of interest can be readily applied in fruit trees to functionally characterise miRNAs and/or their targets. Ultimately, plant miRNAs could be incorporated as novel molecular breeding strategies for trait improvement in fruit breeding programmes. miRNAs could also be used to develop novel markers (Gui et al. 2011). Alternatively, cisgenic fruit plants could be generated to overexpress candidate miRNA genes (Molesini et al. 2011). Cisgenesis refers to the introduction of natural, unmodified genes into the same species using biotechnology tools, and may be more acceptable to the consumer than the production of transgenic plants.

Although miRNA research in fruit trees has mostly been descriptive to date, miRNAs offer great potential for trait improvement in these economically important commodity crops. Hundreds of diverse miRNA genes, including highly conserved, non-conserved and several species-specific miRNAs, have been identified from the above species. Putative targets of identified miRNAs have been described in the literature and include homologues of well-characterised targets from model plant species for highly conserved miRNA families. An important goal is the identification of target mRNAs for species-specific miRNAs, and elucidation of their associated functions. While several experimental approaches have been used to demonstrate function of miRNAs in the model species Arabidopsis, rice and poplar, these methods have not been readily applied to fruit trees and grapevines to date. It is thus essential to develop and implement experimental approaches tailored to each woody fruit species, in order to validate the function of the identified miRNAs and their putative targets.

CONCLUSIONS Over the last decade, miRNAs have emerged as a hot topic in plant biology. This is especially true since the advent of NGS technologies, which have resulted in a deluge of recently identified miRNAs in several plant species. In this review, we have outlined the current status of miRNA research in the economically important fruit trees peach, apple, citrus and grapevine. REFERENCES Adai A., Johnson C., Mlotshwa S., Archer-Evans S., Manocha V., Vance V., Sundaresan V. (2005) Computational prediction of miRNAs in Arabidopsis thaliana. Genome Research, 15, 78–91. Alabi O.J., Zheng Y., Jagadeeswaran G., Sunkar R., Naidu R.A. (2012) High-throughput sequence analysis of small RNAs in grapevine (Vitis vinifera L.) affected by grapevine leafroll disease. Molecular Plant Pathology, 13, 1060–1076. Allen R.S., Millar A.A.. (2012) Genetic and molecular approaches to assess microRNA function. In: Sunkar R. (Ed.), MicroRNAs in Plant Development and Stress Responses Signaling and Communication in Plants, Vol. 15. Springer, Berlin, Germany, pp 123–148. Argout X., Salse J., Aury J.M., Guiltinan M.J., Droc G., Gouzy J., Allegre M., Chaparro C., Legavre T., Maximova S.N., Abrouk M., Murat F., Fouet O., Poulain J., Ruiz M., Roguet Y., Rodier-Goud M., BarbosaNeto J.F., Sabot F., Kudrna D., Ammiraju J.S., Schuster S.C., Carlson J.E., Sallet E., Schiex T., Dievart A., Kramer M., Gelley L., Shi Z., Berard A., Viot C., Boccara M., Risterucci A.M., Guignon V., Sabau X., Axtell M.J., Ma Z., Zhang Y., Brown S., Bourge M., Golser W., Song X., Clement D., Rivallan R., Tahi M., Akaza J.M., Pitollat B., Gramacho K., D’Hont A., Brunel D., Infante D., Kebe I., Costet P., Wing R., McCombie W.R., Guiderdoni E., Quetier F., Panaud O., Wincker P., Bocs S., Lanaud C. (2011) The genome of Theobroma cacao. Nature Genetics, 43, 101–108. Aryal R., Yang X., Yu Q., Sunkar R., Li L., Ming R. (2012) Asymmetric purine-pyrimidine distribution in cellular small RNA population of papaya. BMC Genomics, 13, 682.

8

SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article: Table S1. List of all miRNA families registered in miRBase version 20 from Arabidopsis thaliana; Oryza sativa; Populus trichocarpa; Prunus persica.

Axtell M.J., Snyder J.A., Bartel D.P. (2007) Common functions for diverse small RNAs of land plants. The Plant Cell, 19, 1750–1769. Barakat A., Sriram A., Park J., Zhebentyayeva T., Main D., Abbott A. (2012) Genome-wide identification of chilling responsive microRNAs in Prunus persica. BMC Genomics, 13, 481. Bartel D.P. (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 116, 281– 297. Bonnet E., Wuyts J., Rouze P., Van de Peer Y. (2004a) Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativa identifies important target genes. Proceedings of the National Academy of Sciences of the United States of America, 101, 11511–11516. Bonnet E., Wuyts J., Rouze P., Van de Peer Y. (2004b) Evidence that microRNA precursors, unlike other non-coding RNAs, have lower folding free energies than random sequences. Bioinformatics, 20, 2911– 2917. Carra A., Mica E., Gambino G., Pindo M., Moser C., Pe M.E., Schubert A. (2009) Cloning and characterization of small non-coding RNAs from grape. The Plant Journal, 59, 750–763. Chaib J., Torregrosa L., Mackenzie D., Corena P., Bouquet A., Thomas M.R. (2010) The grape microvine – a model system for rapid forward and reverse genetics of grapevines. The Plant Journal, 62, 1083– 1092. Chen M., Meng Y., Mao C., Chen D., Wu P. (2010) Methodological framework for functional characterization of plant microRNAs. Journal of Experimental Botany, 61, 2271–2280. Cuperus J.T., Fahlgren N., Carrington J.C. (2011) Evolution and functional diversification of miRNA genes. The Plant Cell, 23, 431–442.

Dai X., Zhao P.X. (2011) psRNATarget: a plant small RNA target analysis server. Nucleic Acids Research, 39, W155–W159. Dalmay T. (2010) Short RNAs in tomato. Journal of Integrative Plant Biology, 52, 388–392. Dezulian T., Remmert M., Palatnik J.F., Weigel D., Huson D.H. (2006) Identification of plant microRNA homologs. Bioinformatics, 22, 359–360. Ding J., Zhou S., Guan J. (2012) Finding microRNA targets in plants: current status and perspectives. Genomics, Proteomics & Bioinformatics, 10, 264–275. Eamens A., Wang M.-B., Smith N.A., Waterhouse P.M. (2008) RNA silencing in plants: Yesterday, today, and tomorrow. Plant Physiology, 147, 456–468. Eamens A.L., Agius C., Smith N.A., Waterhouse P.M., Wang M.B. (2011) Efficient silencing of endogenous microRNAs using artificial microRNAs in Arabidopsis thaliana. Molecular Plant, 4, 157–170. Eldem V., Celikkol Akcay U., Ozhuner E., Bakir Y., Uranbey S., Unver T. (2012) Genome-wide identification of miRNAs responsive to drought in peach (Prunus persica) by high-throughput deep sequencing. PLoS ONE, 7, e50298. Franco-Zorrilla J.M., Valli A., Todesco M., Mateos I., Puga M.I., Rubio-Somoza I., Leyva A., Weigel D., Garcia J.A., Paz-Ares J. (2007) Target mimicry provides a new mechanism for regulation of microRNA activity. Nature Genetics, 39, 1033–1037. Gambino G., Gribaudo I. (2012) Genetic transformation of fruit trees: current status and remaining challenges. Transgenic Research, 21, 1163– 1181. German M.A., Pillay M., Jeong D.H., Hetawal A., Luo S., Janardhanan P., Kannan V., Rymarquis L.A., Nobuta K., German R., De Paoli E., Lu C., Schroth G., Meyers B.C., Green P.J. (2008) Global identification of microRNA–target RNA pairs by parallel

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

Solofoharivelo, Walt, Stephan, Burger & Murray

analysis of RNA ends. Nature Biotechnology, 26, 941– 946. German M.A., Luo S., Schroth G., Meyers B.C., Green P.J. (2009) Construction of Parallel Analysis of RNA Ends (PARE) libraries for the study of cleaved miRNA targets and the RNA degradome. Nature Protocols, 4, 356–362. Gleave A.P., Ampomah-Dwamena C., Berthold S., Dejnoprat S., Karunairetnam S., Nain B., Wang Y.-Y., Crowhurst R.N., MacDiarmid R.M. (2008) Identification and characterisation of primary microRNAs from apple (Malus domestica cv. Royal Gala) expressed sequence tags. Tree Genetics & Genomes, 4, 343–358. Griffiths-Jones S. (2010) miRBase: microRNA sequences and annotation. Current Protocols in Bioinformatics, 12, 1–10. Gui Y.J., Yan G., Bo S., Tong Z., Wang Y., Xiao B., Lu X., Li Y., Wu W., Fan L. (2011) iSNAP: a small RNA-based molecular marker technique. Plant Breeding, 130, 515–520. Hanke M.V., Flachowsky H. (2010) Fruit crops. In: Jung C., Kempken F. (Eds), Genetic Modification of Plants – Agriculture, Horticulture and Forestry. Springer, Berlin, Germany, pp 307–348. Huijser P., Schmid M. (2011) The control of developmental phase transitions in plants. Development, 138, 4117–4129. International Peach Genome Initiative, Verde I., Abbott A.G., Scalabrin S., Jung S., Shu S., Marroni F., Zhebentyayeva T., Dettori M.T., Grimwood J., Cattonaro F., Zuccolo A., Rossini L., Jenkins J., Vendramin E., Meisel L.A., Decroocq V., Sosinski B., Prochnik S., Mitros T., Policriti A., Cipriani G., Dondini L., Ficklin S., Goodstein D.M., Xuan P., Del Fabbro C., Aramini V., Copetti D., Gonzalez S., Horner D.S., Falchi R., Lucas S., Mica E., Maldonado J., Lazzari B., Bielenberg D., Pirona R., Miculan M., Barakat A., Testolin R., Stella A., Tartarini S., Tonutti P., Arus P., Orellana A., Wells C., Main D., Vizzotto G., Silva H., Salamini F., Schmutz J., Morgante M., Rokhsar D.S (2013) The high-quality draft genome of peach (Prunus persica) identifies unique patterns of genetic diversity, domestication and genome evolution. Nature Genetics, 45, 487–494. Jaillon O., Aury J.M., Noel B., Policriti A., Clepet C., Casagrande A., Choisne N., Aubourg S., Vitulo N., Jubin C., Vezzi A., Legeai F., Hugueney P., Dasilva C., Horner D., Mica E., Jublot D., Poulain J., Bruyere C., Billault A., Segurens B., Gouyvenoux M., Ugarte E., Cattonaro F., Anthouard V., Vico V., Del Fabbro C., Alaux M., Di Gaspero G., Dumas V., Felice N., Paillard S., Juman I., Moroldo M., Scalabrin S., Canaguier A., Le Clainche I., Malacrida G., Durand E., Pesole G., Laucou V., Chatelet P., Merdinoglu D., Delledonne M., Pezzotti M., Lecharny A., Scarpelli C., Artiguenave F., Pe M.E., Valle G., Morgante M., Caboche M., Adam-Blondon A.F., Weissenbach J., Quetier F., Wincker P., French–Italian Public Consortium for Grapevine Genome Characterization (2007) The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature, 449, 463–467. Jelly N.S., Schellenbaum P., Walter B., Maillot P. (2012) Transient expression of artificial microRNAs targeting Grapevine fanleaf virus and evidence for RNA silencing in grapevine somatic embryos. Transgenic Research, 21, 1319–1327. Jones-Rhoades M.W. (2012) Conservation and divergence in plant microRNAs. Plant Molecular Biology, 80, 3–16.

MicroRNAs in fruit trees

Jones-Rhoades M.W., Bartel D.P. (2004) Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Molecular Cell, 14, 787–799. Jones-Rhoades M.W., Bartel D.P., Bartel B. (2006) MicroRNAS and their regulatory roles in plants. Annual Review of Plant Biology, 57, 19–53. Khraiwesh B., Zhu J.K., Zhu J. (2011) Role of miRNAs and siRNAs in biotic and abiotic stress responses of plants. Biochimica et Biophysica Acta, 1819, 137–148. Kozomara A., Griffiths-Jones S. (2011) miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Research, 39, D152–D157. Lazzari B., Caprera A., Cestaro A., Merelli I., Del Corvo M., Fontana P., Milanesi L., Velasco R., Stella A. (2009) Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs. BMC Plant Biology, 9, 82. Liang G., Li Y., He H., Wang F., Yu D. (2013) Identification of miRNAs and miRNA-mediated regulatory pathways in Carica papaya. Planta, 238, 739–752. Llave C., Franco-Zorrilla J.M., Solano R., Barajas D. (2011) Target validation of plant microRNAs. Methods in Molecular Biology, 732, 187–208. McCormick K.P., Willmann M.R., Meyers B.C. (2011) Experimental design, preprocessing, normalization and differential expression analysis of small RNA sequencing experiments. Silence, 2, 2. Mendes N.D., Freitas A.T., Sagot M.F. (2009) Current tools for the identification of miRNA genes and their targets. Nucleic Acids Research, 37, 2419–2433. Mica E., Piccolo V., Delledonne M., Ferrarini A., Pezzotti M., Casati C., Del Fabbro C., Valle G., Policriti A., Morgante M., Pesole G., Pe M.E., Horner D.S. (2010) Correction: High throughput approaches reveal splicing of primary microRNA transcripts and tissue specific expression of mature microRNAs in Vitis vinifera. BMC Genomics, 11, 109. Molesini B., Pii Y., Pandolfini T. (2011) Fruit improvement using intragenesis and artificial microRNA. Trends in Biotechnology, 30, 80–88. Palatnik J.F., Allen E., Wu X., Schommer C., Schwab R., Carrington J.C., Weigel D. (2003) Control of leaf morphogenesis by microRNAs. Nature, 425, 257–263. Pantaleo V., Szittya G., Moxon S., Miozzi L., Moulton V., Dalmay T., Burgyan J. (2010) Identification of grapevine microRNAs and their targets using highthroughput sequencing and degradome analysis. The Plant Journal, 62, 960–976. Poethig R.S. (2009) Small RNAs and developmental timing in plants. Current Opinion in Genetics and Development, 19, 374–378. Poethig R.S. (2010) The past, present, and future of vegetative phase change. Plant Physiology, 154, 541–544. Reinhart B.J., Weinstein E.G., Rhoades M.W., Bartel B., Bartel D.P. (2002) MicroRNAs in plants. Genes and Development, 16, 1616–1626. Rhoades M.W., Reinhart B.J., Lim L.P., Burge C.B., Bartel B., Bartel D.P. (2002) Prediction of plant microRNA targets. Cell, 110, 513–520. Schwab R., Ossowski S., Warthmann N., Weigel D. (2010) Directed gene silencing with artificial microRNAs. Methods in Molecular Biology, 592, 71–88. Song C., Fang J., Li X., Liu H., Thomas Chao C. (2009) Identification and characterization of 27 conserved microRNAs in citrus. Planta, 230, 671–685. Song C., Jia Q., Fang J., Li F., Wang C., Zhang Z. (2010a) Computational identification of citrus

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands

microRNAs and target analysis in citrus expressed sequence tags. Plant Biology, 12, 927–934. Song C., Wang C., Zhang C., Korir N.K., Yu H., Ma Z., Fang J. (2010b) Deep sequencing discovery of novel and conserved microRNAs in trifoliate orange (Citrus trifoliata). BMC Genomics, 11, 431. Stocks M.B., Moxon S., Mapleson D., Woolfenden H.C., Mohorianu I., Folkes L., Schwach F., Dalmay T., Moulton V. (2012) The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets. Bioinformatics, 28, 2059–2061. Sun G. (2011) MicroRNAs and their diverse functions in plants. Plant Molecular Biology, 80, 17–36. Sun Y.H., Shi R., Zhang X.H., Chiang V.L., Sederoff R.R. (2011) MicroRNAs in trees. Plant Molecular Biology, 80, 37–53. Sunkar R., Zhu J.K. (2004) Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. The Plant Cell, 16, 2001–2019. Sunkar R., Girke T., Jain P.K., Zhu J.K. (2005) Cloning and characterization of microRNAs from rice. The Plant Cell, 17, 1397–1411. Sunkar R., Li Y.F., Jagadeeswaran G. (2012) Functions of microRNAs in plant stress responses. Trends in Plant Science, 17, 196–203. Tang G., Yan J., Gu Y., Qiao M., Fan R., Mao Y., Tang X. (2012) Construction of short tandem target mimic (STTM) to block the functions of plant and animal microRNAs. Methods, 58, 118–125. Todesco M., Rubio-Somoza I., Paz-Ares J., Weigel D. (2010) A collection of target mimics for comprehensive analysis of microRNA function in Arabidopsis thaliana. PLoS Genetics, 6, e1001031. Varkonyi-Gasic E., Gould N., Sandanayaka M., Sutherland P., MacDiarmid R.M. (2010) Characterisation of microRNAs from apple (Malus domestica ‘Royal Gala’) vascular tissue and phloem sap. BMC Plant Biology, 10, 159. Velasco R., Zharkikh A., Troggio M., Cartwright D.A., Cestaro A., Pruss D., Pindo M., Fitzgerald L.M., Vezzulli S., Reid J., Malacarne G., Iliev D., Coppola G., Wardell B., Micheletti D., Macalma T., Facci M., Mitchell J.T., Perazzolli M., Eldredge G., Gatto P., Oyzerski R., Moretto M., Gutin N., Stefanini M., Chen Y., Segala C., Davenport C., Dematte L., Mraz A., Battilana J., Stormo K., Costa F., Tao Q., Si-Ammour A., Harkins T., Lackey A., Perbost C., Taillon B., Stella A., Solovyev V., Fawcett J.A., Sterck L., Vandepoele K., Grando S.M., Toppo S., Moser C., Lanchbury J., Bogden R., Skolnick M., Sgaramella V., Bhatnagar S.K., Fontana P., Gutin A., Van de Peer Y., Salamini F., Viola R. (2007) A high quality draft consensus sequence of the genome of a heterozygous grapevine variety. PLoS ONE, 2, e1326. Velasco R., Zharkikh A., Affourtit J., Dhingra A., Cestaro A., Kalyanaraman A., Fontana P., Bhatnagar S.K., Troggio M., Pruss D., Salvi S., Pindo M., Baldi P., Castelletti S., Cavaiuolo M., Coppola G., Costa F., Cova V., Dal Ri A., Goremykin V., Komjanc M., Longhi S., Magnago P., Malacarne G., Malnoy M., Micheletti D., Moretto M., Perazzolli M., Si-Ammour A., Vezzulli S., Zini E., Eldredge G., Fitzgerald L.M., Gutin N., Lanchbury J., Macalma T., Mitchell J.T., Reid J., Wardell B., Kodira C., Chen Z., Desany B., Niazi F., Palmer M., Koepke T., Jiwan D., Schaeffer S., Krishnan V., Wu C., Chu V.T., King S.T., Vick J., Tao Q., Mraz A., Stormo A., Stormo K., Bogden R., Ederle D., Stella A., Vecchietti A., Kater M.M., Masiero S., Lasserre P., Lespinasse Y., Allan A.C.,

9

MicroRNAs in fruit trees

Bus V., Chagne D., Crowhurst R.N., Gleave A.P., Lavezzo E., Fawcett J.A., Proost S., Rouze P., Sterck L., Toppo S., Lazzari B., Hellens R.P., Durel C.E., Gutin A., Bumgarner R.E., Gardiner S.E., Skolnick M., Egholm M., Van de Peer Y., Salamini F., Viola R. (2010) The genome of the domesticated apple (Malus x domestica Borkh.). Nature Genetics, 42, 833–839. Voinnet O. (2009) Origin, biogenesis, and activity of plant microRNAs. Cell, 136, 669–687. Wang C., Shangguan L., Kibet K.N., Wang X., Han J., Song C., Fang J. (2011a) Characterization of microRNAs identified in a table grapevine cultivar with validation of computationally predicted grapevine miRNAs by miR-RACE. PLoS ONE, 6, e21259. Wang C., Wang X., Kibet N.K., Song C., Zhang C., Li X., Han J., Fang J. (2011b) 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. Physiologia Plantarum, 143, 64–81. Wang C., Han J., Liu C., Kibet K.N., Kayesh E., Shangguan L., Li X., Fang J. (2012) Identification of

10

Solofoharivelo, Walt, Stephan, Burger & Murray

microRNAs from Amur grape (Vitis amurensis Rupr.) by deep sequencing and analysis of microRNA variations with bioinformatics. BMC Genomics, 13, 122. Wu X.M., Liu M.Y., Ge X.X., Xu Q., Guo W.W. (2011) Stage- and tissue-specific modulation of ten conserved miRNAs and their targets during somatic embryogenesis of Valencia sweet orange. Planta, 233, 495–505. Xia R., Zhu H., An Y., Beers E.P., Liu Z. (2012) Apple miRNAs and tasiRNAs with novel regulatory networks. Genome Biology, 13, R47. Xie F., Zhang B. (2010) Target-align: a tool for plant microRNA target identification. Bioinformatics, 26, 3002–3003. Xu Q., Liu Y., Zhu A., Wu X., Ye J., Yu K., Guo W., Deng X. (2010) Discovery and comparative profiling of microRNAs in a sweet orange red-flesh mutant and its wild type. BMC Genomics, 11, 246. Yan J., Gu Y., Jia X., Kang W., Pan S., Tang X., Chen X., Tang G. (2012) Effective small RNA destruction by the expression of a short tandem target mimic in Arabidopsis. The Plant Cell, 24, 415–427.

Yu H., Song C., Jia Q., Wang C., Li F., Nicholas K.K., Zhang X., Fang J. (2011) Computational identification of microRNAs in apple expressed sequence tags and validation of their precise sequences by miRRACE. Physiologia Plantarum, 141, 56–70. Zhang Z., Yu J., Li D., Zhang Z., Liu F., Zhou X., Wang T., Ling Y., Su Z. (2009) PMRD: Plant microRNA database. Nucleic Acids Research, 38, D806–D813. Zhang J.Z., Ai X.Y., Guo W.W., Peng S.A., Deng X.X., Hu C.G. (2012a) Identification of miRNAs and their target genes using deep sequencing and degradome analysis in trifoliate orange [Poncirus trifoliata (L.) Raf]. Molecular Biotechnology, 51, 44–57. Zhang Y., Yu M., Yu H., Han J., Song C., Ma R., Fang J. (2012b) Computational identification of microRNAs in peach expressed sequence tags and validation of their precise sequences by miR-RACE. Molecular Biology Reports, 39, 1975–1987. Zhu H., Xia R., Zhao B., An Y.Q., Dardick C.D., Callahan A.M., Liu Z. (2012) Unique expression, processing regulation, and regulatory network of peach (Prunus persica) miRNAs. BMC Plant Biology, 12, 149.

Plant Biology © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands