Literature DB >> 24376253

Global and local perturbation of the tomato microRNA pathway by a trans-activated DICER-LIKE 1 mutant.

Michael Kravchik1, Ramanjulu Sunkar, Subha Damodharan, Ran Stav, Matat Zohar, Tal Isaacson, Tzahi Arazi.   

Abstract

DICER-like 1 (DCL1) is a major player in microRNA (miRNA) biogenesis and accordingly, its few known loss-of-function mutants are either lethal or display arrested development. Consequently, generation of dcl1 mutants by reverse genetics and functional analysis of DCL1 in late-developing organs are challenging. Here, these challenges were resolved through the unique use of trans-activated RNA interference. Global, as well as organ-specific tomato DCL1 (SlDCL1) silencing was induced by crossing the generated responder line (OP:SlDCL1IR) with the appropriate driver line. Constitutive trans-activation knocked down SlDCL1 levels by ~95%, resulting in severe abnormalities including post-germination growth arrest accompanied by decreased miRNA and 21-nucleotide small RNA levels, but prominently elevated levels of 22-nucleotide small RNAs. The increase in the 22-nucleotide small RNAs was correlated with specific up-regulation of SlDCL2b and SlDCL2d, which are probably involved in their biogenesis. Leaf- and flower-specific OP:SlDCL1IR trans-activation inhibited blade outgrowth, induced premature bud senescence and produced pale petals, respectively, emphasizing the importance of SlDCL1-dependent small RNAs in these processes. Together, these results establish OP:SlDCL1IR as an efficient tool for analysing processes regulated by SlDCL1-mediated gene regulation in tomato.

Entities:  

Keywords:  Carotenoid; DCL1; leaf; miRNA; mutant; petal; tomato.

Mesh:

Substances:

Year:  2013        PMID: 24376253      PMCID: PMC3904720          DOI: 10.1093/jxb/ert428

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


Introduction

Small RNAs, ranging from 20 to 24 nucleotides (nt) in size, have many key functions in plants, particularly in genome stability, regulation of gene expression, and defence by directing sequence-specific repression of target RNAs (Chen, 2009; Axtell, 2013). Plant microRNAs (miRNAs) constitute a major class of endogenous small RNAs that have emerged as important post-transcriptional regulators of plant development, stress responses, and nutrient homeostasis (Jones-Rhoades ; de Lima ; Sunkar ). In contrast to small interfering RNAs (siRNAs), which are generated via processing of long double-stranded RNA precursors with perfect complementarity, miRNAs are processed from a single-stranded RNA precursor transcript or pri-miRNA that can form imperfect fold-back structures (Reinhart ). The diversification of small RNA pathways in plants can be attributed in part to specific DICER-like (DCL) proteins that specialize in the production of distinct small RNAs. Four types of DCLs are present in all angiosperms (Margis ). Among them, the product of DCL1, also termed SHORT INTEGUMENTS1 (SIN1)/SUSPENSOR1 (SUS1)/CARPEL FACTORY (CAF) (Robinson-Beers ; Jacobsen ; McElver ; Schauer ), catalyses the formation of predominantly 20- to 22-nt canonical miRNAs (Park ; Reinhart ; Kurihara and Watanabe, 2004). In addition, certain inverted repeat-derived siRNAs and secondary siRNAs—including trans-acting siRNAs (ta-siRNAs), natural antisense siRNAs, and phased siRNAs—which do not derive from fold-back structures but arise from transcripts targeted by miRNAs, also depend on DCL1 for their accumulation (Allen ; Borsani ; Henderson ; Li ; Shivaprasad ). Moreover, DCL1 was found to contribute to the silencing of a subset of transposons, apparently through an effect on DNA methylation (Laubinger ). DCL2 catalyses the formation of 22-nt siRNAs and 22- to 24-nt natural antisense siRNAs (Xie ; Borsani ; Deleris ). DCL3 is responsible for the processing of 24-nt heterochromatin-associated siRNAs (hc-siRNAs) and long miRNAs (Xie ; Qi ; Wu ). DCL4 sequentially processes 21-nt secondary siRNAs including ta-siRNAs and other phased siRNAs, and is required for the production of several Arabidopsis thaliana miRNAs such as miR822 and miR839 (Xie ; Gasciolli ; Rajagopalan ; Howell ). To date, dcl1 loss-of-function mutants have been isolated from Arabidopsis, Oryza sativa, and the moss Physcomitrella patens (Schauer ; Liu ; Khraiwesh ). In Arabidopsis, null dcl1 alleles (sus1) are embryo lethal (Castle ). In addition, several hypomorphic dcl1 mutants have been described, such as dcl1-7 (sin 1-1) and dcl1-9 (caf), which show pleiotropic developmental phenotypes due to reduced miRNA levels (Robinson-Beers ; Jacobsen ; Park ). Physcomitrella harbours two DCL1-like proteins, PpDCL1a and PpDCL1b. Deletion of PpDCL1a but not PpDCL1b drastically reduced miRNA levels, indicating its functional equivalence to AtDCL1. ΔPpDCL1a-null mutants showed developmental defects and abnormalities in cell size and shape; their growth was severely retarded and they were developmentally arrested at the filamentous protonema stage (Khraiwesh ). In rice, a DCL1 loss-of-function mutant (OsDCL1IR) was generated by RNA interference (RNAi). Silenced plants had reduced levels of miRNAs, developed severe dwarfism, rolled and curly leaves, and tortuous shoots, and were arrested at the young seedling stage (Liu ). The lethality and severe growth arrest associated with dcl1 loss-of-function mutants prevents their functional characterization at late developmental stages. It also impedes the generation of dcl1 loss-of-function mutants by reverse genetics in plants whose transformation includes a regeneration phase in tissue culture. For example, attempts to stably silence Nicotiana attenuata DCL1 by RNAi have failed due to lethality of the regenerated transformants (Bozorov ). Solanum lycopersicum (tomato) is one of the most important crops in the fresh vegetable market and the food-processing industry, and is a good model for crop species with fleshy berry fruits (Giovannoni, 2001). Deep sequencing of small RNAs from various tomato tissues has revealed the presence of a complex population of small RNAs, including miRNAs (Moxon ; Li ; Shivaprasad ; Axtell, 2013). Recently, a tomato dcl4 mutant has been described, demonstrating its function in the biogenesis of ta-siRNAs and their involvement in the regulation of lamina expansion during compound leaf development (Yifhar ). The functions of other tomato DCLs, including DCL1, remain unstudied. In the current study, a trans-activated RNAi approach was employed to silence tomato DCL1 (SlDCL1) globally or in specific organs, and the resulting mutants were utilized to investigate SlDCL1 functions in small RNA biogenesis and development.

Materials and methods

Plant material and growth conditions

The tomato (S. lycopersicum) cv. M82 driver lines 35S:LhG4, FIL:LhG4 (Lifschitz ), AP1:LhG4, and AP3:LhG4 (Fernandez ; Hendelman ) are described elsewhere. Tomato plants were grown under greenhouse conditions with temperatures ranging between 15 °C and 30 °C in a tuff–peat mix with nutrients, using 4 litre pots. Germination and seedling growth took place in a growth chamber with a 16h light period and 8h dark period (photosynthetic photon flux density: 50–70 μmol m–2 s–1) at a constant temperature of 24 °C. For crosses, closed flowers were emasculated by removal of the petals and stamens and hand pollinated with the pollen of an appropriate homozygous driver line.

Sequencing of full-length SlDCL1 and SlDCL2a, b, and d 5′-untranslated regions (UTRs)

To determine the full-length sequence of SlDCL1, total RNA was extracted from tomato cv. M82 flowers at anthesis as described below and a 3′ and 5′ RNA ligase-mediated rapid amplification of cDNA ends (RLM-RACE) procedure was performed on this RNA. The partial Solyc10g005130 sequence was used to design gene-specific primers (all primer sequences are given in Supplementary Table S1 available at JXB online) as follows: for the 5′ end, SlDCL1-5′-RACE and SlDCL1-5′-RACE-nested; for the 3′ end, SlDCL1-3′-RACE and SlDCL1-3′-RACE-nested. The resulting amplified products were gel-purified, cloned, and sequenced. After assembling the full-length sequence of SlDCL1, its 5′ (nt 86–2685) and overlapping 3′ (nt 2481–6168) cDNA sequences were PCR-amplified with SlDCL1_F_XhoI and SlDCL1_R_2685, and SlDCL1_F_2481 and SlDCL1_R_6168, respectively, and sequenced. The 5′ UTR of SlDCL2b (Solyc11g008540) was determined by RLM-RACE of total flower RNA with SlDCL2b-5′-RACE and SlDCL2b-5′-RACE-nested primers. On the basis of their sequence, the 5′ UTRs of SlDCL2a (Solyc06g048960) and SlDCL2d (Solyc11g008530) were determined by PCR on flower cDNA with the primer pairs SlDCL2a_F_28 and qRT-SlDCL2a_R, and SlDCL2d_R_280 and qRT-SlDCL2d_F, respectively. Amplified products were then gel-purified and sequenced directly.

Plasmid construction

For the SlDCL1IR RNAi reporter construct, a 674bp SlDCL1 sequence composed of 264bp and 410bp of its promoter and cDNA, respectively, was amplified by two-step PCR. The primers SlDCL1IRDNA_F, which contains SalI and PstI sites at its 5′ end, and SlDCL1IRDNA_R were used to amplify the promoter sequence. Primers SlDCL1IRRNA_F and SlDCL1IRRNA_R, which contains HindIII/EcoRI sites at its 5′ end, were used to amplify an overlapping fragment that contained the cDNA sequence. Then the 674bp product was assembled by using the amplified fragments as a template for PCR with primer pair SlDCL1IRDNA_F and SlDCL1IRRNA_R. The amplified assembled fragment was restricted with either PstI/EcoRI or SalI/HindIII and cloned in sense and antisense orientation, respectively, around the first intron of the Arabidopsis AKT1 gene to generate max2intpFLAP-SlDCL1IR. Following sequence validation, the max2intpFLAP-SlDCL1IR XhoI fragment was mobilized into the XhoI site of the OP-TATA-BJ36 shuttle vector between an OP array (Moore ) and Agrobacterium tumefaciens octopine synthase terminator (OCS) to generate OP:SlDCL1IR. Following orientation validation, the NotI fragment of the OP:SlDCL1IR vector was mobilized into the binary vector pART27 to generate pART27-OP:SlDCL1IR.

Transformation of tomato plants

The binary vector pART27-OP:SlDCL1IR was transformed into tomato cv. M82 as described previously (Hendelman ). Transgenic progeny were selected by germinating sterilized seeds on selective medium [1× Murashige and Skoog (MS) medium, 3% (w/v) sucrose, 100mg l–1 kanamycin], where only transgenic seedlings developed a branched root system. Further validation was performed by PCR of genomic DNA with the primer pair pFlap_intron_F and OCS_rev to detect the OP:SlDCL1IR transgene.

Total RNA extraction and small RNA gel-blot analysis

Total RNA was isolated from tomato tissues as described previously (Hendelman ). Blot hybridization analysis was performed according to Stav . Radiolabelled probes were made by 5′-end-labelling DNA oligonucleotides complementary to the corresponding small RNA sequences (probe sequences are listed in Supplementary Table S1 available at JXB online) with [γ-32P]ATP by means of T4 polynucleotide kinase (New England Biolabs, Ipswich, MA, USA). Blots were pre-hybridized and hybridized with EZ-hybridization solution (Biological Industries, Bet-Haemek, Israel). Hybridization was performed at 40 °C overnight. Blots were washed three times at 50 °C with washing buffer (2× SSC, 0.1% SDS) and autoradiographed using a phosphoimager (Fuji).

Real-time quantitative PCR (qRT-PCR) analyses

Total RNA was extracted from the indicated tomato tissues as described above. DNase treatment, concentration determination, preparation of cDNA from 1 μg of total RNA, and real-time quantitative PCR were performed as described in Hendelman ). The relative expression levels of all transcripts were calculated using the two standard curve method normalized to TIP41 or CAC as reference genes.

Small RNA libraries constructions, sequencing, and bioinformatic analyses

Total RNA was extracted from shoots of control (35S:LhG4) and SlDCL1-silenced (35S>>SlDCL1) seedlings 14 d after sowing (two biological replicates per genotype combined from 12 seedlings each) using Bio-TRI RNA reagent (Bio-Lab, Jerusalem, Israel) according to the manufacturer’s protocol. Extracted RNA samples were used to construct two control and two SlDCL1-silenced small RNA libraries (Supplementary Table S2 available at JXB online) using the TruSeq small RNA kit (Illumina, San Diego, CA, USA) as described by the manufacturer, and submitted to sequencing on an Illumina HiSeq 2000 analyser. Sequencing was performed by Illumina. The data for this article have been deposited at the National Center for Biotechnology Information Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE51959. The small RNA sequences from all sequenced libraries were parsed, mapped, quantified, and managed using The Cache ASsisted Hash Search with Xor logic (CASHX) Pipeline (release 2.3) (Fahlgren ). All reads were mapped to the tomato genome (SGN release version SL2.40; http://solgenomics.net/organism/Solanum_lycopersicum/genome) and perfectly matching reads in the size range of 18–26 nt were retained. The small RNA CASHX database was annotated with the Repeats Master version 5.0 (ftp://ftp.solgenomics.net/tomato_genome/repeats/), Plant snoRNAs Database (version 1.2; http://bioinf.scri.sari.ac.uk/cgi-bin/plant_snorna/home), SILVA rRNA database (http://www.arb-silva.de/), miRbase (release 19, http://www.mirbase.org/), and the tomato genome annotation (SGN release version ITAG2.3; ftp://ftp.solgenomics.net/tomato_genome/annotation/ITAG2.3_release/). After annotation, only ‘clean’ reads not matching tRNAs, rRNAs, small nuclear RNAs (snRNAs), or small nucleolar RNAs (snoRNAs) were used for further analysis. For all small RNA data analyses, clean reads from both biological replicates were used. The differential expression between control and SlDCL1-silenced clean small RNAs (two biological replicates per genotype) was performed by the analysis of digital gene expression data in the R (EdgeR) package (version 3.07) (Robinson ). By using this package, first low count reads were removed in each library by retaining reads with at least 1 count per million in at least three samples. Then normalization factors were calculated, effective library sizes were estimated by using normalization factors, fitted according to the Negative Binomial model, estimates of common dispersions were made, and differential expression tests were performed. The resultant P-values were adjusted for false discovery rate (FDR) and only adjusted P-values <0.05 were considered statistically significant. Cluster analysis of clean reads against the tomato genome was performed using the ShortStack software tool (version 0.4.1) (Axtell, 2013) with options -mindepth=10 and -inv. The Inv file was generated from the tomato SL2.40 genome by einverted (EMBOSS 6.3.1) with option -maxrepeat 10000. Clean small RNAs from both biological replicates of each genotype were used as input to the ShortStack pipeline.

Carotenoid determination in petals

Total pigments from petals at anthesis (~100mg) were extracted with acetone. Acetone samples were dried under a stream of N2 and dissolved in 450 μl of ethanol. Then, 50 μl of 60% KOH (w/v) were added and samples were incubated in the dark for 16h at 4 °C for saponification. Saponified samples were mixed gently with 0.5ml of diethyl ether and 0.1ml of 12% (w/v) NaCl/H2O. The upper phase was collected and dried under a stream of N2 and dissolved in acetone for further analysis. Total carotenoid content was determined spectroscopically at 440nm using an extinction coefficient of 2400 (Schiedt and Liaaen-Jensen, 1995). For identification, carotenoids were separated by reverse-phase high performance liquid chromatography (RP-HPLC) using a Waters 600 system (Waters, Milford, MA, USA) and a Spherisorb ODS2 C18 column (silica 5 μm, 3.2 mm×250mm) (Phenomenex, Torrance, CA, USA). The mobile phase consisted of acetonitrile:water (9:1; A) and ethylacetate (B), at a constant flow rate of 1.6ml min–1. The gradient was: 100% to 80% A during 8min; 80% to 65% A during 4min; followed by 65% to 45% A during 14min; and a final segment of 7min at 100% B. Spectra at the wavelength range of 250–700nm of eluting HPLC solvent were recorded and absorption peaks were detected. Carotenoids were identified by their absorption spectra and retention time.

Results

Generation of a reporter line that is able to silence the tomato DCL1 homologue upon trans-activation

The full-length sequence of the tomato DCL1 homologue was determined (SlDCL1; GenBank accession no. JX962774). Sequence analysis suggested that it is targeted by sly-miR162, similar to AtDCL1 mRNA (Xie ), and encodes a DCL1-like protein (Supplementary Fig. S1A available at JXB online). Analysis of published RNA sequencing data indicated that SlDCL1 is expressed at similar levels in vegetative and reproductive organs, with maximum expression in the root and minimum expression in breaking fruit (Tomato Genome Consortium, 2012) (Supplementary Fig. S1B available at JXB online). In the absence of a tomato dcl1 mutant, its function was addressed by silencing it in transgenic tomato. However, plant dcl1 loss-of-function mutants are likely to be either lethal or arrested during early development (Errampalli ; Castle ; Liu ). To overcome this problem, a trans-activated RNAi was employed via the OP/LhG4 transcription factor system. A responder RNAi construct (OP:SlDCL1IR) that spanned the transcriptional start site of SlDCL1 was constructed with the intention of improving knockdown efficiency by invoking post-transcriptional as well as transcriptional silencing of SlDCL1 (Fig. 1A; Supplementary Fig. S1A available at JXB online). Following OP:SlDCL1IR transformation into M82 tomato and characterization of regenerated transgenic responder plants, the OP:SlDCL1IR-13 responder line (hereafter OP:SlDCL1IR) was selected for further analysis because SlDCL1 was almost completely silenced (~5% of control plants) in its trans-activated F1 progeny (35S>>SlDCL1IR) (Fig. 1B). The strong silencing was associated with the accumulation of siRNAs that matched SlDCL1 mRNA as well as its putative promoter (Fig. 1C), demonstrating the functionality of the RNAi construct and the usefulness of trans-activation for DCL1 silencing. In agreement with DCL1 being the primary producer of canonical miRNAs (Park ; Kurihara and Watanabe, 2004), northern blots of 35S>>SlDCL1IR seedlings revealed decreased levels of several known tomato miRNAs, but no significant change in the levels of type III fold-back transposon anionic peroxidase inverted repeat (TAPIR)-derived heterochromatic siRNA (Moxon ) (Fig. 1D). Consistent with the down-regulation of miRNAs, corresponding target mRNA levels increased significantly (Fig. 1E). In accordance with the perturbation of their miRNA pathway, the 35S>>SlDCL1IR seedlings could only germinate in tissue culture, had narrow cotyledons, and their development was arrested at the first to third true leaf primordium stage (Fig. 2).
Fig. 1.

Molecular characterization of 35S>>SlDCL1IR plants. (A) Schematic representation of the binary responder SlDCL1 RNAi (pART27-OP:SlDCL1IR) construct. (B) Quantitative RT-PCR analysis of SlDCL1 transcript in 35S>>SlDCL1IR seedlings 28 d after sowing. Primers were designed around the miR162 complementary site, and TIP41 expression values were used for normalization. Data are means ±SD of three independent biological repeats, each measured in triplicate. An asterisk indicates a significant difference as determined by Student’s t-test (P ≤ 0.01). (C) Schematic of siRNA accumulation at the SlDCL1IR RNAi sequence. The siRNA sequences were determined by deep sequencing of the seedling RNA used for qRT-PCR analysis in B. The normalized abundances of siRNAs were plotted relative to the sequence used for RNAi (Supplementary Table S1 available at JXB online) as a function of the positions of their 5′ ends. Maximum normalized reads per million (RPM) were set at 200/–200 to enable the visualization of relatively low abundance siRNAs. TSS, transcription start site as determined by RACE. (D) RNA gel-blot analysis of small RNAs in the RNA samples analysed in B. The total RNA (2.5 μg) was hybridized with the indicated small RNA antisense probe. An antisense probe for U6 snRNA served as a loading control. Small RNA expression was normalized to U6 snRNA, and levels are indicated below each panel. (E) qRT-PCR analysis of miRNA target transcripts in the RNA samples analysed in B. The corresponding miRNA is shown below each target mRNA. TIP41 expression values were used for normalization. Error bars indicate ±SD of three biological replicates, each measured in triplicate. Asterisks indicate significant difference as determined by Student’s t-test (P ≤ 0.01).

Fig. 2.

Phenotypic characterization of 35S>>SlDCL1IR seedlings. (A–C) Phenotypes of control (35S:LhG4) and 35S>>SlDCL1IR plants. (A) Seedlings at 28 d after sowing. (B) A magnified view of cotyledons from the seedlings in A. (C) A magnified view of shoot apices from the seedlings in A.

Molecular characterization of 35S>>SlDCL1IR plants. (A) Schematic representation of the binary responder SlDCL1 RNAi (pART27-OP:SlDCL1IR) construct. (B) Quantitative RT-PCR analysis of SlDCL1 transcript in 35S>>SlDCL1IR seedlings 28 d after sowing. Primers were designed around the miR162 complementary site, and TIP41 expression values were used for normalization. Data are means ±SD of three independent biological repeats, each measured in triplicate. An asterisk indicates a significant difference as determined by Student’s t-test (P ≤ 0.01). (C) Schematic of siRNA accumulation at the SlDCL1IR RNAi sequence. The siRNA sequences were determined by deep sequencing of the seedling RNA used for qRT-PCR analysis in B. The normalized abundances of siRNAs were plotted relative to the sequence used for RNAi (Supplementary Table S1 available at JXB online) as a function of the positions of their 5′ ends. Maximum normalized reads per million (RPM) were set at 200/–200 to enable the visualization of relatively low abundance siRNAs. TSS, transcription start site as determined by RACE. (D) RNA gel-blot analysis of small RNAs in the RNA samples analysed in B. The total RNA (2.5 μg) was hybridized with the indicated small RNA antisense probe. An antisense probe for U6 snRNA served as a loading control. Small RNA expression was normalized to U6 snRNA, and levels are indicated below each panel. (E) qRT-PCR analysis of miRNA target transcripts in the RNA samples analysed in B. The corresponding miRNA is shown below each target mRNA. TIP41 expression values were used for normalization. Error bars indicate ±SD of three biological replicates, each measured in triplicate. Asterisks indicate significant difference as determined by Student’s t-test (P ≤ 0.01). Phenotypic characterization of 35S>>SlDCL1IR seedlings. (A–C) Phenotypes of control (35S:LhG4) and 35S>>SlDCL1IR plants. (A) Seedlings at 28 d after sowing. (B) A magnified view of cotyledons from the seedlings in A. (C) A magnified view of shoot apices from the seedlings in A.

Small RNAs that depend on SlDCL1 for their biogenesis

To determine the effect of SlDCL1 silencing on global small RNA metabolism in tomato, the small RNA populations of control and 35S>>SlDCL1IR seedlings were compared using Illumina sequencing by synthesis technology. Two small RNA libraries, representing biological replicates, were prepared and sequenced from each genotype, generating >19 million raw reads in total (Supplementary Table S2 available at JXB online). For the analyses presented here, only sequences that were 18–26 nt in length were used. Depending on the library, read representation was between 6 and 4 million, from which ~70% matched the published tomato genome. Around 30% of the matched reads originated from tRNA, rRNA, snRNA, and snoRNA sequences. The remaining genome-matched reads (referred to as clean reads hereafter) were used for further analysis and represented ~1 million distinct tomato small RNA sequences (Supplementary Table S2 available at JXB online). The abundance of small RNAs was calculated as reads per million (RPM). After processing, clean small RNAs were annotated as described in the Materials and methods (Supplementary Table S3 available at JXB online). Consistent with the distribution of small RNA sizes that is typically observed in rice and Arabidopsis (Kasschau ; Wu ), in 35S:LhG4, the 24-nt small RNAs accounted for 45% of the population, making them the most abundant size class, with 21-nt small RNAs forming a secondary peak (Fig. 3A). Compared with 35S:LhG4 control seedlings, in 35S>>SlDCL1IR, the 21-nt size class was under-represented, whereas the 22-nt size class was over-represented (Fig. 3A), but a significant change in diversity was not observed (Fig. 3B). The question then was which tomato small RNAs require SlDCL1 for their biogenesis. EdgeR and ShortStack analyses were employed to identify the small RNAs and their producing loci, respectively, that show significantly modified expression on SlDCL1 down-regulation (Robinson ; Axtell, 2013). First, to identify and annotate the wild-type tomato small RNA clusters, the 35S:LhG4 clean small RNAs were subjected to ShortStack analysis. Then, the expression of 35S>>SlDCL1IR clean small RNAs from identified wild-type clusters was quantified and the clusters were re-annotated accordingly. ShortStack analysis of control clean small RNAs identified 128 621 small RNA-producing clusters, of which 92 were annotated as MIRNA-derived clusters (Supplementary Table S4 available at JXB online). Since DCL1 is known to catalyse the formation of predominantly 21-nt RNAs (Park ; Reinhart ; Qi ), the analysis was focused on the clusters that contained significant numbers (≥25 RPM) of 21-nt small RNAs and are therefore more likely to involve SlDCL1 in their biogenesis. Only 995 clusters fulfilled this criterion, and 132 of these showed at least a 2-fold change in their 21-nt small RNA numbers upon SlDCL1 silencing (hereafter termed DEclusters). Eighty-nine DEclusters were underexpressed in 35S>>SlDCL1IR relative to controls (Supplementary Table S5 available at JXB online). Cluster_61425, which derived from the MIR395a locus and contained ~30-fold fewer 21-nt small RNAs in 35S>>SlDCL1IR, showed the strongest decrease. As expected, MIRNA-derived small RNAs were almost exclusively down-regulated in 35S>>SlDCL1IR seedlings, and MIRNA-encoding loci comprised the largest group (61%, 32/89) of underexpressed DEclusters (Supplementary Table S5 available at JXB online). The results of the ShortStack analysis also indicated that several miRBase tomato miRNAs were not the most abundant small RNAs from their hairpin precursors and corresponded either to the predicted miRNA* [sly-miR6027 (Cluster_134922), sly-miR1919a-c (1892963), sly-miR5301 (Cluster_93957)] or to an undefined pre-miRNA position [sly-miR5302 (Cluster_93957)]. In the case of sly-miR5301, the predicted miRNA was found to be a close homologue of miR482. EdgeR analysis identified 2.5% (1421 of 56 052) and 0.9% (494 of 56 052) of the relatively abundant clean small RNAs (at least 1 RPM in three libraries), that had at least 2-fold fewer or more reads (FDR ≤0.05), respectively, in 35S>>SlDCL1IR relative to the control (Supplementary Table S6 available at JXB online). Among the down-regulated small RNAs, many were 21–22 nt in length originating from MIRNA genes, but also small RNAs 23–24 nt in length, which derived from non-annotated genomic loci and not likely to be produced by SlDCL1 (Qi ), were present (Fig. 3C, D). In contrast, among the up-regulated small RNAs, most were 21–22 nt in length, derived from non-annotated genomic loci (Fig. 3C, D). In agreement with the ShortStack analysis, edgeR analysis indicated the significant down-regulation of 47 miRNAs in 35S>>SlDCL1IR relative to controls (Supplementary Table S6 available at JXB online). Annotation of these miRNAs indicated that 14 were identical to miRBase, 16 were homologues of known miRNAs, and 17 represented novel miRNAs. The degree of miRNA down-regulation was 4-fold on average, but varied considerably between miRNAs, indicating differential SlDCL1 requirement for their biogenesis (Fig. 3E).
Fig. 3.

Characterization of small RNAs from control (35S:LhG4) and 35S>>SlDCL1IR seedlings. (A, B) Size distribution of small RNAs in the indicated genotypes. The distributions of total (A) and unique (B) small RNAs are shown. Data are means ±SD of two biological replicates. (C–E) Characterization of differentially expressed small RNAs. (C) Size distribution of differentially expressed small RNAs. (D) Features of genomic loci that generate the small RNAs shown in C. (E) Change in miRNA accumulation upon SlDCL1 silencing.

Characterization of small RNAs from control (35S:LhG4) and 35S>>SlDCL1IR seedlings. (A, B) Size distribution of small RNAs in the indicated genotypes. The distributions of total (A) and unique (B) small RNAs are shown. Data are means ±SD of two biological replicates. (C–E) Characterization of differentially expressed small RNAs. (C) Size distribution of differentially expressed small RNAs. (D) Features of genomic loci that generate the small RNAs shown in C. (E) Change in miRNA accumulation upon SlDCL1 silencing. In tomato, sly-miR390- and sly-miR482c-guided cleavage sets the phase for the biogenesis of trans-acting siRNA gene 3 (TAS3)-derived and TAS5-derived ta-siRNAs, respectively (Li ). EdgeR analysis suggested that sly-miR390 and sly-miR482c are significantly down-regulated, by 3.9- and 5.4-fold, respectively, in 35S>>SlDCL1IR seedlings (Fig. 3E). Consistent with this, the present analysis revealed significantly fewer TAS3-1 and TAS5 ta-siRNAs in 35S>>SlDCL1IR seedlings, thus confirming the requirement of SlDCL1 for ta-siRNA biogenesis (Fig. 4A, C). In contrast, a slight increase, rather than the expected decrease, was observed in the numbers of TAS4-derived (Cluster 99854) ta-siRNAs (Fig. 4B). Since the expression of TAS4 is induced by different stresses (Hsieh ), a possible explanation is that an increase in TAS4 transcription occurred in the stressed 35S>>SlDCL1IR seedlings.
Fig. 4.

Effect of SlDCL1 silencing on phased siRNA accumulation. Schematic of 35S>>SlDCL1IR and control siRNA accumulation at indicated TAS (A–C) and R genes (D). The normalized abundances of siRNAs were plotted relative to their mRNA sequence as a function of the positions of their 5′ ends. Values above and below zero indicate siRNA matching of the plus and minus strand, respectively. The corresponding miRNA cleavage site is indicated. Bars=21 nt. Size distribution of total gene-derived siRNAs is shown on the right. Data are means of two biological replicates.

Effect of SlDCL1 silencing on phased siRNA accumulation. Schematic of 35S>>SlDCL1IR and control siRNA accumulation at indicated TAS (A–C) and R genes (D). The normalized abundances of siRNAs were plotted relative to their mRNA sequence as a function of the positions of their 5′ ends. Values above and below zero indicate siRNA matching of the plus and minus strand, respectively. The corresponding miRNA cleavage site is indicated. Bars=21 nt. Size distribution of total gene-derived siRNAs is shown on the right. Data are means of two biological replicates. Except for ta-siRNAs, which depend on initial cleavage by miRNA for their biogenesis (Allen ), cleavage by 22-nt miRNAs was found to set up the production of secondary 21-nt siRNAs from various target RNAs (Chen ; Cuperus ). In tomato and Medicago, such a mechanism was suggested to trigger the production of phased secondary 21-nt siRNAs from nucleotide-binding site (NBS)–leucine-rich repeat (LRR) R genes, thus preventing their unregulated expression (Li ; Zhai ; Shivaprasad ). Accordingly, most (78%, 14/18) of the gene-derived DEclusters contained 21-nt siRNAs that matched NBS–LRR-encoding loci (Supplementary Table S5 available at JXB online). The 21-nt small RNA numbers from this DEcluster set were reduced by 2- to 5.3-fold upon SlDCL1 silencing, probably as a result of lower levels of the miRNA that triggers their biogenesis. An example of an NBS–LRR gene-derived DEcluster (Cluster_146573), which is predicted to be triggered by sly-miR6024-mediated cleavage, is shown in Fig. 4D. Indeed, in 35S>>SlDCL1IR seedlings, sly-miR6024 was down-regulated 4-fold and Solyc11g071430-derived 21-nt phased siRNA numbers decreased by 2.6-fold. The rest of the down-regulated gene-derived DEclusters were generated from genes with unknown functions. In addition, the analysis identified 13 repeat-associated DEclusters that were down-regulated upon SlDCL1 silencing, suggesting its involvement in the biogenesis of siRNAs from these loci (Supplementary Table S5 available at JXB online).

SlDCL1 silencing induces the up-regulation of certain SlDCL2 genes

It has been suggested that soybean and Medicago DCL2 mRNAs are targeted by the 22-nt miR1515 and miR1507, respectively, triggering the generation of 21-nt secondary phased siRNAs (Li ; Zhai ). Tomato has four DCL2 genes (SlDCL2a–d), three of which (SlDCL2b–d) are clustered on chromosome 11 (SL2.40ch11:2690601–2724508) (Bai ). Similar to Medicago DCL2, ShortStack analysis identified small RNA clusters that were derived from SlDCL2a (clusters 78419–78430), SlDCL2b (clusters 136462–136472), SlDCL2c (clusters 136447–136454), and SlDCL2d (clusters 136455–136460). These clusters were almost all (34/35) dominated by 21-nt small RNAs (DicerCall=21) that in a few cases were significantly phased (Supplementary Table S5, Fig. S2 available at JXB online). In addition, a legitimate target site for the 22-nt sly-miR6026 was predicted in the 5′ UTRs of SlDCL2a, b, and d but not in SlDCL2c, which contains a different sequence instead (Fig. 5A). Cleavage by 22-nt miRNAs has been shown to induce the biogenesis of 21-nt secondary siRNAs (Cuperus ), raising the possibility that sly-miR6026 acts as a trigger for siRNA biogenesis from SlDCL2a, b, and d. In Medicago, miR1507 has been suggested to target DCL2 as well as NBS–LRR genes (Zhai ). Consistent with this, sly-miR6026 has been predicted to target the Tobacco mosaic virus resistance gene of tomato (TM2, Solyc09g018220) (Li ), and ShortStack analysis identified 21-nt small RNA clusters that derived from it (clusters 113162 and 113163) (Supplementary Table S5 available at JXB online), suggesting that similar to miR1507 in Medicago, in tomato, sly-miR6026-guided cleavage of SlDCL2a, b, and d as well as the NBS–LRR TM2 gene triggers secondary siRNA production. RNA gel blots detected a slight decrease in sly-miR6026 upon global and tissue-specific (see below) SlDCL1 silencing (Fig. 5B). However, the present analysis indicated that a significant increase, rather than a decrease, in the numbers of SlDCL2a, b, and d-derived small RNAs had occurred in 35S>>SlDCL1IR seedlings (Supplementary Table S5, Fig. S2 available at JXB online). The most significant increase was in SlDCL2b (DEclusters 136464–136470, average of ~4.73±0.97-fold) and SlDCL2d (DEclusters 136455–136458, average of ~3.13±1.02-fold). Possible explanations include an increase in the expression of either SlDCL4, which is required for 21-nt phased siRNA biogenesis (Yifhar ), or SlDCL2b and d, whose transcripts may serve as substrates for sly-miR6026-mediated cleavage. qRT-PCR analysis of these genes in different SlDCL1-depleted tissues confirmed the significant increase in SlDCL2b and d accumulation, whereas accumulation of SlDCL2a, SlDCL3, and SlDCL4 was not significantly changed (Fig. 5C, D). Since DCL2 has been shown to be required for the formation of 22-nt siRNAs (Xie ; Gasciolli ; Deleris ), the up-regulation of SlDCL2b and d in 35S>>SlDCL1IR seedlings might explain the global increase in 22-nt numbers (Fig. 3A) and the majority (43%) of the 22-nt up-regulated DEclusters (Supplementary Table S5 available at JXB online).
Fig. 5.

Certain SlDCL2 paralogues are up-regulated upon SlDCL1 silencing. Sequence alignment between SlDCL2 genes (A) predicted to serve as sly-miR6026 targets. Identical nucleotides in all or at least three sequences are shaded in black and grey, respectively. Watson–Crick pairing with sly-miR6026 is shown below. Mismatched nucleotides are in lower case. (B) RNA gel-blot analysis of sly-miR6026 in the indicated genotypes from seedlings 28 d after sowing, leaf P6-7 primordia, and flower petals in 10mm buds (left to right). Total RNA (5 μg) from the indicated tissues was hybridized with sly-miR6026 antisense probe. Sly-miR6026 expression was normalized to U6 snRNA and levels are indicated below each panel. (C, D) qRT-PCR analysis of the expression levels of the indicated SlDCL genes in the RNA samples analysed in B: seedlings 28 d after sowing (C), leaf P6-7 primordia (D top), and flower petals in 10mm buds (D bottom). Error bars indicate ±SD of three biological replicates, each measured in triplicate. Single (P ≤ 0.01) and double (P ≤ 0.05) asterisks indicate significant difference as determined by Student’s t-test.

Certain SlDCL2 paralogues are up-regulated upon SlDCL1 silencing. Sequence alignment between SlDCL2 genes (A) predicted to serve as sly-miR6026 targets. Identical nucleotides in all or at least three sequences are shaded in black and grey, respectively. Watson–Crick pairing with sly-miR6026 is shown below. Mismatched nucleotides are in lower case. (B) RNA gel-blot analysis of sly-miR6026 in the indicated genotypes from seedlings 28 d after sowing, leaf P6-7 primordia, and flower petals in 10mm buds (left to right). Total RNA (5 μg) from the indicated tissues was hybridized with sly-miR6026 antisense probe. Sly-miR6026 expression was normalized to U6 snRNA and levels are indicated below each panel. (C, D) qRT-PCR analysis of the expression levels of the indicated SlDCL genes in the RNA samples analysed in B: seedlings 28 d after sowing (C), leaf P6-7 primordia (D top), and flower petals in 10mm buds (D bottom). Error bars indicate ±SD of three biological replicates, each measured in triplicate. Single (P ≤ 0.01) and double (P ≤ 0.05) asterisks indicate significant difference as determined by Student’s t-test.

Depletion of SlDCL1 from developing leaf primordium inhibits blade expansion

Constitutive SlDCL1 silencing induced seedling lethality before lateral organs could develop (Fig. 2). However, tissue-specific driver lines allowed investigation of the requirement of SlDCL1 of leaf and flower development. In tomato, the Filamentous Flower (FIL) promoter drives strong expression throughout young leaf primordia soon after they initiate from the shoot apical meristem (SAM), but not while they are in the SAM (Lifschitz ; Shani ). Thus, leaf-specific SlDCL1 silencing was induced by crossing the OP:SlDCL1IR responder line with the FIL:LhG4 driver line. As expected, germination of FIL>>SlDCL1IR progeny seedlings was normal (Supplementary Fig. S3 available at JXB online). In addition, relatively subtle phenotypes were observed in the first two leaves. These leaves contained one instead of two pairs of primary leaflets, which were smaller than controls, and had a morphologically distinct terminal leaflet blade (Fig. 6A). More severe phenotypes were observed in later formed leaves. Compared with FIL:LhG4 control leaves, these leaves were much smaller, and had wavy rachises that supported almost bladeless primary and terminal leaflets (Fig. 6A). As the plants matured, their cotyledons became abnormally elongated. In addition, precocious outgrowth of cotyledonary as well as juvenile axillary meristems was observed, suggesting loss of apical dominance in these plants (Supplementary Fig. S3 available at JXB online). The bladeless FIL>>SlDCL1IR leaf phenotype was reminiscent of the later formed wiry leaves of TAS3 pathway mutants that overaccumulate Auxin Response Factor 3 (SlARF3) and SlARF4, due to reduced levels of ta-siARF (Yifhar ). Reduced tomato leaf lamina outgrowth has also been associated with ectopic accumulation of miR160-resistant SlARF10 (Hendelman ). Molecular analysis of young leaf primordia confirmed the silencing of SlDCL1 (Fig. 6B) and, accordingly, revealed reduced accumulation of sly-miR160a and sly-miR390, which is required for ta-siARF biogenesis (Fig. 6C) (Yifhar ). Nevertheless, significant up-regulation of SlARF3, SlARF4, and SlARF10 was not detected in these primordia, most probably due to insufficient down-regulation of sly-miR390 and sly-miR160a, respectively (Fig. 6D).
Fig. 6.

Characterization of SlDCL1-depleted leaves. (A) Comparison of whole M82 tomato plants 42 d after sowing and representative leaves (from left to right) between control (FIL:LhG4) and FIL>>SlDCL1IR. Scale bar=5cm. (B) qRT-PCR analysis of SlDCL1 transcript levels in FIL:LhG4 and FIL>>SlDCL1IR P5 leaf primordia. (C) RNA gel-blot analysis of miRNAs in the RNA samples analysed in B. Total RNA (2 μg) was hybridized with the indicated miRNA antisense probe. Expression levels were determined relative to the control after normalization to U6 and are indicated below each panel. (D) qRT-PCR analysis of miRNA target transcripts in the RNA samples analysed in B. The corresponding miRNA is shown below each target mRNA. (B, D) CAC expression values were used for normalization. Error bars indicate ±SD of three biological replicates, each measured in triplicate. Asterisks indicate significant difference as determined by Student’s t-test (P ≤ 0.01).

Characterization of SlDCL1-depleted leaves. (A) Comparison of whole M82 tomato plants 42 d after sowing and representative leaves (from left to right) between control (FIL:LhG4) and FIL>>SlDCL1IR. Scale bar=5cm. (B) qRT-PCR analysis of SlDCL1 transcript levels in FIL:LhG4 and FIL>>SlDCL1IR P5 leaf primordia. (C) RNA gel-blot analysis of miRNAs in the RNA samples analysed in B. Total RNA (2 μg) was hybridized with the indicated miRNA antisense probe. Expression levels were determined relative to the control after normalization to U6 and are indicated below each panel. (D) qRT-PCR analysis of miRNA target transcripts in the RNA samples analysed in B. The corresponding miRNA is shown below each target mRNA. (B, D) CAC expression values were used for normalization. Error bars indicate ±SD of three biological replicates, each measured in triplicate. Asterisks indicate significant difference as determined by Student’s t-test (P ≤ 0.01).

Partial depletion of SlDCL1 from petals results in lower accumulation of carotenoids

The flower-specific AP1:LhG4 driver line drives expression throughout the young floral primordia and, as the buds mature, its activity is mainly confined to developing sepals and petals. The AP3:LhG4 driver line drives expression throughout the developing petals, in the stamen vasculature, and on the abaxial side of anthers (Hendelman ). Hence, flower-specific SlDCL1 silencing was induced by crossing the OP:SlDCL1IR responder line to these driver lines. Both AP1>>SlDCL1IR and AP3>>SlDCL1IR plants showed a wild-type phenotype during vegetative growth (data not shown). Moreover, young AP1>>SlDCL1IR buds did not show any developmental aberrations despite containing only 40% of the wild-type SlDCL1 levels (Supplementary Fig. S4A available at JXB online). However, most of the buds underwent premature senescence at 4–5mm in size and could not develop into mature flowers. The senescence initiated as yellowing of the receptacle area in one or more buds from the same inflorescence. This yellowing spread downward along the stack to the abscission zone and upward to the sepals, ultimately leading to complete drying of the bud (Fig. 7A). Only ~10% of the buds developed into mature flowers that produced pale petals (Fig. 7B). Interestingly, the AP3>>SlDCL1IR flowers produced similarly pale and slightly smaller petals (Fig. 7B–D). The composition of carotenoids in AP3>>SlDCL1IR petals was analysed to determine whether the pale phenotype is associated with quantitative or qualitative differences. While the carotenoid profile in AP3>>SlDCL1IR petals is relatively similar to that of the control, consisting of mainly neoxanthin and violaxanthin, the total level of carotenoids was reduced >2-fold (Table 1). Additional visual abnormalities were not observed in the AP3>>SLDCL1IR flowers (Fig. 7C). qRT-PCR analysis of SlDCL1 levels in isolated petals, at the start of yellowing, revealed that it accumulated to only 25% of controls, indicating partial silencing of SlDCL1 in the petals (Supplementary Fig. S4B available at JXB online). Accordingly, miRNA levels were down-regulated and corresponding target mRNAs were up-regulated in the silenced petals (Fig. 7E, F).
Fig. 7.

Characterization of SlDCL1-depleted flowers. (A) Phenotype of representative control (AP1:LhG4) and AP1>>SlDCL1IR inflorescences bearing young (top) and mature (bottom) buds. Arrowheads mark the abscission zone. Scale bars=1cm. (B) Representative flowers of the indicated genotypes at anthesis. (C) Representative flowers of the indicated genotypes at different developmental stages: 2 d before anthesis, anthesis, and 1 d post-anthesis (left to right). (D) Quantitation of petals area at anthesis in control and AP3>>SlDCL1IR. Error bars represent ± SD (n=54). (E) RNA gel-blot analysis of miRNAs in petals from 10mm buds of the indicated genotypes. Total RNA (5 μg) was hybridized with the corresponding miRNA antisense probe. Expression levels were determined relative to the control after normalization to U6 and are indicated below each panel. (F) qRT-PCR analysis of miRNA target transcripts in the RNA samples analysed in E. The corresponding miRNA is shown below each target mRNA. CAC expression values were used for normalization. Error bars indicate ±SD of three biological replicates, each measured in triplicate. (D, F) Asterisks indicate significant difference as determined by Student’s t-test (P ≤ 0.01).

Table 1.

Carotenoid composition in control and AP3>>SlDCL1IR petals

AP3:LhG4 a AP3>>SlDCL1lR a
Neoxanthin71.6±2.266.4±4.2
Violaxanthin24.3±1.923.0±2.4
Antheraxanthin 1.2±0.5 1.4±0.4
Lutein 1.8±0.4 5.6±1.9
β-Carotene 1.1±0.4 3.7±0.5
Totalb (μg g fresh weight–1)620.6±112.8246.4±28.8

Numbers correspond to percentage of total carotenoids (n=4).

All isomers.

Carotenoid composition in control and AP3>>SlDCL1IR petals Numbers correspond to percentage of total carotenoids (n=4). All isomers. Characterization of SlDCL1-depleted flowers. (A) Phenotype of representative control (AP1:LhG4) and AP1>>SlDCL1IR inflorescences bearing young (top) and mature (bottom) buds. Arrowheads mark the abscission zone. Scale bars=1cm. (B) Representative flowers of the indicated genotypes at anthesis. (C) Representative flowers of the indicated genotypes at different developmental stages: 2 d before anthesis, anthesis, and 1 d post-anthesis (left to right). (D) Quantitation of petals area at anthesis in control and AP3>>SlDCL1IR. Error bars represent ± SD (n=54). (E) RNA gel-blot analysis of miRNAs in petals from 10mm buds of the indicated genotypes. Total RNA (5 μg) was hybridized with the corresponding miRNA antisense probe. Expression levels were determined relative to the control after normalization to U6 and are indicated below each panel. (F) qRT-PCR analysis of miRNA target transcripts in the RNA samples analysed in E. The corresponding miRNA is shown below each target mRNA. CAC expression values were used for normalization. Error bars indicate ±SD of three biological replicates, each measured in triplicate. (D, F) Asterisks indicate significant difference as determined by Student’s t-test (P ≤ 0.01).

Discussion

As part of the effort to unveil the roles of miRNA regulation in tomato development, transgenic tomato responder lines were previously generated that, by trans-activation, can express the viral silencing suppressors Tomato bushy stunt virus P19 and Beet western yellows virus P0, thereby perturbing the miRNA pathway in the activated plants (Stav ; Hendelman ). However, because P19 binds siRNA duplexes and P0 can lead to the decay of various ARGONAUTES, their transgenic expression may interfere with endogenous siRNA pathways as well (Dunoyer ; Baumberger ). In the current study, the OP:SlDCL1IR tomato responder line was used; this line is a more specific miRNA-inhibiting tool that enables the silencing of SlDCL1, the tomato homologue of DCL1, by trans-activation. DCL1 has been found to be the predominant DCL involved in the biogenesis of canonical miRNAs, with no other DCL acting as its surrogate (Gasciolli ). Accordingly, trans-silencing of SlDCL1 to 5% of its normal levels was associated with diminished miRNA levels, demonstrating that in tomato, like in Arabidopsis and rice, DCL1 is central for miRNA production. The involvement of DCL1 in the biogenesis of certain siRNAs renders the criterion of DCL1 dependence for accumulation insufficient to warrant annotation of a small RNA as an miRNA (Meyers ). ShortStack is a recently published stand-alone application that can predict and annotate plant miRNAs based on small RNA sequencing data (Axtell, 2013). By combining ShortStack predictions and the SlDCL1 dependence criterion, 33 new SlDCL1-dependent miRNAs were confidently discovered, 17 of which represent novel plant miRNAs. This method is suggested for reliable annotation of canonical miRNA in tomato. A total of 47 miRNAs that depend on SlDCL1 for their biogenesis were identified in this study. These miRNAs were shown to be differentially reduced by SlDCL1 silencing. This differential response ranged from a 2-fold to a 64-fold decrease and might indicate the in vivo cleavage efficiency and specificity of SlDCL1 for various miRNA precursors. Interestingly, sly-miR159a, which is encoded by a single precursor (SL2.40ch03:61786005–61786301), was reduced by only 2.4-fold in 35S>>SlDCL1IR plants, indicating relatively efficient processing and low sensitivity to SlDCL1 silencing. Indeed, the sly-miR159a precursor has been successfully used as a backbone for the expression of an artificial miRNA (amiR) precursor in transgenic tomato and it was more efficiently processed than sly-miR168a-based amiR (reduced by 2.7-fold in 35S>>SlDCL1IR) (Vu ). The present data revealed that SlDCL1 silencing causes two significant but contrasting changes in the small RNA population of tomato seedlings. The 35S>>SlDCL1IR seedlings exhibited a lower proportion of 21-nt small RNAs and a higher proportion of 22-nt small RNAs. The former was also observed in other dcl1 mutants and can be attributed to a substantial reduction in 21-nt miRNAs which depend on DCL1 for their biogenesis, and phased siRNAs, which depend on initial miRNA cleavage for their production (Kasschau ; Shivaprasad ). Nevertheless, the increase in 22-nt small RNAs has not been observed in other dcl1 mutants (Kasschau ; Wu ). In Arabidopsis, DCL2 has been shown to be required for the formation of 22-nt long siRNAs (Xie ; Gasciolli ; Deleris ). The tomato genome encodes four DCL2 paralogues, three of which (SlDCL2a, b, and d) are clustered on chromosome 11 (Bai ). The results of the present study indicate that SlDCl2b and SlDCl2d are up-regulated upon SlDCL1 silencing, suggesting that these paralogues are responsible for the observed increase in 22-nt small RNAs. Sly-miR6026, which is predicted to target SlDCL2a, b, and d, was not significantly down-regulated upon SlDCL1 silencing. Consistent with this, SlDCL2b- and SlDCL2d-derived siRNAs increased rather than decreased and SlDCl2a was not up-regulated in 35S>>SlDCL1IR seedlings. Therefore, the up-regulation of SlDCl2b and SlDCl2d is probably due to an increase in transcription rather than reduced targeting by sly-miR6026. One appealing explanation for this is the existence of a specific SlDCl2b and SlDCl2d miRNA-regulated transcriptional activator that is up-regulated upon SlDCL1 silencing. Consistent with the severe developmental phenotypes of known dcl1 mutants (Schauer ; Liu ; Khraiwesh ), the 35S>>SlDCL1IR seedlings were growth arrested at the first to third leaf stage, emphasizing the importance of miRNAs for tomato’s post-germination development. Nevertheless, the trans-activated RNAi strategy enabled, for the first time, SlDCL1 silencing in a specific organ, without disturbing prior development. This enabled a direct unbiased assessment of SlDCL1 functions in the silenced tissue. In addition, activation of the OP:SlDCL1IR construct by different promoters generated variable silencing strengths that were manifested by hypomorphic phenotypes. Reducing SlDCL1 levels by 85% in the leaf primordia led to strong inhibition of blade outgrowth, but did not modify its abaxial–adaxial polarity, regulated in part by miR166 and miR390 (Chitwood ). Similarly, the hypomorphic Arabidopsis mutant dcl1-9 (caf) produced polar leaves that were thinner than the wild type and ~10% of them did not develop any blade (Jacobsen ), together indicating that blade outgrowth is dependent on DCL1-mediated silencing in simple as in compound leaf species. Indeed, perturbation of the post-transcriptional regulation of SlARF10, and SlARF3 and SlARF4, which are normally cleaved by sly-miR160a and tasiARF, respectively, has been shown to reduce blade outgrowth dramatically in tomato leaves (Hendelman ; Yifhar ). Surprisingly, none of these target genes was significantly up-regulated in FIL>>SlDCL1IR leaf primordia, suggesting that they are not the main cause for the bladeless phenotype. In addition, FIL>>SlDCL1IR plants also demonstrated loss of apical dominance. Since both blade outgrowth and apical dominance are regulated by auxin (Cline, 1997; Koenig ), disruption of its signalling pathway by SlDCL1 silencing is likely to be a major cause for the observed FIL>>SlDCL1IR phenotypes. The distinct yellow colour of tomato flowers is a result of accumulation of carotenoids, mainly the xanthophylls neoxanthin and violaxanthin (Hirschberg, 2001). A novel pale phenotype was observed in AP1>>SlDCL1IR and AP3>>SlDCL1IR petals with partially silenced SlDCL1. This phenotype was associated with a reduction of >2-fold in the total rather than an alteration in the ratio between the individual carotenoids. The exact reason for this is currently unknown. Nevertheless, by profiling Arabidopsis dcl1 mutant embryos, it was shown that the two most up-regulated miRNA targets are responsible for a large part of the mutant embryo phenotype, thus proving the usefulness of dcl1 mutants for revealing specific miRNA regulatory modules involved in development (Nodine and Bartel, 2010; Willmann ). The availability of a tomato dcl1 mutant, as presented in the current study, now enables the use of a similar approach to elucidate the molecular bases of the observed phenotypes.

Supplementary data

Supplementary data are available at JXB online. Figure S1. Sequence analysis of the tomato DCL1 homologue. Figure S2. Effect of SlDCL1 silencing on SlDCL2-derived siRNAs accumulation. Figure S3. Additional phenotypes of FIL>>SlDCL1IR plants. Figure S4. Quantitative analysis of SlDCL1 levels in trans-activated flowers. Table S1. List of primers and probes used in this study. Table S2. Summary of small RNA profiling. Table S3. Summary of small RNA annotations. Table S4. Summary of ShortStack-predicted miRNAs. Table S5. List of ShortStack small RNA clusters. Table S6. EdgeR results and differentially expressed miRNAs.
  65 in total

1.  22-Nucleotide RNAs trigger secondary siRNA biogenesis in plants.

Authors:  Ho-Ming Chen; Li-Teh Chen; Kanu Patel; Yi-Hang Li; David C Baulcombe; Shu-Hsing Wu
Journal:  Proc Natl Acad Sci U S A       Date:  2010-07-19       Impact factor: 11.205

2.  Inhibition of lamina outgrowth following Solanum lycopersicum AUXIN RESPONSE FACTOR 10 (SlARF10) derepression.

Authors:  A Hendelman; K Buxdorf; R Stav; M Kravchik; T Arazi
Journal:  Plant Mol Biol       Date:  2012-04       Impact factor: 4.076

3.  Global effects of the small RNA biogenesis machinery on the Arabidopsis thaliana transcriptome.

Authors:  Sascha Laubinger; Georg Zeller; Stefan R Henz; Sabine Buechel; Timo Sachsenberg; Jia-Wei Wang; Gunnar Rätsch; Detlef Weigel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-09-24       Impact factor: 11.205

4.  Computational and analytical framework for small RNA profiling by high-throughput sequencing.

Authors:  Noah Fahlgren; Christopher M Sullivan; Kristin D Kasschau; Elisabeth J Chapman; Jason S Cumbie; Taiowa A Montgomery; Sunny D Gilbert; Mark Dasenko; Tyler W H Backman; Scott A Givan; James C Carrington
Journal:  RNA       Date:  2009-03-23       Impact factor: 4.942

Review 5.  Carotenoid biosynthesis in flowering plants.

Authors:  J Hirschberg
Journal:  Curr Opin Plant Biol       Date:  2001-06       Impact factor: 7.834

6.  Insertional mutagenesis of genes required for seed development in Arabidopsis thaliana.

Authors:  J McElver; I Tzafrir; G Aux; R Rogers; C Ashby; K Smith; C Thomas; A Schetter; Q Zhou; M A Cushman; J Tossberg; T Nickle; J Z Levin; M Law; D Meinke; D Patton
Journal:  Genetics       Date:  2001-12       Impact factor: 4.562

7.  The Polerovirus silencing suppressor P0 targets ARGONAUTE proteins for degradation.

Authors:  Nicolas Baumberger; Ching-Hsui Tsai; Miranda Lie; Ericka Havecker; David C Baulcombe
Journal:  Curr Biol       Date:  2007-09-18       Impact factor: 10.834

8.  MicroRNAs play critical roles during plant development and in response to abiotic stresses.

Authors:  Júlio César de Lima; Guilherme Loss-Morais; Rogerio Margis
Journal:  Genet Mol Biol       Date:  2012-12-18       Impact factor: 1.771

9.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

10.  The tomato NAC transcription factor SlNAM2 is involved in flower-boundary morphogenesis.

Authors:  Anat Hendelman; Ran Stav; Hanita Zemach; Tzahi Arazi
Journal:  J Exp Bot       Date:  2013-10-01       Impact factor: 6.992

View more
  14 in total

1.  Small RNA and degradome sequencing reveals microRNAs and their targets involved in tomato pedicel abscission.

Authors:  Tao Xu; Yanling Wang; Xin Liu; Shuangshuang Lv; Chaoyang Feng; Mingfang Qi; Tianlai Li
Journal:  Planta       Date:  2015-05-29       Impact factor: 4.116

2.  Redistribution of CHH Methylation and Small Interfering RNAs across the Genome of Tomato ddm1 Mutants.

Authors:  Shira Corem; Adi Doron-Faigenboim; Ophélie Jouffroy; Florian Maumus; Tzahi Arazi; Nicolas Bouché
Journal:  Plant Cell       Date:  2018-06-06       Impact factor: 11.277

3.  Sp-miR396a-5p acts as a stress-responsive genes regulator by conferring tolerance to abiotic stresses and susceptibility to Phytophthora nicotianae infection in transgenic tobacco.

Authors:  Lei Chen; Yushi Luan; Junmiao Zhai
Journal:  Plant Cell Rep       Date:  2015-08-05       Impact factor: 4.570

4.  RNA sequencing and functional analysis implicate the regulatory role of long non-coding RNAs in tomato fruit ripening.

Authors:  Benzhong Zhu; Yongfang Yang; Ran Li; Daqi Fu; Liwei Wen; Yunbo Luo; Hongliang Zhu
Journal:  J Exp Bot       Date:  2015-05-06       Impact factor: 6.992

5.  miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets.

Authors:  Claudia Paicu; Irina Mohorianu; Matthew Stocks; Ping Xu; Aurore Coince; Martina Billmeier; Tamas Dalmay; Vincent Moulton; Simon Moxon
Journal:  Bioinformatics       Date:  2017-08-15       Impact factor: 6.937

6.  A novel DCL2-dependent miRNA pathway in tomato affects susceptibility to RNA viruses.

Authors:  Zhengming Wang; Thomas J Hardcastle; Alex Canto Pastor; Wing Hin Yip; Shuoya Tang; David C Baulcombe
Journal:  Genes Dev       Date:  2018-08-27       Impact factor: 11.361

7.  Tomato DCL2b is required for the biosynthesis of 22-nt small RNAs, the resulting secondary siRNAs, and the host defense against ToMV.

Authors:  Tian Wang; Zhiqi Deng; Xi Zhang; Hongzheng Wang; Yu Wang; Xiuying Liu; Songyu Liu; Feng Xu; Tao Li; Daqi Fu; Benzhong Zhu; Yunbo Luo; Hongliang Zhu
Journal:  Hortic Res       Date:  2018-09-01       Impact factor: 6.793

8.  Overexpression of MiR482c in Tomato Induces Enhanced Susceptibility to Late Blight.

Authors:  Yu-Hui Hong; Jun Meng; Xiao-Li He; Yuan-Yuan Zhang; Yu-Shi Luan
Journal:  Cells       Date:  2019-08-03       Impact factor: 6.600

9.  DCL-suppressed Nicotiana benthamiana plants: valuable tools in research and biotechnology.

Authors:  Konstantina Katsarou; Eleni Mitta; Eirini Bardani; Anastasis Oulas; Elena Dadami; Kriton Kalantidis
Journal:  Mol Plant Pathol       Date:  2018-12-19       Impact factor: 5.663

10.  Signatures of selection and host-adapted gene expression of the Phytophthora infestans RNA silencing suppressor PSR2.

Authors:  Sophie de Vries; Janina K von Dahlen; Constanze Uhlmann; Anika Schnake; Thorsten Kloesges; Laura E Rose
Journal:  Mol Plant Pathol       Date:  2016-10-02       Impact factor: 5.663

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.