Open Access

Identification of Nicotiana benthamiana microRNAs and their targets using high throughput sequencing and degradome analysis

  • Ivett Baksa1,
  • Tibor Nagy1,
  • Endre Barta1,
  • Zoltán Havelda1,
  • Éva Várallyay1,
  • Dániel Silhavy1,
  • József Burgyán1 and
  • György Szittya1Email author
BMC Genomics201516:1025

https://doi.org/10.1186/s12864-015-2209-6

Received: 23 July 2015

Accepted: 12 November 2015

Published: 1 December 2015

Abstract

Background

Nicotiana benthamiana is a widely used model plant species for research on plant-pathogen interactions as well as other areas of plant science. It can be easily transformed or agroinfiltrated, therefore it is commonly used in studies requiring protein localization, interaction, or plant-based systems for protein expression and purification. To discover and characterize the miRNAs and their cleaved target mRNAs in N. benthamiana, we sequenced small RNA transcriptomes and degradomes of two N. benthamiana accessions and validated them by Northern blots.

Results

We used a comprehensive molecular approach to detect and to experimentally validate N. benthamiana miRNAs and their target mRNAs from various tissues. We identified 40 conserved miRNA families and 18 novel microRNA candidates and validated their target mRNAs with a genomic scale approach. The accumulation of thirteen novel miRNAs was confirmed by Northern blot analysis. The conserved and novel miRNA targets were found to be involved in various biological processes including transcription, RNA binding, DNA modification, signal transduction, stress response and metabolic process. Among the novel miRNA targets we found the mRNA of REPRESSOR OF SILENCING (ROS1). Regulation of ROS1 by a miRNA provides a new regulatory layer to reinforce transcriptional gene silencing by a post-transcriptional repression of ROS1 activity.

Conclusions

The identified conserved and novel miRNAs along with their target mRNAs also provides a tissue specific atlas of known and new miRNA expression and their cleaved target mRNAs of N. benthamiana. Thus this study will serve as a valuable resource to the plant research community that will be beneficial well into the future.

Keywords

Nicotiana benthamiana microRNA Non-coding RNAs Small RNA Degradome High throughput sequencing

Background

Nicotiana benthamiana is a widely used model plant species for research on plant-pathogen interactions as well as other areas of plant science. It is particularly popular among plant virologist as it is susceptible to a large number of different plant viruses. It is also widely used in studies requiring protein localization, interaction, or plant-based systems for protein expression and purification. In addition, its susceptibility to pathogens has been used to transiently express proteins, using either engineered viruses or syringe-infiltration of Agrobacterium tumefaciens [1, 2]. The syringe-infiltration method proved to be extremely powerful tool to identify and characterize many viral silencing suppressor proteins [3], pathogens effector proteins [4] and also components of the plant nonsense-mediated mRNA decay system [5].

N. benthamiana is an herbaceous plant endemic to Australia [2], belonging to the Suaveolentes section of the Nicotiana genus of Solanaceae family. N. benthamiana is an allotetraploid species with 19 chromosome pairs, resulting from the hybridization of two unknown progenitors. The estimated genome size of N. benthamiana is 3 GB [2]. The draft genome sequence of the N. benthamiana Nb-1 accession has been published recently [1]. The origins of the N. benthamiana accessions used for research are generally not known. However it has been suggested that only a single accession of N. benthamiana, or a collection of closely related accessions, are being used by the plant research community today, since they are very similar in both susceptibility to pathogens and also in phenotype [2]. The genomes of economically important close relatives of N. benthamiana, such as potato (Solanum tuberosum), tomato (Solanum lycopersicum) and pepper (Capsicum annuum), genomes have been also sequenced recently [69]. These species has either smaller or very similar genome size to N. benthamiana. The Potato (Solanum tuberosum) genome size is 844 Mb [6], the tomato (Solanum lycopersicum) genome size is approximately 900 Mb [8] and both species has twelve chromosomes. Other economically important members of the Solanaceae family is the pepper and the eggplant. The widely cultivated C. annuum accession Zunla-1 genome size is estimated to be 3.26 Gb [9], while the genome size of the eggplant is approximately 833.1 Mb [10].

Gene expression is regulated at several layers to ensure optimal spatial and temporal accumulation of proteins. RNA silencing is an evolutionarily conserved, important gene expression regulator of various cellular processes in eukaryotes, whereby 21-24 nt small RNAs (sRNAs) direct silencing of endogenous genes or pathogens. Plant sRNAs have two major categories based on their biogenesis: small interfering RNA (siRNA) processed from perfectly double stranded RNA; and microRNA (miRNA) derived from single stranded RNA transcripts that form imperfectly double-stranded stem loop precursor structures [11]. MIR genes encode the precursor transcripts which are cleaved into miRNAs by Dicer-like 1 (DCL-1), and subsequently loaded into an RNA Induced Silencing Complex (RISC), containing an ARGONAUTE (AGO) protein. miRNA guided RISCs are able to inhibit expression of genes with at least partial homology to the miRNA by either transcript cleavage or translational arrest [12]. miRNAs have important roles in different cellular processes including developmental/ physiological processes and abiotic/biotic stress [13, 14]. miRNAs are classified into families, whereby miRNAs with the same or very similar sequences are grouped into the same family. It has been shown that only a small number of miRNA families are present across phylogenetically distant species [1517]. The majority of plant miRNAs are evolutionarily young and are only present in one to few species and it is likely that MIR loci in plant genomes are in a constant dynamic evolutionary state [15, 16].

Although the draft genome of N. benthamiana is available and transcriptome-wide expression studies have been reported [1, 1820], the miRNA profile of N. benthamiana has not been analysed. In this study, we used a comprehensive molecular and bioinformatic approach to detect and experimentally validate miRNAs and their target mRNAs from five different tissues of two N. benthamiana lines (the N. benthamiana plant, which is used in our laboratory and the sequenced Nb-1 accession). In our study, we used Illumina sequencing to identify small RNAs, their cleaved target mRNAs followed by Northern blot validation of the miRNAs. Furthermore, we examined cleaved miRNA targets from five different tissues of two aforementioned N. benthamiana accessions. We identified 40 conserved and 18 novel microRNAs and validated their target mRNAs in N. benthamiana with a genomic scale method. The targets were found to be involved in various biological processes including transcription, RNA binding, DNA modification, signal transduction, stress response and metabolic processes. We anticipate that this study will serve as a valuable resource of N. benthamiana miRNAs and their validated target mRNAs to the whole plant research community.

Results and discussion

High-throughput sequencing of N. benthamiana small RNAs

To identify and comprehensively describe the expression of endogenous sRNAs in N. benthamiana, sRNAs containing 5′-phosphate and 3′-OH (likely to be a products of Dicer-like proteins) were cloned from roots, stems, leaves, flowers and small seedlings (containing both root tissue and aerial parts) of N. benthamiana plants. The libraries were then sequenced by high-throughput Illumina sequencing. By using biological replicates of five tissues, ten cDNA libraries were made from the N. benthamiana line that is used in our laboratory. To compare the sRNA profile of our N. benthamiana line and the line, which has been sequenced (Nb-1 accession), two additional sRNA libraries were prepared and sequenced from the leaves and small seedlings of Nb-1 accession. These twelve cDNA libraries yielded approximately 90 million reads. Sequences flanked by the 5′ and 3′ Solexa adaptors, with a minimum and maximum length of 16 and 28 nt, respectively, were compared with the draft N. benthamiana genome sequences. More than 15 million non-redundant reads were perfectly matched to at least one locus, and were analysed further (Table 1). The size distribution of sequence reads showed that the majority of sRNAs in our libraries belonged to the 24 nt size class and it was followed by the 21–22 nt size classes (Fig. 1). Our sequence data are in agreement with previous observations which show that in plants, this 24 nt size class is the overall most abundant class of sRNAs [15].
Table 1

High-throughput sequencing statistics of N. benthamiana sRNAs

  

Redundant

Non-redundant

  

Redundant

Non-redundant

  

Reads

Matching N. benthamiana genome

Reads

Matching N. benthamiana genome

  

Reads

Matching N. benthamiana genome

Reads

Matching N. benthamiana genome

Seedling 1

Raw reads

4 353 615

   

Stem 1

Raw reads

2 673 839

   
 

Adaptor removed

3 192 563

 

1 106 502

  

Adaptor removed

2 468 386

 

858 314

 
 

Filter by sequence properties

3 187 558

 

1 102 305

  

Filter by sequence properties

2 464 474

 

854 744

 
 

t/rRNA removed

3 034 009

2 791 655

1 085 271

942 175

 

t/rRNA removed

2 404 489

2 205 954

846 701

746 712

 

Match known miRNAs

262 998

259 394

1 531

792

 

Match known miRNAs

121 361

119 819

1 376

860

Seedling 2

Raw reads

13 565 620

   

Stem 2

Raw reads

13 390 095

   
 

Adaptor removed

9 931 841

 

1 048 202

  

Adaptor removed

12 682 160

 

3 280 430

 
 

Filter by sequence properties

9 916 497

 

1 036 381

  

Filter by sequence properties

12 662 117

 

3 263 087

 
 

t/rRNA removed

9 461 135

8 656 790

1 016 371

841 123

 

t/rRNA removed

12 195 396

11 213 510

3 246 517

2 773 011

 

Match known miRNAs

1 132 848

1 117 758

2 423

1 030

 

Match known miRNAs

664 082

654 984

3 455

1 969

Root 1

Raw reads

4 416 396

   

Flower 1

Raw reads

17 715 434

   
 

Adaptor removed

3 567 326

 

673 485

  

Adaptor removed

15 107 462

 

4 920 011

 
 

Filter by sequence properties

3 561 838

 

669 035

  

Filter by sequence properties

15 084 084

 

4 899 263

 
 

t/rRNA removed

3 250 883

2 926 826

652 495

553 372

 

t/rRNA removed

14 374 989

13 270 386

4 872 774

4 186 250

 

Match known miRNAs

368 908

363 793

1557

827

 

Match known miRNAs

517 965

510 930

3 461

2 128

Root 2

Raw reads

6 227 488

   

Flower 2

Raw reads

8 784 135

   
 

Adaptor removed

5 472 237

 

2 020 365

  

Adaptor removed

8 156 033

 

2 71814

 
 

Filter by sequence properties

5 463 791

 

2 013 081

  

Filter by sequence properties

8 143 554

 

262 570

 
 

t/rRNA removed

5 041 719

4 673 608

1 992 006

1 746 022

 

t/rRNA removed

7 295 596

6 508 891

253 399

185 299

 

Match known miRNAs

308 179

304 276

2 402

1 474

 

Match known miRNAs

817 620

807 317

1 526

547

Leaf 1

Raw reads

4 481 051

   

Leaf BTI

Raw reads

2 646 118

   
 

Adaptor removed

3 752 733

 

1 675 147

  

Adaptor removed

2 373 816

 

445 460

 
 

Filter by sequence properties

3 746 943

 

1 670 236

  

Filter by sequence properties

2 370 062

 

442 372

 
 

t/rRNA removed

3 567 987

3 252 343

1 644 909

1 440 195

 

t/rRNA removed

2 277 189

2 092 901

433 297

375 749

 

Match known miRNAs

258 610

255 179

2 368

1 502

 

Match known miRNAs

234 022

231 082

1 025

489

Leaf 2

Raw reads

3 801 050

   

Seedling BTI

Raw reads

7 874 296

   
 

Adaptor removed

2 925 945

 

1 149 340

  

Adaptor removed

7 174 326

 

2 105 046

 
 

Filter by sequence properties

2 921 408

 

1 145 456

  

Filter by sequence properties

7 163 048

 

2 095 876

 
 

t/rRNA removed

2 834 354

2 596 026

1 131 710

982 432

 

t/rRNA removed

6 906 776

6 088 762

2 070 845

287 724

 

Match known miRNAs

274 028

270 476

1 434

737

 

Match known miRNAs

786 266

423 581

2205

113

Fig. 1

The size distribution of sequenced small RNA reads. The size class distribution of redundant and non redundant small RNA sequences in the twelve tissue samples. The percentage of the different size classes (y-axis) and the different tissues, which includes seedling, root, leaf, stem and flower with biological replicates and BTI seedling and leaf cDNA libraries (x-axis) represented in N. benthamiana

Identification of known and conserved miRNAs in N. benthaniana

miRNAs are a well-studied class of regulatory sRNAs. They are present in all plant species studied so far and have important functions in plant development and stress responses. Conserved families of miRNAs were found in many plant species and analysis of data from high-throughput sequencing approaches identified eight deeply conserved miRNA families that are present in all embryophytes [16]. First we looked for known miRNAs by comparing our libraries to known miRNAs from other plant species and we identified 40 known or conserved miRNA families in the twelve sRNA libraries generated (Fig. 2, Additional file 1: Table S1). As expected, all of the deeply conserved miRNA families (miR156/157, miR159/319, miR160, miR165/166, miR171, miR408, miR390/391 and miR395) were present in our data sets (Fig. 2). We analysed the number of reads for conserved miRNAs and miR156, 159, 166, 168, 319, 396 and 403 were represented most frequently in the libraries (Fig. 2). As expected miRNA families expressed at very different levels and some miRNA families showed clear tissue-specific expression changes (Fig. 2). For example, the expression level of miR159 and miR166 families were high, while the expression of miR395 and miR399 families were similarly low in all tissues (Fig. 2). However, for miR395 and miR399 low expression is not surprising because their expression level is generally low under normal growth conditions as they are induced by sulphur or phosphate deficiency respectively [21, 22]. A recent comprehensive atlas of miRNAs from 31 representative species across vascular plants identified 82 known miRNA families that were present across several terrestrial plants. These families formed eight groups depending on their distribution across lineages and species. miRNAs belonging to group 1 were ubiquitous and generally highly expressed across all terrestrial species (miR156, miR166, miR167, miR168 and miR172) while group 2 miRNA families were represented in all taxonomic lineages but could be absent or present at very low abundance levels in some species (miR158, miR159, miR160, miR162, miR164, miR169, miR171, miR319, miR390, miR393, miR394, miR396, miR397, miR529, miR535 and miR4414) [15]. Most of the group 1 and group 2 miRNA families were present in our data sets except the miR529, miR535 and miR4414 families (Fig. 2). Similar to our result, these three miRNA families were absent or their abundance was very low (1–10 reads per million (RPM) or in some cases 11–100 RPM) in sRNA libraries prepared from different Solanaceae species such as petunia, pepper, potato, tomato and tobacco [15]. Furthermore, the remaining six miRNA groups were distributed across species with diverse lineage enrichment and one of them (group 8, containing miR1919, miR4376, miR5300, miR53001, miR6022, miR6023, miR6024, miR6025, miR6026, miR6027 and miR6149) was shown to be predominant in Solanaceae species [15]. As expected, in our libraries we identified several miRNA families that belong to group 8 such as miR1919, miR4376, miR6025 and miR6149. Among the group 8 miRNA families the miR6149 abundance level was the highest in our libraries similar to the tobacco libraries reported by Chavez Montes et al. [15]. Some of the group 8 miRNA families were missing from our libraries (miR5300, miR5301, miR6022, miR6023, miR6024, miR6026 and miR6027), however those miRNA families also showed low abundance (0–100 RPM) in the reported tobacco libraries (such as miR5300, miR5301, miR6023 and miR6027) [15].
Fig. 2

Conserved and other known miRNAs in N. benthamiana. Normalized read numbers of conserved and other known miRNAs across the tissues included in this study. Expression profiles are expressed in reads per million (RPM) genome matching reads. Heat map colours represents absolute normalized levels of miRNA expression ranging from less than 1 RPM (white) to more than 1000 RPM (red) as indicated in the colour key. We have identified 40 known or conserved miRNA families in the twelve sRNA libraries generated. All of the deeply conserved miRNA families (miR156/157, miR159/319, miR160, miR165/166, miR171, miR408, miR390/391 and miR395) were present in our data sets. The expression levels of different miRNA families were different and we also observed clear tissue-specific expressional changes within some miRNA families as it was expected

We also identified several miRNA families which were identified previously as tobacco (N. tabacum) specific miRNAs such as miR6019, miR6020, miR6147, miR6151, miR6153, miR6155, miR6157 and miR6161 [23, 24]. These miRNA families generally showed low abundance across all tissues in our libraries with the exception of miR6153, which was expressed at medium levels in all samples (160–450 RPM across all tissue) and miR6155, which was relatively abundant in leaf and seedling samples (175–525 RPM) (Fig. 2).

We checked the size distribution and starting nucleotide of the conserved and known miRNA families in our libraries. In 30 miRNA families, 21 nt long miRNAs were the most significant size class (Fig. 3a). In several cases they were accompanied by additional size classes, mostly 20 nucleotide long sequences or in some cases 22 nucleotide sequences were present in significant proportions (miR4376, miR393, miR167 and miR6157). Three miRNA families exhibited a strong preference for 20 nucleotide sequences and in seven miRNA families the 22 nucleotide long sequences were the most abundant size class (Fig. 3a). Our observation that the miR394 has a predominant 20 nucleotide size in our libraries is consistent with previous result and it might suggest a functional consequence since its size and sequence is conserved in terrestrial plant species [15]. It was shown in several cases that size specificity has a functional consequence, like the 22 nucleotide preference of phase initiating miRNAs associated with the generation of tasiRNAs [25, 26]. We found seven miRNA families with the 22 nucleotide sequence dominance and two of them (miR6019 and miR482) belongs to the described phase initiating miRNAs [23, 27, 28]. It is likely they are also involved in tasiRNA generation in N. benthamiana.
Fig. 3

Size distribution and starting nucleotide of the conserved and other known miRNAs. The relative abundance of different size categories (a), from 20 to 24 nucleotides is shown for the conserved and other known miRNAs presented in Fig. 2. The relative abundance of the 5′-nucleotide (b) is shown for the conserved and other known miRNAs presented in Fig. 2. In 31 miRNA families, 21 nt long miRNAs were the most significant size class. In 32 of the 40 conserved miRNA families, the majority of sequences started with uracyl at their 5′-end, although a portion of these have a different nucleotide composition at position 1 to a variable degree. Three miRNA families exhibited a preference for an adenine at position 1

Sorting of sRNAs into AGO complexes is influenced by their 5′ terminal nucleotide. Hence, we checked the 5′-nucleotide distribution of the conserved and known miRNA families in our libraries, since it is an important feature that is correlating to their biogenesis and function [29]. In 34 of the 40 conserved miRNA families, the majority of sequences started with uracyl at their 5′-end, although a portion of these have a different nucleotide composition at position 1 to a variable degree (Fig. 3b). Three miRNA families exhibited a preference for an adenine at position 1, although one of them has a different nucleotide composition at position 1 to a variable degree (miR172). In three miRNA families the most frequently found first nucleotide at their 5′-end was cytosine (miR395, miR479, miR477). miRNAs mostly are incorporated into the AGO1 effector complex to give sequence specificity to either slice or translationally repress their target mRNAs [12]. AGO1 harbours miRNAs that favour a 5′ terminal uridine [30]. In line with this observation, most of the conserved and known miRNA families in our libraries started with uracyl at their 5′-end. We also found several miRNAs that start with either adenine or cytosine (miR172, miR390 and miR395). It was reported in many different plant species that miRNAs belonging to these miRNA families are starting with the same nucleotide at the 5′-position [15].

Many plant miRNAs show tissue-specific and developmental-stage-specific expression patterns and they have important roles during development and stress adaptation [13]. To validate the tissue-specific expression patterns of selected conserved and known miRNAs we carried out Northern blot analysis using seedling (Se), root (R), leaf (L), stem (St) and flower (F) samples isolated from our N. benthamiana line; and leaf (LBTI) and seedling (SeBTI) samples from N. benthamiana Nb-1 accession that were obtained from the Boyce Thompson Institute for Plant Research. Northern analysis usually was in broad agreement with the sequencing data as in the cases of miR156, miR159, miR162, miR164, miR165, miR168, miR390 and miR393 (Fig. 4). In certain cases we observed a discrepancy between the Northern blot and sequencing data, as in the cases of miR167, miR171, miR482, miR6025 and miR6149 (Fig. 4; Fig. 2). However, these differences are not unexpected as it has been reported that Northern analysis are not always in full agreement with the sequencing data, presumably due to the inherent biases in next-generation sequencing technologies [3136]. Theoretically, the oligoprobes used for Northern analysis might have detected heterogeneous miRNAs. However, we expect that Northern analysis should reveal more accurate in vivo expression patterns. We also performed RT-qPCR analysis to validate our Northern results by checking the expression pattern of miR167 and miR482 in N. benthamiana tissues. We found that the results of Northern analysis and RT-qPCR were identical (Additional file 2 Figure S1.). Furthermore, comparing the Northern analysis data of our N. benthamiana line to the Nb-1 accession to detect tissue specific expression pattern of miRNAs, we were not able to confirm the differences occasionally observed in the miRNA read numbers at certain miRNA families (in seedlings: miR156, miR168, miR319, miR396, miR482 and miR6149; in leaf: miR156, miR319, miR398, miR403 and miR1919) (Fig. 4). Our miRNA expression data therefore might indicate that these N. benthamiana lines are closely related based on their very similar miRNA expression patterns.
Fig. 4

Expression analysis of selected conserved and other known miRNAs in different N. benthamiana tissues. Total RNA was extracted from different tissues including, seedling (Se), root (R), leaf (L), stem (St), flower (F) from N. benthamiana plants used in our laboratory and from plants from Boyce Thompson Institute (leafBTI - LBTI, seedlingBTI - SeBTI). The RNA was separated on PAGE and transferred to nylon membranes for Northern blot analysis of the miRNAs. Oligonucleotide probes were used to detect specific miRNAs, and an U6-specific probe was used to detect U6 RNA as a loading control for each membrane

Targets of conserved and known miRNAs

To generate a miRNA cleaved target library (degradome) from N. benthamiana we applied a high-throughput experimental approach that can identify mRNAs targeted by sRNAs [37]. The poly-A fraction of total RNA extracted from seedling (Se), root (R), leaf (L), stem (St), flower (F) of N. benthamiana plants; and leaf (LBTI) and seedling (SeBTI) of the Nb-1 accession were analysed for the identification of target transcripts of conserved, other known, and new miRNAs.

We obtained a total number of 47 million short sequencing reads representing the 5′ ends of uncapped, poly-adenylated RNAs. After initial processing, equal numbers of 20- and 21-nt sequence reads were obtained, and 48 % of the short sequencing reads could be mapped to the N. bentamiana transcriptome.

In plants, miRNA mediated mRNA cleavage is highly specific and miRNAs have been shown to bind with near perfect complementarity to their mRNA targets, which generally leads to the slicing of the mRNA between positions 10 and 11 of the AGO1 bound miRNA. As a consequence, the cleaved mRNA targets should have distinct peaks in the degradome sequence tags at the predicted cleavage site relative to the other regions of the transcript [38, 39]. In our analysis we have applied the PAREsnip pipeline [40] to identify cleaved targets for both known (conserved and non-conserved) and new miRNAs in N. benthamiana. Abundance of the sequenced tags was plotted on each transcript and the results are shown on Additional file 3: Figure S2. The cleaved target transcripts have been categorized into five classes (categories 0, 1, 2, 3 and 4) as it was defined previously in CleaveLand (version2) [41]. In our target list we kept high-confidence miRNA-target gene interactions (categories 0, 1, 2) and only category 3 targets as low–confidence miRNA-target pairs. Category 4 targets are defined as only one raw read at the expected cleavage position, however it might also be the result of the degradation of the target RNA, therefore they were omitted from our target list. This approach identified a total of 55 target mRNAs, for conserved and other known miRNAs (Table 2, Additional file 4: Table S2).
Table 2

Targets of conserved and other known miRNAs in Nicotiana benthamiana a

miRNA family

miRNA sequence

Gene ID

Clevage position

Category

Normalized abundancea

Annotation

Conserved miRNAs and their targets

Nb_miR156

TGACAGAAGAGAGTGAGCAC

comp77119_c0_seq6 2667_2942

1787

0

2,40

Squamosa promoter-binding-like protein 6

Nb_miR156

TGACAGAAGAGAGTGAGCAC

comp69399_c0_seq4 393_944

650

2

1,28

Squamosa promoter-binding-like protein 16

Nb_miR159

TTTGGATTGAAGGGAGCTCTA

comp71582_c0_seq2 1_1230

673

0

40,63

No annotationb

Nb_miR159

TTTGGATTGAAGGGAGCTCTA

comp69815_c0_seq4 1_894

601

0

0,39

Transcription factor GAMYB

Nb_miR159

TTTGGATTGAAGGGAGCTCTA

comp73942_c0_seq1 927_2375

1839

0

2,14

Transcription factor GAMYB

Nb_miR160

TGCCTGGCTCCCTGTATGCCA

comp78286_c0_seq3 693_2783

2065

0

307,20

Auxin response factor 18

Nb_miR160

TGCCTGGCTCCCTGTATGCCA

comp79462_c0_seq1 2477_3379

2658

0

6,41

Auxin response factor 16

Nb_miR164

TGGAGAAGCAGGGCACGTGCA

comp72325_c0_seq2 310_1305

994

0

3,43

Protein CUP-SHAPED COTYLEDON 2

Nb_miR165/166

TCGGACCAGGCTTCATTCCCC

comp80060_c0_seq5 1298_3817

1868

0

51,20

Homeobox-leucine zipper protein REVOLUTA

Nb_miR165/166

TCGGACCAGGCTTCATTCCTC

comp79517_c0_seq6 1043_3556

1601

0

246,61

Homeobox-leucine zipper protein ATHB-15

Nb_miR165/166

TCGGACCAGGCTTCATTCCTC

comp79347_c3_seq8 336_611

546

1

1,60

No annotationb

Nb_miR167

AGATCATGTGGTAGCTTCACC

comp79742_c0_seq4 124_2421

1700

2

5,90

5-methyltetrahydropteroyltriglutamate--homocysteine methyltransferaseb

Nb_miR167

AGATCATGTGGTAGCTTCACC

comp74516_c0_seq2 292_2619

1160

2

3,54

Subtilisin-like proteaseb

Nb_miR168

TCGCTTGGTGCAGGTCGGGACC

comp79927_c1_seq7 1_243

876

 

1,60

Protein argonaute 1A

Nb_miR169

TAGCCAAGGATGACTTGCCT

comp72459_c1_seq2 1230_1673

1724

2

0,19

Nuclear transcription factor Y subunit A-5/CCAAT-binding transcription factor

Nb_miR169

TAGCCAAGGATGACTTGCCT

comp72338_c0_seq4 1046_1396

1439

2

0,29

Nuclear transcription factor Y subunit A-5/CCAAT-binding transcription factor

Nb_miR169

TAGCCAAGGATGACTTGCCT

comp73705_c1_seq8 1254_1739

1836

1

3,15

Nuclear transcription factor Y subunit A-8/CCAAT-binding transcription factor

Nb_miR169

TAGCCAAGGATGACTTGCCT

comp67524_c0_seq9 544_1167

1246

0

1,96

Nuclear transcription factor Y subunit A-10/CCAAT-binding transcription factor

Nb_miR171

TTGAGCCGCGCCAATATCACG

comp76988_c0_seq2 277_1911

896

0

26,05

Scarecrow-like protein 15

Nb_miR171

TTGAGTCGCGCCAATATCACT

comp80119_c0_seq4 672_2573

1552

0

34,34

Scarecrow-like protein 6

Nb_miR171

TTGAGTCGCGCCAATATCACT

comp75200_c0_seq2 459_2717

1696

0

109,89

Scarecrow-like protein 6

Nb_miR172

AGAATCTTGATGATGCTGCAG

comp78340_c2_seq4 552_1409

2200

0

4,42

Floral homeotic protein APETALA 2

Nb_miR319

TTGGACTGAAGGGAGCTCCCT

comp68096_c0_seq1 79_1191

1046

0

1,02

Transcription factor TCP4

Nb_miR319

TTGGACTGAAGGGAGCTCCCT

comp73714_c2_seq12 2093_2317

2006

 

0,98

Transcription factor TCP2

Nb_miR393

TCCAAAGGGATCGCATTGATCC

comp80206_c0_seq2 468_4724

4235

2

0,29

No annotationb

Nb_miR394

TTGGCATTCTGTCCACCTCC

comp60101_c0_seq1 5351_5605

5291

2

2,16

Tripeptidyl-peptidase 2b

Nb_miR395

CTGAAGTGTTTGGGGGAACTC

comp75863_c0_seq1 200_1609

553

2

0,53

ATP sulfurylase 1, chloroplastic

Nb_miR395

CTGAAGTGTTTGGGGGAACTC

comp29318_c1_seq1 108_620

254

0

1,07

Sulfate transporter 2.1

Nb_miR396

TTCCACATCTTTCTTGAACTG

comp71133_c0_seq1 1089_1355

935

2

2,10

Protein THYLAKOID FORMATION1, chloroplasticb

Nb_miR396

TTCCACAGCTTTCTTGAACTG

comp77639_c0_seq4 942_2765

1723

0

4,42

Growth-regulating factor 6

Nb_miR396

TTCCACAGCTTTCTTGAACTG

comp67678_c0_seq1 205_573

279

0

12,19

Thioredoxin H-type 1b

Nb_miR396

TTCCACAGCTTTCTTGAACTG

comp50987_c1_seq1 2_379

144

1

0,48

40S ribosomal protein S15b

Nb_miR396

TTACACAGCTTTCTTGAACTG

comp69468_c0_seq1 204_1724

1425

2

0,58

Protein IQ-DOMAIN 14b

Nb_miR396

TTCCACAGCTTTCTTGAACTG

comp77795_c0_seq2 2_1780

1546

 

0,58

Pentatricopeptide repeat-containing protein At5g04810, chloroplasticb

Nb_miR396c

TTCCACAGCTTTCTTGAACTG

comp77334_c1_seq28 1342_2196

1370

0

3,74

Growth-regulating factor 5

Nb_miR396

TTCCACAGCTTTCTTAAACTG

comp79406_c0_seq1 393_3506

1932

2

0,29

No annotationb

Nb_miR396

TTCCACAGCTTTCTTGAACTG

comp76253_c0_seq1 643_1557

767

0

0,19

Growth-regulating factor 9

Nb_miR396

TTCCACAGCTTTCTTGGACTG

comp69128_c0_seq2 114_806

521

2

0,19

DNA-directed RNA polymerase V subunit 5A-l ikeb

Nb_miR397

TCATTGAGTGCAGCGTTGATG

comp73318_c2_seq1 87_1109

883

2

4,42

Glyceraldehyde-3-phosphate dehydrogenase, cytosolicb

Nb_miR397

TCATTGAGTGCAGCGTTGATG

comp75344_c1_seq2 127_1839

810

2

0,24

Laccase-7

Nb_miR397

TCATTGAGTGCAGCGTTGATG

comp77652_c0_seq1 1261_3177

176

2

0,29

Probable serine/threonine-protein kinase abkCb

Nb_miR398

TATGTTCTCAGGTCGCCCCTG

comp100607_c0_seq1 102_557

78

0

9,46

Umecyanin

Nb_miR408

TGCACTGCCTCTTCCCTGGCT

comp85708_c0_seq1 121_624

630

0

15,30

Uclacyanin-2

Nb_miR408

TGCACTGCCTCTTCCCTGGCT

comp79061_c1_seq3 184_1473

2346

0

12,38

Copper-transporting ATPase PAA2, chloroplastic

Other known miRNAs and their targets

      

Nb_miR482

TTCCAATTCCACCCATTCCTA

comp75828_c0_seq3 249_1742

1609

2

1,07

No annotationb

Nb_miR827

TTAGATGAACATCAACAAACT

comp75426_c0_seq1 2_226

1982

2

1,36

UPF0496 protein 4

Nb_miR4376

TACGCAGGAGAGATGATACTG

comp79500_c0_seq4 305_3562

284

2

0,98

Calcium-transporting ATPase 8, plasma membrane-type

Nb_miR6020

AAATGTTCTTCGAGTATCTTC

comp70698_c0_seq1 752_1555

996

1

0,68

GPN-loop GTPase 3 homologb

Nb_miR6020

AAATGTTCTTCGAGTATCTTC

comp74553_c0_seq5 265_702

596

0

1,47

No annotationb

Nb_miR6020

AAATGTTCTTCGAGTATCTTC

comp75715_c0_seq5 271_2055

1544

2

0,27

Probable methylenetetrahydrofolate reductaseb

Nb_miR6149

TTGATACGCACCTGAATCGGG

comp80883_c0_seq1 2_310

14

2

0,27

Tubulin alpha chainb

Nb_miR6149

TTGATACGCACCTGAATCGGG

comp75221_c0_seq2 455_1678

1646

2

1,77

Serine/threonine-protein kinase HT1b

Nb_miR6151

TGAGTGTGAGGCGTTGGATTGA

comp84169_c0_seq1 105_1127

334

2

2,10

Probable carboxylesterase 8b

Nb_miR6157

TGGTAGACGTAGGATTTGAAA

comp66224_c0_seq2 136_780

259

 

0,68

Ras-related protein RABA2bb

Nb miR6161

TGCTGGACCGACATACTTTGT

comp74264_c0_seq1 147_1052

343

2

0,48

60S ribosomal protein L5b

a The abundance for the degradome fragment (tag) indicating cleavage at that position/total number of fragments x 1,000,000

b New target in N. benthamiana for conserved and other known miRNAs

Altogether we found 44 targets for conserved miRNAs, from which 23 were classed as category 0, six as category 1 and fifteen as category 2. For other known miRNAs we have found 11 targets, from which one was classed as category 0, two as category 1 and eight as category 2.

We identified targets for 18 conserved miRNA families out of 23. Some of the conserved miRNAs without any identified targets (miR390 and miR399) were expressed at a low level in all of the sRNA libraries (Fig. 2), which may explain the lack of detection of cleaved targets. However, both miR162 and miR403 were expressed at a considerable level in at least some of the tissues (Fig. 2) without mRNA targets identified in the degradome libraries. As an alternative explanation these miRNAs might be engaged in translational repression, however in different plant species cleaved target mRNAs were identified as their target which makes this explanation less plausible [13]. We have confirmed 29 conserved targets of conserved miRNAs already identified in different plants [13]. Many of the identified conserved targets are members of different families of transcription factors, such as squamosal promoter-binding (SBP), MYB, ARF, NAC, HD-ZIPIII, CCAAT-binding, AP2 and TCP. In addition to these targets we also identified 15 new targets in N. benthamiana for conserved miRNAs (Table 2). We found one target of the non-conserved miR4376 which was already identified in tomato [42]. We also identified nine new targets of seven non-conserved miRNAs (Table 2). Most of the non-conserved miRNA families for which no target had been identified were expressed at a very low level in all tissues (miR170, miR477, miR1446, miR6019, miR6025, miR6147), except miR479, miR1919, miR6153 and miR6155 (expressed at moderate level at least in one sample) (Table 2, Fig. 2).

N. benthamiana specific miRNAs

We used strict criteria to identify new miRNAs. Briefly, the sRNA reads were mapped to the N. benthamiana genome and secondary structures were predicted for each locus. Based on the hairpin prediction, the presence of miRNA* strands in the sRNA libraries and validated target mRNA in the degradome libraries we found 18 new miRNA candidates (Fig. 5, Additional file 5: Figure S3.). Nb_miRC1_3p was the most abundant Nicotiana specific miRNA in our sRNA libraries and it expressed in all of the tissues. The sequence of Nb_miRC1_3p was also reported previously from a large scale sRNA dataset as endogenous small RNA of Nicotiana attenuata [43], however it was not further investigated which small RNA class it belongs to. The second most abundant miRNA was the Nb_miRC2_3p and it was also present in all of the small RNA libraries. For the remaining N. benthamiana specific miRNAs the relative number of reads in all tissues was low (Fig. 5). However, this result is in line with the observation shown previously, that miRNA abundance decreases as the conservation of the sequence decreases [15].
Fig. 5

Novel miRNAs in N. benthamiana. Normalized read numbers of novel miRNAs across the tissues included in this study. Expression profiles are expressed in reads per million genome matching reads. Heat map colours represents absolute normalized levels of miRNA expression ranging from less than 1 RPM (white) to more than 1000 RPM (red) as indicated in the colour key

As a next step, we checked the size distribution and starting nucleotide of the new N. benthamiana specific miRNAs in our libraries. The 21 nt long miRNAs were the most significant size class and half of the new miRNAs belong to this group (Fig. 6a). In several cases they were accompanied by additional size class, 20 nucleotide long sequences were present in significant proportions (Nb_miRC18_3p and Nb_miRC11_5p). Three miRNAs exhibited a strong preference for 22 nucleotide sequences (Nb_miRC6_3p, Nb_miRC4_3p and Nb_miRC14_5p) and in five miRNA families the 24 nucleotide long sequences were the most abundant size class (Nb_miRC8_3pa, Nb_miRC17_5p, Nb_miRC7_3p, Nb_miRC13_3p and Nb_miRC10_3p). We found that two miRNA families showed the coexistence of 20–24 nucleotide variants with the 24 nucleotides being the most abundant variants (Nb_miRC5_3p and Nb_miRC9_5p) (Fig. 6a).
Fig. 6

Size distribution and starting nucleotide of the novel N. benthamiana specific miRNAs. The relative abundance of different size categories (a), from 20 to 24 nucleotides is shown for the novel miRNAs presented in Fig. 5. The relative abundance of the 5′-nucleotide (b) is shown for the novel miRNAs presented in Fig. 5

Next we checked the 5′-nucleotide distribution of the new miRNA families in our libraries. Seven started with uracil at their 5′-end (Nb_miRC16_3p, Nb_miRC14_5p, Nb_miRC1_3p, Nb_miRC18_3p, Nb_miRC15_5p, Nb_miRC3_5p and Nb_miRC2_3p) (Fig. 6b). Eight miRNA families exhibited a preference for an adenine at position 1, although six of these have a different nucleotide composition at position 1 to a variable degree (NB_miRC9_5p, NB_miRC5_3p, NB_miRC8_3p_a, NB_miRC13_3p, NB_miRC7_3p and NB_miRC10_3p). In three miRNA families the most frequently found first nucleotide at their 5′-end was cytosine (Nb_miRC11_5p, Nb_miRC4_3p and Nb_miRC12_5p). One miRNA family exhibited a preference for a guanine at position 1, although a significant fraction has uracil at the 5′-position (Nb_miRC6_3p) (Fig. 6b). Although the majority of plant miRNAs have a uracil at position 1, it is not unusual that some miRNA families contain adenine, cytosine and even guanine in significant proportions at the 5′-position [15].

Young miRNAs are often weakly expressed, processed imprecisely or lack targets [16]. Our data fits well with these previous observations since most of the N. benthamiana specific miRNAs showed low relative abundance in our libraries (below 25 RPM; except Nb_miRC1_3p, Nb_miRC2_3p and Nb_miRC3_5p) and in several cases they were accompanied by additional size classes for various degrees. Furthermore, some of the new miRNAs identified in our sRNA libraries are produced from long hairpin precursors that may also indicate the young evolutionary origin (Nb_miRC2_3p, Nb_miRC3_5p, Nb_miRC5_3p, Nb_miRC8_3pa and Nb_miRC18_3p) (Additional file 5: Figure S3). This situation is well observable on the Nb_miRC8 precursor where two miRNA duplexes were both identified in the sRNA libraries and detected by Northern blots (Additional file 6: Figure S4). However, we did not identify miRNAs without target mRNAs in our data set, since we used the presence of cleaved target mRNA as a criterion to select new miRNAs.

We used Northern blot analysis to check the expression level of N. benthamiana specific miRNAs in five tissues (seedling, root, leaf, stem and flower). The miRNAs that gave signal on the Northern blot, in most cases were detectable in all of the tissues tested (Fig. 7). Some of the new miRNAs were abundant in specific tissues (Nb_miRC10_3p in stem and flower; Nb_miRC16_3p in seedling and flower), and many of them showed differential expression in the tissues analysed (Nb_miRC1_3p, Nb_miRC2_5p, Nb_miRC10_3p, Nb_miRC11_5p and Nb_miRC16_3p) (Fig. 7). The relative number of reads in all tissues was very low for most of the miRNAs (Nb_miRC1_3p, Nb_miRC2_3p and Nb_miRC3_5p was an exception) and this was also reflected in the Northern blot analysis, since we did not obtain signal for six miRNAs (Nb_miRC5_5p, Nb_miRC12_5p, Nb_miRC13_3p, Nb_miRC14_5p, Nb_miRC15_5p and Nb_miRC18_3p). The expression profiles obtained by Northern blot analysis were different from the sequencing data for Nb_miRC3_5p, Nb_miRC6_3p, Nb_miRC8_3pa, Nb_miRC11_5p and Nb_miRC17_5p. However, for the other new miRNAs (Nb_miRC1_3p, Nb_miRC7_3p, Nb_miRC9_5p and Nb_miRC10_3p), sequencing data and expression profiles obtained by Northern blot analysis showed good correlation (Fig. 5 and Fig. 7). Although the relative read numbers for most of the new miRNAs were low, we were able to confirm the presence of 13 N. benthamiana specific miRNAs by Northern blot.
Fig. 7

Expression patterns of novel miRNAs found in N. benthamiana. Total RNA was extracted from different tissues including, seedling (Se), root (R), leaf (L), stem (St), flower (F) from N. benthamiana plants used in our laboratory and from plants from Boyce Thompson Institute (leafBTI - LBTI, seedlingBTI - SeBTI). The RNA was separated on PAGE and transferred to nylon membranes for Northern blot analysis of the novel miRNAs. Oligonucleotide probes were used to detect specific miRNAs, and an U6-specific probe was used to detect U6 RNA as a loading control for each membrane

Targets of N. benthamiana specific miRNAs

We identified 32 targets for new miRNAs using our degradome libraries. Interestingly, in the case of Nb_miRC5 we found target for both the mature and the star strand of the new miRNA (Table 3; Additional file 7: Figure S5; Additional file 8: Table S3). Based on the degradome data, among the identified target mRNAs of the specific, new N. benthamiana miRNAs, three were classed as category 0, two as category 1, twenty-two as category 2 and five as category 3. Comparing the target list of the known (conserved and non-conserved) and new miRNAs the most obvious difference between them is that the known miRNA targets mostly belong to category 0 and 1 (Tables 2 and 3). Based on their molecular function both groups regulate various genes that are included in transcriptional regulation or enzymatic activity (Additional file 9: Figure S6.).
Table 3

Targets of novel miRNAs found in Nicotiana benthamiana

new miRNA ID

Gene ID

Cleavage position

Category

Alignment score

Normalized abundancea

Annotation

Nb_miRC1_3p

comp79937_c1_seq1 312_1058

862

3

3,5

0,2

Elongation factor 1-alpha 4

Nb_miRC1_3p

comp78325_c0_seq3 335_2797

1128

1

1,0

0,2

Protein ROS1

Nb_miRC2_3p

comp75577_c0_seq17 1347_1982

405

2

4,0

1,2

Down syndrome critical region protein 3 homolog

Nb_miRC3_5p

comp79768_c0_seq4 287_3412

1868

2

3,5

1,1

Elongation factor Ts

Nb_miRC4_3p

comp76033_c0_seq2 367_1701

917

2

4,0

1,9

CBL-interacting serine/threonine-protein kinase 5

Nb_miRC5_3p

comp73317_c0_seq28 1673_2236

2967

0

3,5

2,1

Peroxisome biogenesis factor 10

Nb_miRC5_3p

comp69461_c0_seq1 371_982

1380

2

0,5

0,2

Protein CREG1

Nb_miRC5_3p

comp76292_c1_seq18 500_808

1632

2

1,5

0,2

Probable WRKY transcription factor 53

Nb_miRC5_3p

comp72235_c0_seq2 239_1444

1720

2

2,5

0,3

Cytochrome b561 and DOMON domain-containing protein At5g47530-like

Nb_miRC5_5p

comp70843_c0_seq1 178_1023

528

2

4,0

1,4

Protein TIC 21, chloroplastic

Nb_miRC6_3p

comp75362_c2_seq1 7645_8472

2399

2

3,5

0,2

G-type lectin S-receptor-like serine/threonine-protein kinase At1g11330

Nb_miRC7_3p

comp73495_c0_seq6 312_1019

1288

2

3,5

1,4

Proteasome subunit alpha type-2-A

Nb_miRC7_3p

comp56753_c0_seq1 215_457

517

0

2,0

5,5

WAT1-related protein At5g40240-like

Nb_miRC8_3p_a

comp71383_c0_seq6 99_857

1317

3

2,5

0,6

Aquaporin TIP1-3

Nb_miRC8_3p_a

comp75266_c2_seq4 3193_3486

3454

2

1,0

0,7

Probable isoaspartyl peptidase/L-asparaginase 3

Nb_miRC9_5p

comp71496_c0_seq1 489_1463

462

2

4,0

0,2

Serine/threonine-protein phosphatase 2A regulatory subunit B” subunit alpha

Nb_miRC9_5p

comp64986_c0_seq1 125_487

1232

2

2,5

0,2

60S ribosomal protein L34

Nb_miRC10_3p

comp77607_c3_seq4 3_1151

2317

2

4,0

0,2

Suberization-associated anionic peroxidase

Nb_miRC10_3p

comp80078_c3_seq4 193_2097

2131

2

1,0

1,1

Formate--tetrahydrofolate ligase

Nb_miRC10_3p

comp72702_c0_seq4 152_2431

2575

3

2,0

1,0

Beta-amyrin synthase

Nb_miRC11_5p

comp82078_c0_seq1 3_1277

938

2

3,5

2,7

Threonine deaminase

Nb_miRC11_5p

comp78978_c0_seq3 374_2785

2557

2

3,0

0,4

Transcription factor RF2a/ Probable transcription factor PosF21

Nb_miRC11_5p

comp89465_c0_seq1 218_1237

532

3

4,0

0,2

Ervatamin-B-like

Nb_miRC12_5p

comp79295_c0_seq1 283_3321

3114

2

3,5

2,7

Probably inactive leucine-rich repeat receptor-like protein kinase At3g28040

Nb_miRC12_5p

comp56752_c0_seq1

568

1

3,5

0,7

ZRT/IRT-like protein 1

Nb_miRC13_3p

comp77835_c0_seq3 61_621

797

2

2,5

0,3

Disease resistance response protein 206

Nb_miRC14_5p

comp74263_c0_seq1 230_2029

966

2

4,0

3,8

Chaperonin 60 subunit beta 2, chloroplastic

Nb_miRC15_5p

comp78088_c1_seq1 1536_2366

3251

3

4,0

0,7

Peroxisome biogenesis protein 19-1

Nb_miRC15_5p

comp85070_c0_seq1 3_2648

2151

2

2,5

1,0

(E,E)-geranyllinalool synthase

Nb_miRC16_3p

comp88815_c0_seq1 2_1909

1845

2

2,5

0,9

Polyphenol oxidase, chloroplastic

Nb_miRC17_5p

comp63365_c1_seq3 3_242

29

0

1,0

1,3

Heterotrimeric GTP binding protein alpha subunit

Nb_miRC18_3p

comp67145_c0_seq1 106_930

361

2

3,5

2,0

50S ribosomal protein L3, chloroplastic

a The abundance for the degradome fragment (tag) indicating cleavage at that position/total number of fragments x 1,000,000

The new miRNAs target different genes with a wide variety of predicted functions. One of the three identified category 0 targets of the new miRNAs is the mRNA of the heterotrimeric GTP binding protein (G proteins) alpha subunit (targeted by Nb_miR17_5p). G proteins are highly conserved in eukaryotes. Plant G proteins play an important regulatory role in multiple physiological processes. They are involved in signal transduction from hormone receptors, including the plant hormones gibberellin and abscisic acid that regulate gene expression; secretion, defence, stomata movements, channel regulation, sugar sensing and cell death [44]. The heterotrimeric G protein complex is minimally composed of three subunits: alpha, beta and gamma. Plants have only a small number of genes encoding the G proteins subunits. Arabidopsis has only one canonical G protein alpha subunit, one beta subunit and three gamma subunit [45]. Plant alpha subunits are highly conserved between species, it binds and hydrolyse GTP and relay signals by interacting with downstream effector proteins [46]. Interestingly, during convergent evolution human G protein alpha-13 (GNA13) expression is also regulated by miRNA (miR-31) in breast cancer cells [47].

Another category 0 target is the mRNA of Peroxisome Biogenesis Factor 10 (PEX10). It is cleaved by Nb_miRC5_3p and has been demonstrated to be a component of the peroxisomal matrix protein import machinery. Peroxisomes are eukaryotic organelles and they are involved in a wide range of processes. Plant peroxisomes are important in primary and secondary metabolism, development, and responses to abiotic and biotic stresses. Previous studies identified 22 PEX genes in the Arabidopsis genome and demonstrated that they play a pivotal role in the import of peroxisomal matrix proteins [48]. PEX 10 perform multiple functions, including the biogenesis of ER-derived protein and oil bodies [49], the maintenance of ER morphology, the formation of cuticular wax [50], peroxisome and chloroplast connections [51].

One of the category 1 targets is REPRESSOR OF SILENCING (ROS1) which is cleaved by Nb_miRC1_3p. Interestingly, the sequence of Nb_miRC1_3p can also be found in Nicotiana attenuata [43] and its target site on ROS1 is conserved in other Nicotiana species as well. ROS1 encodes a nuclear DNA glycosylase domain protein that catalyse the release of 5-methylcytosine (5-meC) from DNA via a base excision repair reaction [52]. DNA cytosine methylation is an important epigenetic mark conserved in many eukaryotes. It has important roles in transposon silencing, genome organization, genomic imprinting and regulation of gene expression [53]. During continuous adaptation to variable external and internal environments DNA methylation patterns are dynamically controlled by methylation and demethylation reactions. ROS1 plays an important role in active DNA demethylation and helps to maintain gene expression [54, 55]. The targeting of ROS1 by a miRNA provides a new regulatory layer to reinforce transcriptional gene silencing by a post-transcriptional repression of its activity. The targeting of a DNA glycosylase (DEMETER-LIKE protein3) by a miRNA (miR402) was first predicted in Arabidopsis [56] and later it was shown that the expression of DEMETER-LIKE protein3 mRNA was down-regulated in miR402-overexpressing transgenic plants [57].

The other category 1 target is a zinc-regulated transporter (ZRT), iron-regulated transporter (IRT)-like protein 1 (ZRT/IRT-like protein 1) and is cleaved by NB-miRC12_5p. ZRT/IRT-like protein family has been demonstrated to be involved in metal uptake and transport. ZRT/IRT-like proteins generally contribute to metal ion homeostasis by transporting cations into the cytoplasm [58]. It has been reported in several plant species that various miRNAs are vital for maintaining nutrient homeostasis by regulating the expression of transporters that are involved in nutrient uptake and mobilization [59].

Other targets that are worthy to note are the WAT1-related protein At5g40240-like gene targeted by Nb_miRC7_3p; the CBL-interacting serine/threonine-protein kinase gene targeted by Nb_miRC4_3p, proteasome subunit alpha type-2-A gene targeted by Nb_miRC7_3p, suberization-associated anionic peroxidase targeted by Nb_miRC10_3p and beta-amyrin synthase targeted by Nb_miRC10_3p.

Conclusions

In this study we have confirmed the expression of known and new miRNAs in various tissues of N. benthamiana using high-throughput sequencing and Northern blot analysis. As a result, this work represents a tissue specific atlas of known and new miRNA expression of N. benthamiana. In addition, we have experimentally identified many targets of both known and new miRNAs using a high-throughput method for the global identification of miRNAs targets. This study provides a valuable resource of miRNAs and their validated target mRNAs to the plant research community that will be beneficial well into the future.

Methods

Plant materials

Wild-type Nicotiana benthamiana plants and Nicotiana benthamiana plants from Boyce Thompson Institute were grown in soil or, for seedling and root samples, on half-strength Murashige and Skoog plates under standard growth conditions at 24 °C with 16 h of illumination per day. Total RNA was extracted from 14 day old seedlings and root tissues grown on plates. Furthermore total RNA was also extracted from leaves, stems and flowers without sepals collected from plants grown in soil. Total RNA was isolated by using the phenol/chloroform extraction method [60]. The quality and the quantity of the isolated total RNAs were checked using a nanodrop spectrophotometer and the integrity of RNAs was checked via non-denaturing agarose gel electrophoresis.

RNA sequencing (RNA-Seq) library preparation for Solexa sequencing

cDNA library for RNA-Seq was generated from 1 μg total RNA using TruSeq RNA Sample Preparation Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s protocol. Briefly, poly-A tailed RNAs were purified by oligodT conjugated magnetic beads and fragmented on 94 °C for 8 min, then 1st strand cDNA was transcribed using random primers and SuperScript II reverse transcriptase (Lifetechnologies, Carslbad, CA, USA). Following this step second strand cDNA were synthesized, then double stranded cDNA molecules were end repaired and 3′ ends adenylated then Illumina index adapters were ligated. After adapter ligation step enrichment PCR was performed to amplify the adapter-ligated cDNA fragments. Fragment size distribution and molarity of libraries were checked on Agilent BioAnalyzer DNA1000 chip (Agilent Technologies, Santa Clara, CA, USA). 10pM of denatured libraries were used for cluster generation on cBot instrument, and then sequencing run was performed on Illumina HiSeq 2000 instrument (100 bp paired-end) (Illumina, San Diego, CA, USA).

Small RNA sequencing libraries for Solexa sequencing

The small RNA cDNA libraries were constructed using the Small RNA Sample Prep Kit (Illumina, CA, US), according to the manufacturer’s instructions. Briefly, 1 μg of total RNA from wild-type Nicotiana benthamiana samples, including, seedling, root, leaf, stem and flower were ligated to Solexa adaptors and then converted to cDNA by RT-PCR. The resulting cDNAs were then amplified by PCR, gel-purified and submitted for Illumina/Solexa sequencing. High-throughput sequencing was performed using HiScan SQ platform (50 bp single-end).

Degradome cDNA libraries for Solexa sequencing

The degradome cDNA library was prepared using a total RNA from wild-type Nicotiana benthamiana samples, including, seedling, root, leaf, stem and flower following the procedures previously described by German et al. [39]. Conversely to the small RNA libraries, the degradome cDNA library was sequenced with a custom-made sequencing primer (5′-CCACCGACAGGTTCAGAGTTCTACAGT-3′) [36] on HiScan SQ platform (50 bp single-end).

Northern blot analysis

A total amount of 5 μg of RNA from each Nicotiana benthamiana tissues (seedling, root, leaf, stem, flower, leaf BTI, seedling BTI) were individually separated on a 8 M UREA/12 % polyacrylamid 1 x TBE gel. After gel run we transferred the RNAs from dPAGE onto the neutral nylon membrane, Hybond NX (Amersham/GE Healthcare) by semi-dry electroblotter. The transferred molecules were cross-linked by the enhanced sensitivity 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) chemical cross-linking method at 60 °C for 90 min as described previously by Pall et al. [61]. The membranes were prehybridized at 38 °C for 1 h in ULTRAhyb® Ultrasensitive Hybridization Buffer (Ambion/thermo Scientific). DNA oligo probes were end labelled by the forward reaction using T4 polynucleotide kinase (Thermo Scientific) and [γ32P] ATP for 1 h at 37 °C. Hybridization was performed at 40 °C overnight. Each membrane was stripped than rehybridized with different probes (The sequences of the used probes are available in Additional file 10: Table S4.). The membranes were exposed to a phosphorimager.

Real-time PCR quantification of miRNAs

We also used real-time looped RT-qPCR procedure for detection and quantification of miRNAs. Stem-loop RT primers and forward qPCR primers were designed according to Chen et al. [62]. (The sequence data is aviable in Additional file 10: Table S4). As internal reference gene, nucleolar small RNA U6 was used [63] . We followed the protocol by Varkonyi-Gasic et al. [64] with optimalisation to our samples. For DNase treatment of the RNA samples 3 units of DNase I (Thermo Scientific) were used to 250 ng total RNA from the different tissues represented in this study. After 30 min incubation at 37 °C, a phenol/chloroform extraction was performed to inactivate the enzyme and purificate the template. For the elution 20 μl MQ water was used. In the next step, a multiplexed cDNA synthesis of U6 and miRNA was performed. Stem-loop pulsed reverse transcription protocol was performed in a 20 μl reaction volume with each sample for RT and NO RT reactions (0.5 μl (10 mM) dNTP’s, 1–1 μl (1 μM) U6 reference and miRNA specific primer and MQ water was mixed and heated to 65 °C for 5 min and incubate on ice for 2 min. Then 4 units of RNaseOUT (Invitrogen), 50 units of RevertAid H- Reverse transcriptase, 4 μl 5x RT Buffer (Thermo Scientific) and 1 μl RNA template from the previous DNase treatment the was added to the reaction tubes.). The pulsed RT was preformed in thermo cycler: 30 min at 16 °C incubation, followed by pulsed RT of 60 cycles at 30 °C for 30 s, 42 °C for 30 s and 50 °C for 1 s, then at 85 °C for 5 min to inactivate the enzymes. To test the primer specificity and cDNA quality end-point PCR was performed with Pfu polymerase (Thermo Scientific) by 40 cycles following the Várkonyi-Galic et al. protocol. To perform real-time PCR the following components were used: 5 μl 2x FastStart Essential DNA Green Master Mix (Roche), 0,5 μl (10 μM) forward primer, 0,5 μl (10 μM) Universal reverse primer, 3 μl water and 1 μl RT product. PCR tubes were incubated at 95 °C for 10 min, followed by a 2 Step amplicifation by 40 cycles of 95 °C for 15 s, 60 °C for 60 s. For melting curve analysis, the samples were denaturated at 95 °C for 10 s, 65 °C for 60 s, 97 °C 1 s, then cool to 37 °C in a Roche LightCycles 96 instrument. To analyse results the LightCycler software was used.

Small RNA processing

Raw sequence reads quality check was performed using FastQC (version 0.11.3). For adaptor trimming cutadapt (version 1.2.1) was used with the following parameters: minimal sequence length after adaptor removal was 16, maximal sequence length was 28 [65]. We used UEA Small RNA Workbench (version 2.5.0) for all miRNA processing tasks [66]. MiRProf calculated the expression of known miRNAs. This program uses Mirbase (version 20). We allowed 2 mismatches during the analysis. We grouped together mismatches, variants and miRNAs from different organisms and worked only with families. MirCat identified candidant microRNAs. We used the default plant specific parameters. PAREsnip was used to process degradome sequences for finding microRNA targets [40] (Additional file 11). During this analysis, we discarded results from category 4, the maximal mismatch number was 4, mismatches at position 10–11 were not allowed and more than two mismatches at adjacent positions also not allowed. Every other parameter was the default. We have created a non-redundant scaffold set from the available N. benthamiana genome sequencing projects using Blast. We used this set as genome in all programs where genome sequence was a mandatory requirement. Results from these programs were analysed further with custom made Perl and Python scripts. For statistical analysis and visualization R was used [67].

Transcript processing and annotation

To generate the corresponding mRNA transcriptome we have sequenced Illumina paired end TruSeq libraries from the same N. benthamiana leaf, stem, germ, root, flower and seed samples as at the small RNAs. We pooled together 315 million 2x100 bp reads and used Trinity de novo assembly program (r2013-02-16) with default parameters [68].

To find biological function for de-novo transcripts, Trinotate was used (version: 20130225) according to the manual [68]. All related data were pushed into an SQLight database for further processing.

To perform the Gene Ontology (GO) analysis of miRNA targets the agriGO web-based tool and database version 1.2 was used [69]. The analysis setting was the following: Singular Enrichment Analysis (SEA) with the Arabidopsis thaliana TAIR9 reference gene model. The graphical results showing the molecular functions.

Data access

The RNA-seq, sRNA and degradome data discussed in this publication have been deposited in National Center for Biotechnology Informations (NCBI) BioProject database under Accession number: PRJNA288746.

Declarations

Acknowledgements

This work has been supported by OTKA grants to GS (K-101793; K-106170), JB (NK105850), DS (K-109835), EV (K-108718) and ZH (K-109438) and by the Hungarian Ministry of Agriculture to EB and TN (grant number NAIK-MBK/M71411). We would like to thank the help of Andor Auber with the RT-qPCR experiment. We are thankful for Douglas Pyott and Attila Molnar for critically reading the manuscript.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Institute of Plant Biotechnology, National Agricultural Research and Innovation Centre, Agricultural Biotechnology Institute

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