Abstract

MicroRNAs (miRNAs) are a distinct class of small RNAs in plants that not only regulate biological processes but also regulate response to environmental stresses. The toxic heavy metal cadmium (Cd) induces expression of several miRNAs in rapeseed (Brassica napus), but it is not known on a genome-wide scale how the expression of miRNAs and their target genes, is regulated by Cd. In this study, four small RNA libraries and four degradome libraries were constructed from Cd-treated and non-Cd-treated roots and shoots of B. napus seedlings. Using high-throughput sequencing, the study identified 84 conserved and non-conserved miRNAs (belonging to 37 miRNA families) from Cd-treated and non-treated B. napus, including 19 miRNA members that were not identified before. Some of the miRNAs were validated by RNA gel blotting. Most of the identified miRNAs were found to be differentially expressed in roots/shoots or regulated by Cd exposure. The study simultaneously identified 802 targets for the 37 (24 conserved and 13 non-conserved) miRNA families, from which there are 200, 537, and 65 targets, belonging to categories I, II, and III, respectively. In category I alone, many novel targets for miRNAs were identified and shown to be involved in plant response to Cd.

Introduction

Toxic heavy metals such as cadmium (Cd) and mercury (Hg) constitute major contaminants due to their significant release into environments through anthropogenic activities (e.g. use of trace metal-containing fertilizers, sewage sludge, and fungicides) (Alloway and Steinnes, 1999; Chen et al., 2009). Cd ranks first among the top seven metals (Cd, Cr, Cu, Hg, Ni, Pb, and Zn) released into ecosystems (Han et al., 2002). Soils contaminated with Cd have increasingly become a concern, because Cd is mobile in soils and readily accumulated by crops. Thus, it affects not only crop productivity, but also brings risks to food safety (McLaughlin et al., 1999). Overload of Cd in plants leads to its binding to apoplastic and symplastic target sites, which disrupts basic mineral nutrition or blocks cell division and development (Prasad et al., 2001; Sun et al., 2007; Ahmad et al., 2009). 
A secondary toxic response such as oxidative stress may be evoked through the generation of reactive oxygen species by Cd ( Rodriguez-Serrano et al., 2006). Thus, it is of great importance to minimize Cd concentrations in soils.

The use of plants to remove heavy metals from soils, namely phytoremediation, has been considered as cost-effective and environmentally friendly and has been widely used in agricultural practice (Ebbs et al., 1997; Pilon-Smits and Pilon, 2002; Chen et al., 2009). This technique emphasizes hyper-accumulation of heavy metals from soils and translocation of the hazards to above ground, thus reducing the metal concentrations in soils to a minimum level (McGrath et al., 2002). Recently, an alternative way to limit heavy metals entering the food chain without treating soils has been proposed (Grant et al., 2008; Liu, 2009). This concept refers to breeding and genetic techniques to minimize the heavy metal accumulation in edible parts (e.g. grains and seeds) of crops. With this approach, selection of desirable cultivars (or genotypes) that accumulate very low amount of heavy metals is crucial, and the genetic modification of plant traits with the capability of decreasing accumulation of potentially heavy metals is of significance.

To dissect the mechanism for the metal accumulation, the first step is to understand Cd-responsive genes and their regulation networks. Previous studies have shown that transcription of many genes in plants could be induced by Cd exposure (Herbette et al., 2006). Some genes encoding for metal transporters are responsible for Cd uptake and sequestration (Bovet et al., 2003). Recent studies have demonstrated that heavy metal-regulated gene expression can be also achieved at post-transcriptional levels by a group of microRNAs (Zhou et al., 2008, 2012; Huang et al., 2009, 2010; Lima et al., 2011; Wang et al., 2011; Chen 
et al., 2012; Khraiwesh et al., 2012). Using microarray, 19 Cd-responsive microRNAs (miRNAs) were identified and their target genes were predicted in rice (Oryza sativa) (Ding et al., 2011). Recently, high-throughput sequencing technology has become a powerful tool to permit the concomitant sequencing of millions of signatures in genomes of single tissue (Fahlgren et al., 2007; Kwak et al., 2009; Xue et al., 2009). This approach highlights the advantage of providing a more thorough qualitative and quantitative description of gene expression than microarray technology. Using this approach, 52 new miRNAs with ~21 nucleotides have been profiled from Medicagotruncatula seedlings exposed to mercury, most being differentially regulated by the heavy metal (Zhou et al., 2012). These results indicate that miRNA-regulated gene silencing may be involved in plant tolerance to heavy metals.

Brassica napus is one of the most importantly economical and biofuel crops. As a member of Brassicaceae family, B. napus possesses several traits such as fast growth, high biomass, moderate metal accumulation in aerial parts, ease of harvest, and tolerance to metals, and therefore, it is a desirable candidate plant for phytoremediation (Salt et al., 1995; Clemens et al., 2002). Using a computational approach, Xie et al. (2007) identified 21 miRNAs in B. napus and showed that several miRNAs responded to heavy metals. Shortly afterwards, 36 B. napus miRNAs representing 11 miRNA families were cloned using conventional sequencing (Wang et al., 2007). Furthermore, 13 miRNAs (nine families) were cloned from a small RNA library of B. napus seedlings with exposure to Cd and deficiency in sulphate (Huang et al., 2010). To date, a growing number of miRNAs from B. napus have been discovered using various advanced technologies (Buhtz et al., 2008; He et al., 2008; Pant et al., 2009; Wei et al., 2010; Zhao et al., 2012). However, heavy metal-regulated miRNAs and their target genes have not been thoroughly identified in B. napus.

This study used the deep-sequencing technology developed by Solexa/Illumina to profile many more small RNAs and identify 84 conserved and non-conserved miRNAs from B. napus. It analysed miRNA abundance from four small RNA libraries created from Cd-treated and Cd-free roots and shoots. Deep sequencing of four degradome libraries allowed the identification of 802 targets for 37 miRNA families, of which 200, 537, and 65 in categories I, II, and III, respectively, were characterized. Some of the miRNA targets were identified as new transcripts involved in regulation of plant tolerance to Cd.

Materials and methods

Plant culture and treatment

Seeds of B. napus (line Texuan 4) were surface sterilized and germinated on a plastic net floating on 1/4-strength modified Hoagland nutrient solution (Huang et al., 2010). The plants were grown hydroponically for 14 d and then transferred to the same nutrient solution containing 0, 40, or 80 µM CdCl2 for 0, 6, 24, or 48 h. Plants were grown with a 14/10 light/dark cycle at 24 ± 1 °C and 200 µmol m–2 s–1 light intensity. After treatment, roots and shoots were separately harvested and immediately frozen in liquid nitrogen.

Construction and sequencing of small RNA libraries

The creation of the small RNA libraries was based on the procedure of Kwak et al. (2009). Total RNA was isolated from frozen shoots and roots of B. napus with Trizol (Invitrogen). Four sets of total RNA were prepared from samples of Cd-free roots (R–Cd), Cd-treated roots (R+Cd), Cd-free shoots (S–Cd), and Cd-treated shoots (S+Cd). Each RNA sample was derived from the original RNA pool prepared from Cd-free or Cd-treated tissue (roots or leaves) at each time point (0, 6, 24, and 48 h). RNA samples were quantified and equalized so that equivalent amounts of RNA from each treatment were analysed. Total RNA was purified by electrophoretic separation on 15% TBE-urea denaturing polyacrylamide gel, and small RNA regions corresponding to the 18–30 nucleotide bands in the marker lane were excised and recovered. Each library underwent flow-cell cluster generation and bridge amplification (Solexa/Illumina). The sequencer, during automated cycles of extension, recorded fluorophore excitation and determined the sequence of bases for each cluster.

Analysis of small RNA sequencing data

Raw sequence reads were processed into clean full-length reads by the BGI small RNA pipeline. Unique small RNA sequences were mapped to the known B. napus miRNA sequences (Wang et al., 2007; Xie 
et al., 2007; Buhtz et al., 2008; He et al., 2008; Pant et al., 2009; Huang et al., 2010). Small RNAs deposited at the Rfam and GenBank databases were identified using blast (http://blast.ncbi.nlm.nih.gov/Blast.cgi). The remaining unique small RNA sequences were mapped to the expressed sequence tags (EST) and tentative consensus (TC) sequences of the B. napus Gene Index (BnGI release 5.0, http://www.ncbi.nlm.nih.gov/nucest?term=Brassica_napus, http://compbio.dfci.harvard.edu/cgi-bin/tgi/gimain.pl?gudb=oilseed_rape) with no mismatch. miREAP (http://sourceforge.net/projects/mireap/) was used to extract the long precursor sequences and check the base-pairing between the predicted miRNA and miRNA*. Mfold (http://mfold.rna.albany.edu/?q=mfold/RNA-Folding-Form, Zuker, 2003) was used to predict each precursor structure. The criteria were used for selecting the new miRNAs were according to Meyers et al. (2008).

Sequencing of degradome libraries and data analysis

The degradome libraries were constructed according to the method described by Addo-Quaye et al. (2008) and German et al. (2008). Poly(A) RNA was extracted from each sample of total RNA using the Oligotex kit (Qiagen). Polyadenylated transcripts possessing 5'-monophosphates were ligated to RNA adapters consisting of a MmeI recognition site at its 3' end. After ligation, first-strand cDNA was generated using oligo d(T) and amplified using five PCR cycles. The PCR product was purified and digested with MmeI. The digested PCR product was then ligated to a 3' double DNA adapter, amplified 18 PCR cycles, and gel-purified for Solexa/Illumina sequencing.

Sequenced tags (18–21 nucleotides) were normalized after trimming sequence adapters and filtering the low-quality tags. The sliced miRNA targets were identified and classified into categories using the CleaveLand pipeline (Addo-Quaye et al., 2008, 2009a). Unique reads were normalized to give reads per million and subsequently mapped to annotated cDNA sequences from BnGI release 5.0 or B. napus precursors for miRNA analysis.

Northern blotting

For detection of miRNAs, 15 µg total RNA from samples was subjected to denaturing electrophoresis on 15% polyacrylamide gel. Carbodiimide-mediated cross-linking of RNA to Hybond-NX was performed according to Pall et al. (2007). Membranes were hybridized with DNA oligonucleotides complementary to miRNA sequences, labelled with γ-32P-ATP using T4 polynucleotide kinase (Invitrogen) (Supplementary Table S1, available at JXB online). Blots were hybridized overnight at 37 °C in ULTRAhyb-Oligo hybridization buffer (Ambion) and washed twice with 0.2 × SSC and 0.1% SDS at 37 °C for 30 min. The membranes were exposed to phosphor imager plates.

Statistical analysis

Each result in this study is the mean of at least three replicated treatments and each treatment contained at least nine seedlings. Statistical analysis using a rigorous algorithm described previously (Audic and Claverie, 1997) was performed to identify small RNAs differentially expressed between libraries. For small RNAs, the Cd-stress library-derived sequence reads were normalized to the high-quality reads of the control library. The absolute value of log2 ratio ≤ 1 was used as the threshold to judge the significant difference of miRNA expression (Zhou et al., 2012).

Results

Analysis of sequences from libraries

To identify small RNAs from B. napus, seedlings (2-week-old) were exposed to Cd at 0, 40, or 80 µM for 6–48 h. Shoots and roots were separately collected and small RNAs from the samples were isolated and pooled to generate four small RNA libraries for Cd-free roots (R–Cd), Cd-treated roots (R+Cd), Cd-free shoots (S–Cd), and Cd-treated shoots (S+Cd). Each library was individually sequenced using a Solexa/Illumina analyser. High-throughput sequencing generated 18,163,038 primary reads for R–Cd, 20,417,921 for R+Cd, 17,493,993 for S–Cd, and 18,482,210 for S+Cd, respectively (Table 1). After removal of low-quality reads, a total of 17,605,178, 19,592,894, 16,987,042, and 18,035,749 clean reads, corresponding to 5,978,720, 6,476,119, 3,131,102, and 5,753,497 unique signatures, remained for the R–Cd, R+Cd, S–Cd and S+Cd libraries, respectively. The small RNA sequences were matched to the EST database at NCBI and TC sequence database at the Dana-Farber Cancer Institute gene index project of B. napus. When total reads were analysed, 24.45–43.52% reads could be matched to the EST and TC databases, respectively (Table 1). For unique reads, only 7.14–10.25% could be matched to the EST and TC databases. A large percentage of sequences failed to map because the B. napus genome has not yet been completely sequenced.

Table 1. Categorization and abundance of small RNA and degradome reads from Cd-free and Cd-treated roots and shoots of B. napus

Library type R–Cd R+Cd S–Cd S+Cd 
Small RNA 
Total raw reads 18,163,038 20,417,921 17,493,993 18,482,210 
Total clean reads 17,605,178 19,592,894 16,987,042 18,035,749 
Unique clean reads 5,978,720 6,476,119 3,131,102 5,753,497 
Total miRNA reads 3,268,352 3,491,958 9,045,499 5,295,055 
Total rRNA reads 1,334,876 1,498,791 966,51 816,473 
Total tRNA reads 964,750 1,283,914 371,555 249,624 
Total clean reads mapping to 
ESTs and TC sequences 4,305,117 (24.45) 5,180,501 (26.44) 7,392,893 (43.52) 5,532,517 (30.68) 
Unique clean reads mapping to 
ESTs and TC sequences 427,175 (7.14) 466,292 (7.20) 320,785 (10.25) 461,185 (8.02) 
Degradome 
Total raw reads 16,945,142 14,821,751 15,592,037 14,862,060 
Total clean reads 14,352,241 13,054,929 15,418,988 14,674,354 
Unique clean reads 817,705 804,892 5,602,100 6,277,974 
Total clean reads mapping to 
ESTs and TC sequences 9,801,211 (68.29) 9,234,518 (70.74) 11,213,044 (72.72) 10,805,736 (73.64) 
Unique clean reads mapping to 
ESTs and TC sequences 379,910 (46.46) 411,845 (51.17) 3,367,425 (60.11) 3,813,251 (60.74) 
Clean reads mapping to ESTs 
and TC sequences 64,197 (64.19) 65,710 (64.70) 79,713 (78.48) 79,050 (77.83) 
Total clean reads mapping to 
miRNA precursors 27,296 21,554 5286 7125 
Clean reads mapping to 
miRNA precursors 38 49 69 79 
Library type R–Cd R+Cd S–Cd S+Cd 
Small RNA 
Total raw reads 18,163,038 20,417,921 17,493,993 18,482,210 
Total clean reads 17,605,178 19,592,894 16,987,042 18,035,749 
Unique clean reads 5,978,720 6,476,119 3,131,102 5,753,497 
Total miRNA reads 3,268,352 3,491,958 9,045,499 5,295,055 
Total rRNA reads 1,334,876 1,498,791 966,51 816,473 
Total tRNA reads 964,750 1,283,914 371,555 249,624 
Total clean reads mapping to 
ESTs and TC sequences 4,305,117 (24.45) 5,180,501 (26.44) 7,392,893 (43.52) 5,532,517 (30.68) 
Unique clean reads mapping to 
ESTs and TC sequences 427,175 (7.14) 466,292 (7.20) 320,785 (10.25) 461,185 (8.02) 
Degradome 
Total raw reads 16,945,142 14,821,751 15,592,037 14,862,060 
Total clean reads 14,352,241 13,054,929 15,418,988 14,674,354 
Unique clean reads 817,705 804,892 5,602,100 6,277,974 
Total clean reads mapping to 
ESTs and TC sequences 9,801,211 (68.29) 9,234,518 (70.74) 11,213,044 (72.72) 10,805,736 (73.64) 
Unique clean reads mapping to 
ESTs and TC sequences 379,910 (46.46) 411,845 (51.17) 3,367,425 (60.11) 3,813,251 (60.74) 
Clean reads mapping to ESTs 
and TC sequences 64,197 (64.19) 65,710 (64.70) 79,713 (78.48) 79,050 (77.83) 
Total clean reads mapping to 
miRNA precursors 27,296 21,554 5286 7125 
Clean reads mapping to 
miRNA precursors 38 49 69 79 

Values are n or n (%). EST, expressed sequence tag; TC, tentative consensus; R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

The lengths of the small RNA sequences ranged from 18 to 28 nucleotides, but the 21- and 24-nt sequences were dominant in all libraries, and the 24-nt small RNAs were most abundant (Supplementary Fig. S1). This result was consistent with Dicer-derived products and most of the previous reports from other plant species (Sunkar and Zhu, 2004; Lelandais-Brière et al., 2009; Jeong et al., 2011). The patterns for 21- and 24-nt small RNA distribution were similar, but the abundances were not identical. For example, unique small RNAs were sequenced less often in S–Cd plants than in S+Cd plants, with decreases of about 11 and 45% for 21- and 24-nt small RNAs, respectively (Supplementary Fig. S1). This observation suggests that expression of small RNAs in shoots could be modulated by Cd exposure.

The proportions of common and specific small RNAs were further analysed between pairs of libraries (between roots and shoots, or between Cd-free and Cd-treated plants). For total small RNAs in all pairs of libraries, 69.99–75.61% were common to both libraries and 7.22–19.54% were specific to one library, respectively (Fig. 1 and Supplementary Fig. S2). However, for unique small RNAs, the opposite was found: there were larger proportions of specific sequences than those of common sequences. For example, analysis comparing Cd treatment in shoots showed that more than 60% of unique small RNAs were specific to the S+Cd library, whereas only 27.55% were specific to the S–Cd library (Fig. 1C). This tendency was also true for roots, in which 44.74% unique small RNAs were specific to the R+Cd library and 40.14% were specific to the R–Cd library (Fig. 1D). These results indicate that the expression of unique small RNAs was changed by Cd exposure.

Fig. 1.

Venn diagrams for analysis of total (A and B) and unique (C and D) miRNAs between Cd-treated (S+Cd) and Cd-free (S–Cd) shoots (A and C) or between Cd-treated (R+Cd) and Cd-free (R+Cd) roots (B and D) of B. napus (this figure is available in colour at JXB online).

Fig. 1.

Venn diagrams for analysis of total (A and B) and unique (C and D) miRNAs between Cd-treated (S+Cd) and Cd-free (S–Cd) shoots (A and C) or between Cd-treated (R+Cd) and Cd-free (R+Cd) roots (B and D) of B. napus (this figure is available in colour at JXB online).

Analysis of miRNA populations and abundances

To identify miRNAs from rapeseeds, the small RNA data sets (18–24 nt) were mapped to all publicly available miRNA sequences from B. napus and other species with two or fewer nucleotide mismatches (Wang et al., 2007; Xie et al., 2007; Buhtz et al., 2008; Pant et al., 2009; Huang et al., 2010; Griffiths-Jones et al., 2008). The alignment resulted in 3,268,352, 3,491,958, 9,045,499, and 5,295,055 matches for the R–Cd, R+Cd, S–Cd, and S+Cd libraries, respectively (Table 2). Among the miRNA populations, the 21-nt miRNAs were the most abundant and accounted for 69.91–75.63% of each library. The 20-nt miRNAs were the second-most abundant, comprising 22.46–28.49% of each library. The other miRNAs, with 18, 19, or 22–24 nt, comprised less than 2% of each library.

Table 2. Lengths and abundance of miRNAs from Cd-free and Cd-treated roots and shoots of B. napus

miRNA length (nt) R–Cd R+Cd S–Cd S+Cd 
18 3467 (0.11) 5947 (0.17) 8591 (0.09) 4353 (0.08) 
19 12,573 (0.38) 17,658 (0.51) 31,048 (0.34) 18,376 (0.35) 
20 733,937 (22.46) 811,814 (23.25) 2,576,903 (28.49) 1,481,750 (27.98) 
21 2,471,928 (75.63) 2,611,854 (74.8) 6,323,660 (69.91) 3,731,808 (70.48) 
22 42,182 (1.29) 41,070 (1.18) 96,782 (1.07) 54,731 (1.03) 
23 3560 (0.11) 2831 (0.08) 8081 (0.09) 3886 (0.07) 
24 705 (0.02) 784 (0.02) 434 (0) 151 (0) 
Total 3,268,352 (100) 3,491,958 (100) 9,045,499 (100) 5,295,055 (100) 
miRNA length (nt) R–Cd R+Cd S–Cd S+Cd 
18 3467 (0.11) 5947 (0.17) 8591 (0.09) 4353 (0.08) 
19 12,573 (0.38) 17,658 (0.51) 31,048 (0.34) 18,376 (0.35) 
20 733,937 (22.46) 811,814 (23.25) 2,576,903 (28.49) 1,481,750 (27.98) 
21 2,471,928 (75.63) 2,611,854 (74.8) 6,323,660 (69.91) 3,731,808 (70.48) 
22 42,182 (1.29) 41,070 (1.18) 96,782 (1.07) 54,731 (1.03) 
23 3560 (0.11) 2831 (0.08) 8081 (0.09) 3886 (0.07) 
24 705 (0.02) 784 (0.02) 434 (0) 151 (0) 
Total 3,268,352 (100) 3,491,958 (100) 9,045,499 (100) 5,295,055 (100) 

Values are number of reads (%). R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Identification of conserved and non-conserved 
miRNA families

First, this study identified conserved miRNA families by mapping unique small RNAs to miRBase version 17 (http://microrna.sanger.ac.uk) and B. napus miRNAs in the literature with fewer than three mismatches. There are 24 miRNA families for this group of conserved sequences found in model monocot and dicot species (Jones-Rhoades et al., 2006; Rajagopalan et al., 2006). All of these families were detected in the four libraries (Table 3) and 57 known miRNAs were obtained (Supplementary Table S2). For most of these conserved miRNAs, their precursor sequences could be retrieved from the NCBI database and their secondary structures, resembling the fold-back structure of miRNA precursor, could be obtained. Some of the miRNA families, such as miR156/157, miR158, miR165/166, miR167, and miR168, were highly expressed in the four libraries, whereas others had relatively low levels of expression. Some miRNAs were preferentially expressed in roots (e.g. miR319) and others were preferentially expressed in shoots (e.g. miR391).

Table 3. Abundance of conserved and non-conserved miRNA families from Cd-free and Cd-treated roots and shoots of B. napus

miRNA family R–Cd R+Cd S–Cd S+Cd Log2 
(R+Cd/R–Cd) Log2 
(S+Cd/S–Cd) Log2 
(S–Cd/R–Cd) Log2 
(S+Cd/R+Cd) 
Conserved miRNA 
156/157 774,283 846,332 3,717,697 2,089,876 –0.03 –0.92 2.32* 1.42* 
158 88,826 107,966 14,349 46,564 0.13 1.61* –2.58* –1.09* 
159 6676 2584 7648 2979 –1.52* –1.45* 0.25  0.32 
160 5023 5411 4497 3122 –0.05 –0.61 –0.11 –0.67 
161 218 314 97 599 0.37 2.54* –1.12* 1.05* 
162 1978 2154 9406 3181 –0.03 –1.65* 2.30* 0.68 
164 21,068 23,906 121,164 33,924 0.03 –1.92* 2.58* 0.62 
165/166 216,066 187,271 269,046 186,617 –0.36 –0.61 0.37 0.11 
167 1,910,348 2,003,033 4,010,133 2,266,764 –0.09 –0.91 1.12* 0.30 
168 174,898 219,716 601,579 478,276 0.17 –0.42 1.83* 1.24* 
169 21,256 23,023 13,945 9901 –0.04 –0.58 –0.56 –1.10* 
171 509 588 6273 3205 0.05 –1.06* 3.67* 2.57* 
172 5723 7653 11,749 17,034 0.26 0.45 1.09* 1.27* 
319 1453 1468 39 –0.14 –3.05* –5.17* –8.08* 
390 2990 4744 2822 1972 0.51 –0.60 –0.03 –1.15* 
391 495 513 13,579 8823 –0.10 –0.71 4.83* 4.22* 
393 83 111 231 338 0.27 0.46 1.53* 1.73* 
394 78 39 184 24 –1.15* –3.03* 1.29* –0.58 
395 68 62 78 41 –0.29 –1.01* 0.25 –0.48 
396 2066 1879 6906 4343 –0.29 –0.76 1.79* 1.33* 
397 3087 5702 1533 1390 0.73 –0.23 –0.96 –1.92* 
398 23 108 188 302 2.08* 0.60 3.08* 1.60* 
399 48 71 100 72 0.41 –0.56 1.11* 0.14 
408 9554 19,831 220,195 122,181 0.90 –0.94 4.58* 2.74* 
Non-conserved miRNA 
400 408 422 123 522 –0.11 2.00* –1.68* 0.43 
403 3580 3783 6430 7382 –0.07 0.11 0.90 1.08* 
824 3363 4259 741 1021 0.19 0.38 –2.13* –1.94* 
827 246 306 360 342 0.16 –0.16 0.60 0.28 
857 164 365 52 64 1.00* 0.21 –1.61* –2.39* 
858 28 –1.00 –3.31* 1.69 –0.62 
860 78 59 30 39 –0.56 0.29 –1.33* –0.48 
894 10,926 15,229 1389 1404 0.32 –0.07 –2.92* –3.32* 
1140 721 950 2358 1929 0.24 –0.38 1.76* 1.14* 
1863 41 69 41 43 0.60 –0.02 0.05 –0.56 
1885 569 531 161 563 –0.25 1.72* –1.77* 0.20 
2111 112 62 41 11 –1.01* –1.98* –1.40* –2.38* 
2911 1318 1439 308 200 –0.03 –0.71 –2.05* –2.73* 
miRNA family R–Cd R+Cd S–Cd S+Cd Log2 
(R+Cd/R–Cd) Log2 
(S+Cd/S–Cd) Log2 
(S–Cd/R–Cd) Log2 
(S+Cd/R+Cd) 
Conserved miRNA 
156/157 774,283 846,332 3,717,697 2,089,876 –0.03 –0.92 2.32* 1.42* 
158 88,826 107,966 14,349 46,564 0.13 1.61* –2.58* –1.09* 
159 6676 2584 7648 2979 –1.52* –1.45* 0.25  0.32 
160 5023 5411 4497 3122 –0.05 –0.61 –0.11 –0.67 
161 218 314 97 599 0.37 2.54* –1.12* 1.05* 
162 1978 2154 9406 3181 –0.03 –1.65* 2.30* 0.68 
164 21,068 23,906 121,164 33,924 0.03 –1.92* 2.58* 0.62 
165/166 216,066 187,271 269,046 186,617 –0.36 –0.61 0.37 0.11 
167 1,910,348 2,003,033 4,010,133 2,266,764 –0.09 –0.91 1.12* 0.30 
168 174,898 219,716 601,579 478,276 0.17 –0.42 1.83* 1.24* 
169 21,256 23,023 13,945 9901 –0.04 –0.58 –0.56 –1.10* 
171 509 588 6273 3205 0.05 –1.06* 3.67* 2.57* 
172 5723 7653 11,749 17,034 0.26 0.45 1.09* 1.27* 
319 1453 1468 39 –0.14 –3.05* –5.17* –8.08* 
390 2990 4744 2822 1972 0.51 –0.60 –0.03 –1.15* 
391 495 513 13,579 8823 –0.10 –0.71 4.83* 4.22* 
393 83 111 231 338 0.27 0.46 1.53* 1.73* 
394 78 39 184 24 –1.15* –3.03* 1.29* –0.58 
395 68 62 78 41 –0.29 –1.01* 0.25 –0.48 
396 2066 1879 6906 4343 –0.29 –0.76 1.79* 1.33* 
397 3087 5702 1533 1390 0.73 –0.23 –0.96 –1.92* 
398 23 108 188 302 2.08* 0.60 3.08* 1.60* 
399 48 71 100 72 0.41 –0.56 1.11* 0.14 
408 9554 19,831 220,195 122,181 0.90 –0.94 4.58* 2.74* 
Non-conserved miRNA 
400 408 422 123 522 –0.11 2.00* –1.68* 0.43 
403 3580 3783 6430 7382 –0.07 0.11 0.90 1.08* 
824 3363 4259 741 1021 0.19 0.38 –2.13* –1.94* 
827 246 306 360 342 0.16 –0.16 0.60 0.28 
857 164 365 52 64 1.00* 0.21 –1.61* –2.39* 
858 28 –1.00 –3.31* 1.69 –0.62 
860 78 59 30 39 –0.56 0.29 –1.33* –0.48 
894 10,926 15,229 1389 1404 0.32 –0.07 –2.92* –3.32* 
1140 721 950 2358 1929 0.24 –0.38 1.76* 1.14* 
1863 41 69 41 43 0.60 –0.02 0.05 –0.56 
1885 569 531 161 563 –0.25 1.72* –1.77* 0.20 
2111 112 62 41 11 –1.01* –1.98* –1.40* –2.38* 
2911 1318 1439 308 200 –0.03 –0.71 –2.05* –2.73* 

Values are number of reads. * indicates significant differences in expression between two treatments (P < 0.01 and |log2N| ≥ 1). R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Deep sequencing also detected 13 non-conserved miRNA families from B. napus (Table 3 and Supplementary Table S2). This group of miRNAs is conserved only in a few plant species. For instance, miR860 is conserved in Arabidopsis thaliana (Fahlgren et al., 2007; Moldovan et al., 2010) and Arabidopsis lyrata (Ma et al., 2010). Also, miR894 has been shown to exist only in Physcomitrella patens (Fattash et al., 2007). These miRNA families had a moderate or low abundance in the libraries. miR824, miR857, miR894, and miR2911 were preferentially expressed in roots, whereas miR1140 was preferentially expressed in shoots.

Identification of new miRNAs

To identify previously undiscovered miRNAs, a standard computation pipeline was applied based on the recently published criteria for plant microRNAs (Meyers et al., 2008). With this filter, 20–24-nt small RNA sequences were mapped to the B. napus EST database with no mismatch of nucleotides. All reads with low abundance (<10) were removed from the data set (Lister et al., 2009; Zhou et al., 2012). The data sets were also subjected to a query of the non-coding RNA sequences deposited in the GenBank and Rfam databases (Griffiths-Jones et al., 2008). Sequences matching rRNA, tRNA, snRNA, and snoRNA were removed. The consensus surrounding the regions of each sequence was retrieved and secondary structures were obtained (Zuker, 2003). All filtered small RNAs that could fold into a stem–loop structure were considered as miRNA candidates. Finally, 19 new loci belonging to eight conserved miRNA families and one non-conserved miRNA family were identified (Table 4 and Supplementary Table S3). These miRNAs were characterized by star strands (miRNA*) and have not been reported before. Additionally, 1731 miRNA homologues, exhibiting high similarity with miRNAs from other species, were identified using the criteria of no more than two nucleotide mismatches (Supplementary Table S4). However, these miRNAs had no B. napus ESTs or TC sequences to match and consequently their secondary structures could not be obtained.

Table 4. New miRNAs and their transcript abundance identified from Cd-free and Cd-treated roots and shoots of B. napus

miRNA Mature sequence (5'–3') R–Cd R+Cd S–Cd S+Cd Log2 (R+Cd/
R–Cd) Log2 (S+Cd/ 
S–Cd) Log2 (S–Cd/
R–Cd) Log2 (S+Cd/
R+Cd) Total miRNA* 
miR156g–l UGACAGAAGAGAGUGAGCAC 650,821 710,264 2,443,327 1,384,542 −0.03 −0.91 1.96* 1.08* 
miR156m UUGACAGAAGAAAGAGAGCAC 4517 5125 2845 98,985 0.03 5.03* −0.62 4.39* 
miR158a UUUCCAAAUGUAGACAAAGCA 47,104 58,696 11,996 42,611 0.16 1.74* −1.92* −0.34 
miR160b GCGUACAGAGUAGUCAAGCAUA 326 239 883 540 −0.60 −0.80 1.49* 1.30* 813 
miR160c UGCCUGGCUCCCUGUAUACCA 11 14 26 0.19 −1.79 1.29 −0.69 
miR167f–h UGAAGCUGCCAGCAUGAUCU 588 717 14,284 6090 0.13 −1.32* 4.65* 3.21* 
miR167i UGAAGCUGCCAGCAUGAUCUU 14,135 17,376 31,548 13,010 0.14 −1.36* 1.21* −0.30 15 
miR168c UCGCCUGGUGCAGGUCGGGAA 17 14 33 22 −0.43 −0.67 1.01 0.77 
miR172f GAAUCUUGAUGAUGCUGCAU 11 45 96 141 1.88* 0.47 3.18* 1.77* 
miR319c GAGCUUUCUUCGGUCCACUC 1111 1417 38 0.20 −3.75* −4.82* −8.76* 570 
miR319d UUGGACUGAAGGGAGCUCCUU 72 21 −1.93* −0.09 −6.12* −4.27* 
miR398b GGGUCGAUAUGAGAACACAUG 21 96 145 253 2.04* 0.72 2.84* 1.52* 28 
miR860a–b UCAAUACAUUGGACUACAUAU 78 59 30 39 −0.56 0.29 −1.33* −0.48 
miRNA Mature sequence (5'–3') R–Cd R+Cd S–Cd S+Cd Log2 (R+Cd/
R–Cd) Log2 (S+Cd/ 
S–Cd) Log2 (S–Cd/
R–Cd) Log2 (S+Cd/
R+Cd) Total miRNA* 
miR156g–l UGACAGAAGAGAGUGAGCAC 650,821 710,264 2,443,327 1,384,542 −0.03 −0.91 1.96* 1.08* 
miR156m UUGACAGAAGAAAGAGAGCAC 4517 5125 2845 98,985 0.03 5.03* −0.62 4.39* 
miR158a UUUCCAAAUGUAGACAAAGCA 47,104 58,696 11,996 42,611 0.16 1.74* −1.92* −0.34 
miR160b GCGUACAGAGUAGUCAAGCAUA 326 239 883 540 −0.60 −0.80 1.49* 1.30* 813 
miR160c UGCCUGGCUCCCUGUAUACCA 11 14 26 0.19 −1.79 1.29 −0.69 
miR167f–h UGAAGCUGCCAGCAUGAUCU 588 717 14,284 6090 0.13 −1.32* 4.65* 3.21* 
miR167i UGAAGCUGCCAGCAUGAUCUU 14,135 17,376 31,548 13,010 0.14 −1.36* 1.21* −0.30 15 
miR168c UCGCCUGGUGCAGGUCGGGAA 17 14 33 22 −0.43 −0.67 1.01 0.77 
miR172f GAAUCUUGAUGAUGCUGCAU 11 45 96 141 1.88* 0.47 3.18* 1.77* 
miR319c GAGCUUUCUUCGGUCCACUC 1111 1417 38 0.20 −3.75* −4.82* −8.76* 570 
miR319d UUGGACUGAAGGGAGCUCCUU 72 21 −1.93* −0.09 −6.12* −4.27* 
miR398b GGGUCGAUAUGAGAACACAUG 21 96 145 253 2.04* 0.72 2.84* 1.52* 28 
miR860a–b UCAAUACAUUGGACUACAUAU 78 59 30 39 −0.56 0.29 −1.33* −0.48 

Values are number of reads. * indicates significant differences in expression between pairs of libraries (P < 0.01 and |log2N| ≥ 1). R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Differential expression of miRNAs in response to cadmium

To identify the response of miRNAs to Cd, this study compared the abundance of miRNAs between any two libraries. To analyse differential expression of each miRNA family, reads were normalized on the basis of transcripts per million. Most miRNAs were differentially expressed in Cd-treated roots and shoots compared with the controls, but not all miRNA expression was significantly regulated by Cd (Table 3). In roots, there were eight miRNA families, whose expression were significantly regulated by Cd exposure (P < 0.01), including miR159, miR394, miR398, miR857, and miR2111 (Table 3) and miR172f, miR319d, and miR398b (Table 4). Of these, miR398, miR857, and miR172f were up-regulated by Cd exposure and the others were negatively regulated by Cd. In shoots, 13 miRNA families (miR158, miR159, miR161, miR162, miR164, miR171, miR319, miR394, miR395, miR400, miR858, miR1885, and miR2111) (Table 3) 
and five newly identified miRNAs (miR156m, miR158a, miR167f–h, miR167i, and miR319c) (Table 4) were found to be significantly regulated by Cd treatment (P < 0.01), of which four miRNA families (miR158, miR161, miR400, and miR1885) and two miRNA members (miR156m and miR158a) were up-regulated, and the others were down-regulated, by Cd exposure. In contrast, most miRNAs were found to be differentially expressed between roots and shoots under normal or Cd-stress conditions. Treatment with Cd could also result in altered expression between roots and shoots.

To confirm the expression of miRNAs identified by deep sequencing, 14 miRNAs with high and moderate sequencing counts were randomly selected for validation by RNA gel blotting. As shown in Fig. 2, all tested miRNAs were detected; only miR396 and miR400 showed very weak signals. Expression patterns were compared between RNA gel blotting and deep sequencing and most of the results were comparable. miR156 and miR403 were more abundantly expressed in shoots than in roots. In shoots, expression of miR158 was up-regulated by Cd exposure, whereas expression of miR390 was down-regulated by Cd exposure. In roots, both miR397 and miR408 were induced by the presence of Cd. However, expression pattern of miR167 using Northern blotting was not in agreement with that from deep sequencing.

Fig. 2.

Validation of 14 newly identified miRNAs from roots and shoots of B. napusexposed to Cd. Two-week-old seedlings (two true leaves) were exposed to 0, 40, or 80 µM Cd for 6, 24, or 48 h, as described in Materials and methods. Total RNA from each treatment was extracted, pooled, and determined by RNA gel blotting. R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Fig. 2.

Validation of 14 newly identified miRNAs from roots and shoots of B. napusexposed to Cd. Two-week-old seedlings (two true leaves) were exposed to 0, 40, or 80 µM Cd for 6, 24, or 48 h, as described in Materials and methods. Total RNA from each treatment was extracted, pooled, and determined by RNA gel blotting. R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Identification of miRNA targets

Identification of miRNA targets is a prerequisite to understand the functions of miRNAs. At the time of writing, only some dozens of miRNAs from B. napus have been reported (Wang et al., 2007; Xie et al., 2007; Pant et al., 2009; Huang et al., 2010). Also, very few miRNA targets have been experimentally characterized (Huang et al., 2010). To identify more targets in B. napus, the present study performed a genome-wide analysis of miRNA-cleaved mRNAs using a recently developed high-throughput degradome sequencing technology (Addo-Quaye et al., 2008; German et al., 2008). This approach emphasizes detection of cleavage products guided by miRNAs on a large scale and has been successfully used for characterizing hundreds of conserved and non-conserved miRNA targets from other plant species, e.g. rice (Li et al., 2010; Zhou et al., 2010), grapevine (Pantaleo et al., 2010), M. truncatula (Branscheid et al., 2011; Zhou et al., 2012), and soybean (Song et al., 2011).

This study sequenced 14,821,751–16,945,142 signatures for each of the four libraries (Table 1). After removal of low-quality reads, adaptor contaminants, and shorter (<19 nt) reads, a total of 13,054,929–15,418,988 clean reads, corresponding to 804,892–6,277,974 unique reads, were obtained. The distribution of the total and unique reads between any two libraries and their lengths are presented in Supplementary Figs. S3 and S4. Mapping of the unique sequences to the B. napus cDNA database generated 64,197, 65,710, 79,713 and 79,050 ESTs and TC sequences for the R–Cd, R+Cd, S–Cd, and S+Cd libraries, respectively (Table 1).

The sliced targets for conserved and non-conserved miRNAs were identified according to the CleaveLand pipeline (Addo-Quaye et al., 2009a). Abundance of the sequences was plotted on each transcript (Supplementary Figs. S5 and S6). The degraded transcripts could be grouped into three categories based on the relative abundance of the tags sequenced at the target sites (Addo-Quaye et al., 2008). Based on the criteria, category I species were the most abundant degradome tags, in which the expected site is cleaved by corresponding miRNAs; category II comprised degradome sequences with more than one raw read at the position, abundance at position less than the maximum but higher than the median for the transcript; and category III contained all of the other transcripts sliced by miRNAs. Apparently, category I targets always had much higher degradome tags and lower false rates of miRNA-guided cleavage. In total, 802 non-redundant targets of 37 (24 conserved and 13 non-conserved) miRNAs were obtained. There were 200, 537, and 65 targets in categories I, II, and III, respectively (Table 5 and Supplementary Tables S5 and S6). The distribution pattern is similar to recent reports in other plants (Li et al., 2010; Pantaleo et al., 2010; Zhou et al., 2010, 2012). For category I transcripts, they could also be present in category II or III. Taking the R–Cd library as an example, there were 12 and 16 miRNA targets in categories II and III that could be detected in category I in the other three libraries (Table 5).

Table 5. Summary of the miRNA target categories from Cd-free and Cd-treated roots and shoots of B. napus

Library  R–Cd  R+Cd  S–Cd  S+Cd  Total non-redundant targets 
Category II III II III II III II III  
36 12 16 65 18 116 32 108 38 200 
II  41 30  63 16  305 37  368 25 537 
III   12   17   25   21 65 
Total 36 53 58 65 81 41 116 337 65 108 406 48 802 
Library  R–Cd  R+Cd  S–Cd  S+Cd  Total non-redundant targets 
Category II III II III II III II III  
36 12 16 65 18 116 32 108 38 200 
II  41 30  63 16  305 37  368 25 537 
III   12   17   25   21 65 
Total 36 53 58 65 81 41 116 337 65 108 406 48 802 

Categories are defined according to Addo-Quaye et al. (2008). R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

The targets were differentially distributed in the four libraries. Shoots usually had more targets cleaved by miRNAs than roots. Also, more targets from category I were detected in Cd-treated roots than in Cd-free roots, but for shoots, more targets were found in the Cd-free library. Analysis of common and specific targets showed that the sliced targets were differentially present between any two libraries (Table 6). Apart from the common targets, there were more specific targets detected in Cd-exposed than in Cd-free libraries. This suggests that treatment with Cd intensified the cleavage of miRNA targets, resulting in the accumulation of sliced transcripts.

Table 6. Analysis of the miRNA targets between pairs of libraries of B. napus

 R–Cd vs. R+Cd S–Cd vs. S+Cd R–Cd vs. S–Cd R+Cd vs. S+Cd 
Common (I, II, III) 82 (43, 37, 2) 353 (126, 221, 6) 93 (44, 49, 0) 111 (67, 42, 2) 
Only in Cd-free library 66 166 55 75 
Only in Cd-treated library 104 209 426 451 
 R–Cd vs. R+Cd S–Cd vs. S+Cd R–Cd vs. S–Cd R+Cd vs. S+Cd 
Common (I, II, III) 82 (43, 37, 2) 353 (126, 221, 6) 93 (44, 49, 0) 111 (67, 42, 2) 
Only in Cd-free library 66 166 55 75 
Only in Cd-treated library 104 209 426 451 

R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Because targets belonging to category I usually have sites that are more accurately cleaved by miRNAs, this group of targets was analysed in more detail. As shown in Table 7 and Supplementary Fig. S5, of the 24 highly conserved miRNA families, 22 (except for miR391 and miR398) were identified to target 177 transcripts. Most of the miRNAs had multiple targets, except for miR161 and miR399 which had only one. miR156 had the highest number of targets with 28 transcripts, from which 23 transcripts encode different proteins. Also, there were 19 targets identified for miR167, of which 12 come from different gene families. By contrast, miR165, miR319, miR390, miR394, and miR395 had only two targets. Most of the targets for conserved miRNAs were conserved. miR395 targeted a plasma membrane sulphate transporter and an ATP sulphurylase, both of which have been well described previously (Kawashima et al., 2009; Liang et al., 2010). However, some of the conserved miRNAs may also target non-conserved or novel transcripts. For instance, a transcript encoding a malate synthase was identified as a new target for miR396. Phosphatase, a putative new target for miR394, was also identified in this study. Moreover, some transcripts targeted by conserved miRNAs are involved in plant response to environmental stresses, including those encoding for laccase (TC164751, miR397), NRAMP-type metal transporters (CD826328 and GT073274, miR167), and monothiol glutaredoxin (TC185396, miR164).

Table 7. Category I targets identified from any of the four degradomes from Cd-free and Cd-treated roots and 
shoots of B. napus

miRNA  Target genes  Score  Target category Target gene annotation  
   R–Cd R+Cd S–Cd S+Cd  
Conserved miRNA 
miR156 TC210178 Squamosa promoter-binding-like protein 2 
miR156 TC182990 Squamosa promoter-binding-like protein 2 
miR156 TC169034 1.5 no no Squamosa promoter-binding-like protein 3 
miR156 TC177533 no no Squamosa promoter-binding-like protein 3 
miR156 TC195915 no Squamosa promoter-binding-like protein 10 
miR156 TC200337 no Squamosa promoter-binding-like protein 10 
miR156 TC197337 no no II Squamosa promoter-binding-like protein 13 
miR156 ES997975 no no Squamosa promoter-binding-like protein 15 
miR156 TC213662 3.5 no no no Glutathione-γ-glutamylcysteinyl transferase 2 
miR156 TC204681 3.5 no no no 40S ribosomal protein Sa-1 
miR156 EV002651 no II no Probable pleiotropic drug resistance protein 5 
miR156 TC175179 no no no RING/U-box superfamily protein 
miR156 TC168211 3.5 no no II OST3/OST6 family protein 
miR156 TC174107 no no no Chromosome chr5 scaffold_2 
miR156 FG560749 3.5 no no no ATGSL03 (GLUCAN SYNTHASE-LIKE 3); 1,3-beta-glucan 
synthase/transferase 
miR156 TC171252 3.5 no II II Transcriptional regulator 
miR156 TC205146 II II II unknown protein 
miR156 TC168656 no no II SAE1-S9-protein 
miR156 TC194880 no no II GATA transcription factor 27 
miR156 FG576933 no no no Genomic DNA 
miR156 TC195666 3.5 no II no Serine/threonine-protein kinase Nek3 
miR156 ES904551 no no II Eukaryotic aspartyl protease family protein 
miR156 TC183712 3.5 no II Luminal-binding protein 2 precursor 
miR156 TC211628 3.5 no no no Unknown binding protein 
miR156 ES952034 3.5 no no Probable histone H2A.1 
miR156 TC185930 3.5 no no no Ferredoxin thioredoxin reductase 
miR156* CD817244 no no II DEAD-box ATP-dependent RNA helicase 3 
miR156* ES265305 no no no A subfamily of OB folds 
miR157 TC171779 no no no RING-H2 finger protein 
miR157 DY030585 3.5 no no no Chromosome undetermined scaffold_30 
miR157 TC165728 3.5 no no no Chromosome undetermined scaffold_30 
miR157 EE506890 no II no RSZp21 protein 
miR157 TC171167 3.5 no no no Expressed protein 
miR157 TC175876 3.5 no no no Expressed protein 
miR157 CD813575 3.5 no no no Chromosome undetermined scaffold_227 
miR157 ES907812 3.5 no no II Thioredoxin M-type 3 
miR157 EL625648 3.5 no no II Uncharacterized protein 
miR158 TC181466 3.5 no no II DEAD-box ATP-dependent RNA helicase 6 
miR158 TC183657 3.5 no no II DEAD-box ATP-dependent RNA helicase 6 
miR159 TC190748 2.5 no Similarity to NAM 
miR159 EV087133 2.5 MYB65 
miR159 CX195998 3.5 no no Genomic DNA 
miR159 DW999433 3.5 no no YDL167c ARP1 singleton partial 
miR159 FG567250 3.5 no no ABC transporter 
miR159 GR446300 3.5 no no Chromosome chr17 scaffold_12 
miR159 TC186567 no II no Chromosome chr18 scaffold_1 
miR159 DY030757 3.5 no no III Chromosome chr12 scaffold_47 
miR160 TC193317 Auxin response factor 16 
miR160 GT084423 3.5 no no no Unknown 
miR160 TC201448 0.5 no Auxin response factor 17 
miR160* TC165518 0.5 Auxin response factor 17 
miR160* TC183439 no no no Expressed protein 
miR160* TC188717 no no no Chromosome chr8 scaffold_23 
miR161 FG573058 2.5 no no no Pentatricopeptide repeat-containing protein 
miR162 EE408149 no no no RING/U-boxdomain-containing protein 
miR162* TC203508 no III II Cytochrome P450-like protein 
miR164 TC168009 no Protein CUP-SHAPED COTYLEDON 1 
miR164 TC186868 1.5 no no NAM (No apical meristem)-like protein 
miR164 TC211305 no no NAC domain-containing protein 21/22 
miR164 TC185396 no Monothiol glutaredoxin-S12 
miR164 TC203633 no II no Sorting nexin 1 
miR164 TC163443 III III no Carbohydrate-binding X8 domain-containing protein 
miR164 TC210593 no no no Chalcone synthase 
miR164 EV183736 no no no Phosphate starvation response regulator 1 
miR164 EE438989 no no II Unknown 
miR164 TC186668 no no Unknown 
miR164 ES914070 3.5 no no II Unknown 
miR165 EV102172 2.5 no no no Transcriptional regulator 
miR165 EE562244 3.5 Class III HD-Zip protein 1 
miR166 TC167613 II Homeodomain-leucine zipper protein  
miR166 TC192563 no II HD-zip protein 
miR166 TC162295 no no no Development and lipid accumulation within the tapetum  
miR166 TC166514 no no no Development and lipid accumulation within the tapetum  
miR166 TC189133 no no no Development and lipid accumulation within the tapetum  
miR166 TC196490 no no II Development and lipid accumulation within the tapetum  
miR166 ES911720 no no no At1g10410/F14N23_31 Protein of unknown 
miR166 ES963909 no no no Unknown 
miR166 EE424026 II II II Peptide chain release factor subunit 1–3 
miR166 EV172600 no II Unknown protein 
miR166 TC181758 no II II Unknown protein 
miR166* EV089744 3.5 no no II Uncharacterized protein 
miR167 TC163509 3.5 no II II Auxin response factor 8 
miR167 TC179576 3.5 II II Auxin response factor 8 
miR167 TC212888 3.5 II II Auxin response factor 8 
miR167 TC183925 3.5 no ARF6 
miR167 TC200079 3.5 no ARF6 
miR167 TC208397 3.5 no ARF6 
miR167 TC188972 3.5 no no Putative U2 snRNP auxiliary factor small subunit 
miR167 TC205461 no no no Auxin efflux carrier component 1 
miR167 FG560824 no no Probable WRKY transcription factor 21 
miR167 TC164117 no no Probable WRKY transcription factor 21 
miR167 EE562388 II no no Uncharacterized protein 
miR167 TC196372 no no no Unknown protein 
miR167 TC204819 no no no Invertase-like protein 
miR167 CD826328 no no no Metal transporter Nramp1 
miR167 GT073274 no no no Metal transporter Nramp1 
miR167 EL623555 no no no F-box only protein 6 
miR167 GT076997 3.5 no no no Uncharacterized protein 
miR167 TC163902 3.5 II no II Peptidase M1 family protein 
miR167 TC178278 3.5 II no II Peptidase M1 family protein 
miR168 TC193360 3.5 no no no S-adenosyl-l-methionine-dependent methyltransferases superfamily protein 
miR168 TC204355 II no II Hypothetical protein 
miR168 TC196158 3.5 no Involved in cation homeostasis and transport  
miR168 ES952129 no no no Unknown 
miR168 TC161728 III III III NAC-domain protein 5–7 
miR168 TC207530 3.5 no no II Chromosome undetermined SCAF10321 
miR169 TC161690 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC209850 no CCAAT-binding factor B subunit homologue 
miR169 TC183411 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC204571 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC184180 no no no Chromosome chr11 scaffold_13 
miR169 TC202311 no no no Chromosome chr11 scaffold_13 
miR169 EE543166 1.5 no no Uncharacterized protein 
miR169 EV064177 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC212312 1.5 no no II Isoform 2 of Q8SQD7 
miR169 TC169941 2.5 no no Nuclear transcription factor Y subunit A-1 
miR169 ES991856 no no no Serine/threonine protein phosphatase 7 inactive homologue 
miR169* TC167595 no II II Ubiquinol-cytochrome C chaperone family protein 
miR169* TC188279 no II II Ubiquinol-cytochrome C chaperone family protein 
miR171 FG563769 no no no Nucleoside diphosphate kinase family protein 
miR171 TC191279 no no Ap2 SCARECROW-like protein 
miR172 ES922267 no no no Chromosome chr18 scaffold_1 
miR172 TC184340 0.5 no no AP2-like ethylene-responsive transcription factor 
miR172 DY020927 0.5 no AP2-like ethylene-responsive transcription factor 
miR172 TC200318 0.5 no II II AP2-like ethylene-responsive transcription factor 
miR172 ES962400 1.5 no III Ethylene-responsive transcription factor 
miR172 TC161595 3.5 no no II Shaggy-related protein kinase theta 
miR172 TC192206 1.5 no II Ethylene-responsive transcription factor 
miR172 TC195815 0.5 no no AP2-like transcriptional factor 
miR172 TC196185 0.5 no no Floral homeotic protein APETALA 2 
miR172 TC205794 0.5 no no AP2-like transcriptional factor 
miR172 TC209791 0.5 no no Floral homeotic protein APETALA 2 
miR172 DY012557 no no II Eukaryotic translation initiation factor 3 subunit 
E- interacting protein 
miR172* TC177968 2.5 no no II Unknown protein; CONTAINS InterPro DOMAIN 
miR172* TC183087 no no no Serine/arginine-rich protein 
miR319 TC166304 2.5 II TCP family transcription factor 
miR319 TC178420 2.5 II TCP family transcription factor 
miR390 TC164858 II II II Encodes a trans-acting siRNA (tasi-RNA) 
miR390 TC175812 3.5 no no no Rhomboid family  
miR393 EV007466 II Protein AUXIN SIGNALING F-BOX 3 
miR393 EV038237 Protein AUXIN SIGNALING F-BOX 3 
miR393 TC175423 no III Protein AUXIN SIGNALING F-BOX 3 
miR393 TC184499 II Protein AUXIN SIGNALING F-BOX 3 
miR393 TC188384 II Protein AUXIN SIGNALING F-BOX 3 
miR393 TC175098 2.5 no no Protein TRANSPORT INHIBITOR RESPONSE 1 
miR393 TC180163 2.5 no no Protein TRANSPORT INHIBITOR RESPONSE 1 
miR393 TC176250 no no Similarity to DNA-binding protein 
miR393 TC181533 2.5 no II GRR1-like protein 1 
miR394 TC197402 no no II F-box only protein 6 
miR394 GR443433 no no no Protein phosphatase 2C-like protein 
miR395 TC167317 no no II ATP sulphurylase precursor 
miR395 TC196344 1.5 no no Plasma membrane sulphate transporter 
miR396 EE557600 no no Transcription activator 
miR396 ES980066 3.5 no no no Uncharacterized protein 
miR396 FG570467 no no BHLH transcription factor like protein 
miR396 ES923674 2.5 no no BHLH transcription factor like protein 
miR396 GT083908 1.5 no no ORF1a polyprotein Gill-associated virus 
miR396 TC171496 2.5 no no Emb|CAB41081.1 
miR396 TC177516 2.5 no no III Hypothetical protein 
miR396 TC193012 no no II Chromosome chr19 scaffold_66 
miR396 TC197898 3.5 no no no Malate synthase 
miR396 TC174358 no no II Ulp1 protease family protein 
miR396 TC187395 2.5 no no no Growth regulating factor 
miR396* TC205898 3.5 no no II Transmembrane protein-related 
miR397 TC164751 1.5 no II II Laccase-4 precursor 
miR397 FG562711 no no II Chromosome chr7 scaffold_42 
miR397 TC173787 no no II Chromosome chr7 scaffold_42 
miR397 EE553789 3.5 no no no Replication protein 
miR399 TC205260 no no no Unknown 
miR408 ES912459 3.5 no II Uclacyanin-2 precursor 
miR408 TC163049 3.5 no II Uclacyanin-2 precursor 
miR408 TC165443 no no Ascorbate oxidase 
miR408* CX279037 III no no Chromosome undetermined scaffold_225 
miR408* CX279965 III no no Chromosome undetermined scaffold_225 
miR408* ES916657 III no no Chromosome undetermined scaffold_225 
miR408* EV109513 III no no Chromosome undetermined scaffold_225 
miR408* TC181273 III no no Chromosome undetermined scaffold_225 
Non-conserved miRNA 
miR400 CD815994 no no no Chromosome undetermined scaffold_621 
miR400 EE419922 no no II Similarity to salt-inducible protein 
miR403 TC186062 III Putative argonaute protein  
miR403 TC194490 no Putative argonaute protein  
miR403 TC207886 III Putative argonaute protein  
miR414 CD833259 II III U3 small nucleolar RNA-associated protein 18  
miR414 CD841236 II II Expressed protein 
miR414 EV022841 II Ubiquitin carrier protein 
miR414 EG021300 II Genomic DNA 
miR824 CX281097 0.5 no III MADS-box transcription factor 
miR824 TC199394 0.5 III MADS-box transcription factor 
miR824* TC189300 no II no Uncharacterized protein 
miR857 GR455872 3.5 no no no Predicted GPI-anchored protein 
miR858 EE431428 no no no Uncharacterized protein 
miR858 TC166213 2.5 III no II Uncharacterized protein 
miR858 TC193922 2.5 no III Uncharacterized protein 
miR860 TC188635 III II II Enolase 
miR860 EL626463 no no II 40S ribosomal protein S11–3 
miR860 ES953206 III II II 40S ribosomal protein S11–3 
miR860 TC165958 III II II 40S ribosomal protein S11–3 
miR860 TC168756 III II II 40S ribosomal protein S11–3 
miR860 TC194666 III II II 40S ribosomal protein S11–3 
miR860 TC204936 III II II 40S ribosomal protein S11–3 
miRNA  Target genes  Score  Target category Target gene annotation  
   R–Cd R+Cd S–Cd S+Cd  
Conserved miRNA 
miR156 TC210178 Squamosa promoter-binding-like protein 2 
miR156 TC182990 Squamosa promoter-binding-like protein 2 
miR156 TC169034 1.5 no no Squamosa promoter-binding-like protein 3 
miR156 TC177533 no no Squamosa promoter-binding-like protein 3 
miR156 TC195915 no Squamosa promoter-binding-like protein 10 
miR156 TC200337 no Squamosa promoter-binding-like protein 10 
miR156 TC197337 no no II Squamosa promoter-binding-like protein 13 
miR156 ES997975 no no Squamosa promoter-binding-like protein 15 
miR156 TC213662 3.5 no no no Glutathione-γ-glutamylcysteinyl transferase 2 
miR156 TC204681 3.5 no no no 40S ribosomal protein Sa-1 
miR156 EV002651 no II no Probable pleiotropic drug resistance protein 5 
miR156 TC175179 no no no RING/U-box superfamily protein 
miR156 TC168211 3.5 no no II OST3/OST6 family protein 
miR156 TC174107 no no no Chromosome chr5 scaffold_2 
miR156 FG560749 3.5 no no no ATGSL03 (GLUCAN SYNTHASE-LIKE 3); 1,3-beta-glucan 
synthase/transferase 
miR156 TC171252 3.5 no II II Transcriptional regulator 
miR156 TC205146 II II II unknown protein 
miR156 TC168656 no no II SAE1-S9-protein 
miR156 TC194880 no no II GATA transcription factor 27 
miR156 FG576933 no no no Genomic DNA 
miR156 TC195666 3.5 no II no Serine/threonine-protein kinase Nek3 
miR156 ES904551 no no II Eukaryotic aspartyl protease family protein 
miR156 TC183712 3.5 no II Luminal-binding protein 2 precursor 
miR156 TC211628 3.5 no no no Unknown binding protein 
miR156 ES952034 3.5 no no Probable histone H2A.1 
miR156 TC185930 3.5 no no no Ferredoxin thioredoxin reductase 
miR156* CD817244 no no II DEAD-box ATP-dependent RNA helicase 3 
miR156* ES265305 no no no A subfamily of OB folds 
miR157 TC171779 no no no RING-H2 finger protein 
miR157 DY030585 3.5 no no no Chromosome undetermined scaffold_30 
miR157 TC165728 3.5 no no no Chromosome undetermined scaffold_30 
miR157 EE506890 no II no RSZp21 protein 
miR157 TC171167 3.5 no no no Expressed protein 
miR157 TC175876 3.5 no no no Expressed protein 
miR157 CD813575 3.5 no no no Chromosome undetermined scaffold_227 
miR157 ES907812 3.5 no no II Thioredoxin M-type 3 
miR157 EL625648 3.5 no no II Uncharacterized protein 
miR158 TC181466 3.5 no no II DEAD-box ATP-dependent RNA helicase 6 
miR158 TC183657 3.5 no no II DEAD-box ATP-dependent RNA helicase 6 
miR159 TC190748 2.5 no Similarity to NAM 
miR159 EV087133 2.5 MYB65 
miR159 CX195998 3.5 no no Genomic DNA 
miR159 DW999433 3.5 no no YDL167c ARP1 singleton partial 
miR159 FG567250 3.5 no no ABC transporter 
miR159 GR446300 3.5 no no Chromosome chr17 scaffold_12 
miR159 TC186567 no II no Chromosome chr18 scaffold_1 
miR159 DY030757 3.5 no no III Chromosome chr12 scaffold_47 
miR160 TC193317 Auxin response factor 16 
miR160 GT084423 3.5 no no no Unknown 
miR160 TC201448 0.5 no Auxin response factor 17 
miR160* TC165518 0.5 Auxin response factor 17 
miR160* TC183439 no no no Expressed protein 
miR160* TC188717 no no no Chromosome chr8 scaffold_23 
miR161 FG573058 2.5 no no no Pentatricopeptide repeat-containing protein 
miR162 EE408149 no no no RING/U-boxdomain-containing protein 
miR162* TC203508 no III II Cytochrome P450-like protein 
miR164 TC168009 no Protein CUP-SHAPED COTYLEDON 1 
miR164 TC186868 1.5 no no NAM (No apical meristem)-like protein 
miR164 TC211305 no no NAC domain-containing protein 21/22 
miR164 TC185396 no Monothiol glutaredoxin-S12 
miR164 TC203633 no II no Sorting nexin 1 
miR164 TC163443 III III no Carbohydrate-binding X8 domain-containing protein 
miR164 TC210593 no no no Chalcone synthase 
miR164 EV183736 no no no Phosphate starvation response regulator 1 
miR164 EE438989 no no II Unknown 
miR164 TC186668 no no Unknown 
miR164 ES914070 3.5 no no II Unknown 
miR165 EV102172 2.5 no no no Transcriptional regulator 
miR165 EE562244 3.5 Class III HD-Zip protein 1 
miR166 TC167613 II Homeodomain-leucine zipper protein  
miR166 TC192563 no II HD-zip protein 
miR166 TC162295 no no no Development and lipid accumulation within the tapetum  
miR166 TC166514 no no no Development and lipid accumulation within the tapetum  
miR166 TC189133 no no no Development and lipid accumulation within the tapetum  
miR166 TC196490 no no II Development and lipid accumulation within the tapetum  
miR166 ES911720 no no no At1g10410/F14N23_31 Protein of unknown 
miR166 ES963909 no no no Unknown 
miR166 EE424026 II II II Peptide chain release factor subunit 1–3 
miR166 EV172600 no II Unknown protein 
miR166 TC181758 no II II Unknown protein 
miR166* EV089744 3.5 no no II Uncharacterized protein 
miR167 TC163509 3.5 no II II Auxin response factor 8 
miR167 TC179576 3.5 II II Auxin response factor 8 
miR167 TC212888 3.5 II II Auxin response factor 8 
miR167 TC183925 3.5 no ARF6 
miR167 TC200079 3.5 no ARF6 
miR167 TC208397 3.5 no ARF6 
miR167 TC188972 3.5 no no Putative U2 snRNP auxiliary factor small subunit 
miR167 TC205461 no no no Auxin efflux carrier component 1 
miR167 FG560824 no no Probable WRKY transcription factor 21 
miR167 TC164117 no no Probable WRKY transcription factor 21 
miR167 EE562388 II no no Uncharacterized protein 
miR167 TC196372 no no no Unknown protein 
miR167 TC204819 no no no Invertase-like protein 
miR167 CD826328 no no no Metal transporter Nramp1 
miR167 GT073274 no no no Metal transporter Nramp1 
miR167 EL623555 no no no F-box only protein 6 
miR167 GT076997 3.5 no no no Uncharacterized protein 
miR167 TC163902 3.5 II no II Peptidase M1 family protein 
miR167 TC178278 3.5 II no II Peptidase M1 family protein 
miR168 TC193360 3.5 no no no S-adenosyl-l-methionine-dependent methyltransferases superfamily protein 
miR168 TC204355 II no II Hypothetical protein 
miR168 TC196158 3.5 no Involved in cation homeostasis and transport  
miR168 ES952129 no no no Unknown 
miR168 TC161728 III III III NAC-domain protein 5–7 
miR168 TC207530 3.5 no no II Chromosome undetermined SCAF10321 
miR169 TC161690 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC209850 no CCAAT-binding factor B subunit homologue 
miR169 TC183411 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC204571 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC184180 no no no Chromosome chr11 scaffold_13 
miR169 TC202311 no no no Chromosome chr11 scaffold_13 
miR169 EE543166 1.5 no no Uncharacterized protein 
miR169 EV064177 2.5 no CCAAT-binding factor B subunit homologue 
miR169 TC212312 1.5 no no II Isoform 2 of Q8SQD7 
miR169 TC169941 2.5 no no Nuclear transcription factor Y subunit A-1 
miR169 ES991856 no no no Serine/threonine protein phosphatase 7 inactive homologue 
miR169* TC167595 no II II Ubiquinol-cytochrome C chaperone family protein 
miR169* TC188279 no II II Ubiquinol-cytochrome C chaperone family protein 
miR171 FG563769 no no no Nucleoside diphosphate kinase family protein 
miR171 TC191279 no no Ap2 SCARECROW-like protein 
miR172 ES922267 no no no Chromosome chr18 scaffold_1 
miR172 TC184340 0.5 no no AP2-like ethylene-responsive transcription factor 
miR172 DY020927 0.5 no AP2-like ethylene-responsive transcription factor 
miR172 TC200318 0.5 no II II AP2-like ethylene-responsive transcription factor 
miR172 ES962400 1.5 no III Ethylene-responsive transcription factor 
miR172 TC161595 3.5 no no II Shaggy-related protein kinase theta 
miR172 TC192206 1.5 no II Ethylene-responsive transcription factor 
miR172 TC195815 0.5 no no AP2-like transcriptional factor 
miR172 TC196185 0.5 no no Floral homeotic protein APETALA 2 
miR172 TC205794 0.5 no no AP2-like transcriptional factor 
miR172 TC209791 0.5 no no Floral homeotic protein APETALA 2 
miR172 DY012557 no no II Eukaryotic translation initiation factor 3 subunit 
E- interacting protein 
miR172* TC177968 2.5 no no II Unknown protein; CONTAINS InterPro DOMAIN 
miR172* TC183087 no no no Serine/arginine-rich protein 
miR319 TC166304 2.5 II TCP family transcription factor 
miR319 TC178420 2.5 II TCP family transcription factor 
miR390 TC164858 II II II Encodes a trans-acting siRNA (tasi-RNA) 
miR390 TC175812 3.5 no no no Rhomboid family  
miR393 EV007466 II Protein AUXIN SIGNALING F-BOX 3 
miR393 EV038237 Protein AUXIN SIGNALING F-BOX 3 
miR393 TC175423 no III Protein AUXIN SIGNALING F-BOX 3 
miR393 TC184499 II Protein AUXIN SIGNALING F-BOX 3 
miR393 TC188384 II Protein AUXIN SIGNALING F-BOX 3 
miR393 TC175098 2.5 no no Protein TRANSPORT INHIBITOR RESPONSE 1 
miR393 TC180163 2.5 no no Protein TRANSPORT INHIBITOR RESPONSE 1 
miR393 TC176250 no no Similarity to DNA-binding protein 
miR393 TC181533 2.5 no II GRR1-like protein 1 
miR394 TC197402 no no II F-box only protein 6 
miR394 GR443433 no no no Protein phosphatase 2C-like protein 
miR395 TC167317 no no II ATP sulphurylase precursor 
miR395 TC196344 1.5 no no Plasma membrane sulphate transporter 
miR396 EE557600 no no Transcription activator 
miR396 ES980066 3.5 no no no Uncharacterized protein 
miR396 FG570467 no no BHLH transcription factor like protein 
miR396 ES923674 2.5 no no BHLH transcription factor like protein 
miR396 GT083908 1.5 no no ORF1a polyprotein Gill-associated virus 
miR396 TC171496 2.5 no no Emb|CAB41081.1 
miR396 TC177516 2.5 no no III Hypothetical protein 
miR396 TC193012 no no II Chromosome chr19 scaffold_66 
miR396 TC197898 3.5 no no no Malate synthase 
miR396 TC174358 no no II Ulp1 protease family protein 
miR396 TC187395 2.5 no no no Growth regulating factor 
miR396* TC205898 3.5 no no II Transmembrane protein-related 
miR397 TC164751 1.5 no II II Laccase-4 precursor 
miR397 FG562711 no no II Chromosome chr7 scaffold_42 
miR397 TC173787 no no II Chromosome chr7 scaffold_42 
miR397 EE553789 3.5 no no no Replication protein 
miR399 TC205260 no no no Unknown 
miR408 ES912459 3.5 no II Uclacyanin-2 precursor 
miR408 TC163049 3.5 no II Uclacyanin-2 precursor 
miR408 TC165443 no no Ascorbate oxidase 
miR408* CX279037 III no no Chromosome undetermined scaffold_225 
miR408* CX279965 III no no Chromosome undetermined scaffold_225 
miR408* ES916657 III no no Chromosome undetermined scaffold_225 
miR408* EV109513 III no no Chromosome undetermined scaffold_225 
miR408* TC181273 III no no Chromosome undetermined scaffold_225 
Non-conserved miRNA 
miR400 CD815994 no no no Chromosome undetermined scaffold_621 
miR400 EE419922 no no II Similarity to salt-inducible protein 
miR403 TC186062 III Putative argonaute protein  
miR403 TC194490 no Putative argonaute protein  
miR403 TC207886 III Putative argonaute protein  
miR414 CD833259 II III U3 small nucleolar RNA-associated protein 18  
miR414 CD841236 II II Expressed protein 
miR414 EV022841 II Ubiquitin carrier protein 
miR414 EG021300 II Genomic DNA 
miR824 CX281097 0.5 no III MADS-box transcription factor 
miR824 TC199394 0.5 III MADS-box transcription factor 
miR824* TC189300 no II no Uncharacterized protein 
miR857 GR455872 3.5 no no no Predicted GPI-anchored protein 
miR858 EE431428 no no no Uncharacterized protein 
miR858 TC166213 2.5 III no II Uncharacterized protein 
miR858 TC193922 2.5 no III Uncharacterized protein 
miR860 TC188635 III II II Enolase 
miR860 EL626463 no no II 40S ribosomal protein S11–3 
miR860 ES953206 III II II 40S ribosomal protein S11–3 
miR860 TC165958 III II II 40S ribosomal protein S11–3 
miR860 TC168756 III II II 40S ribosomal protein S11–3 
miR860 TC194666 III II II 40S ribosomal protein S11–3 
miR860 TC204936 III II II 40S ribosomal protein S11–3 

Categories are defined according to Addo-Quaye et al. (2008). no, No signature at the expected site for that transcript. * indicates the target genes identified from miRNA* in this study. R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Identification of target mRNAs for non-conserved miRNAs

There were 23 category I targets identified for seven non-conserved miRNA families (Table 7). The target distribution and abundance varied from one library to another (Supplementary Table S5), suggesting that cleavage by miRNAs could be mediated by metal stress. miRNAs in category I targeted genes that are involved in diverse biological functions. In addition, some miRNA targets were identified as environmentally responsive genes. Apart from the conserved targets, some new targets were identified. For instance, miR400 targeted a transcript encoding for a putative salt-inducible protein; miR408 targeted an ascorbate oxidase; and miR860 targeted an enolase. These targets are closely associated with plant tolerance to environmental stresses (Cho et al., 2006; Ameline-Torregrosa et al., 2008; Zörb et al., 2010). Additionally, one target for miR414 was identified to encode for an ubiquitin carrier protein. However, most of the detected transcripts have not been functionally annotated. The non-conserved miRNAs usually had relatively less targeted transcripts than the conserved miRNAs.

Analysis of pre-miRNA degradome patterns

The plant homologue of Dicer or Dicer-like 1 (DCL1) cleaves both primary miRNA transcripts (pri-miRNAs) and miRNA precursors (pre-miRNAs) in the nucleus (Kim et al., 2010). Similarly to AGO-catalysed slicing, the remnants with 5'-monophosphate of pri-miRNAs and pre-miRNAs by DCL1 dicing may be identified by parallel analysis of RNA ends (PARE) or degradome sequencing (German et al., 2008; Addo-Quaye et al., 2009b; Li et al., 2010). A total of 27,296, 21,554, 5286, and 7125 degradome signatures were perfectly mapped to 38, 49, 69, and 79 (conserved and non-conserved) pre-miRNAs in the R–Cd, R+Cd, S–Cd, and S+Cd libraries, respectively (Table 1). In all, 82 of 94 (87.23%) unique pre-miRNAs of B. napus identified from this study had one or more mapping degradome reads. The abundance of degradome signatures corresponding to pre-miRNAs at the four typical sites, the starts and ends of miRNA and miRNA*, was frequently higher than that at other sites, suggesting that DCL1 processes the primary miRNA transcripts precisely (Supplementary Fig. S7). There were 64 unique pre-miRNAs, including 15 of 19 newly identified pre-miRNAs with degradome signatures at the starts/ends of miRNA/miRNA*, corresponding to 26, 17, 52, and 55 in the R–Cd, R+Cd, S–Cd, and S+Cd libraries, respectively (Table 8, Supplementary Tables S3 and S7 and Supplementary Fig. S7). Pre-miRNA degradome patterns can distinguish pri-miRNA transcripts from siRNA-generating transcripts (Li et al., 2010). The present analysis demonstrates that miRNAs that are generated from the 64 precursors are bona fide miRNAs. Of the 64 unique pre-miRNAs, 59 (92.2%) had degradome signatures at the miRNA start, which was higher than those at the miRNA end (19), the miRNA* start (21), and the miRNA* end (11) (Table 8). These results indicate that the 5' remnants cleaved by DCL1 at the miRNA start are usually stable and beneficial for the generation of miRNA mature sequences.

Table 8. Number of degradome reads mapped to miRNA precursors with cleavage at the expected sites of start/end of miRNA/miRNA* in Cd-free and Cd-treated roots and shoots of B. napus

Precursors with cleavage R–Cd R+Cd S–Cd S+Cd Non-redundant precursors 
At miRNA start 24 10 51 45 59 
At miRNA end 15 19 
At miRNA* start 19 19 21 
At miRNA* end 11 
Non-redundant precursors 26 17 55 52 64 
Precursors with cleavage R–Cd R+Cd S–Cd S+Cd Non-redundant precursors 
At miRNA start 24 10 51 45 59 
At miRNA end 15 19 
At miRNA* start 19 19 21 
At miRNA* end 11 
Non-redundant precursors 26 17 55 52 64 

R–Cd, Cd-free roots; R+Cd, Cd-treated roots; S–Cd, Cd-free shoots; S+Cd, Cd-treated shoots.

Discussion

As post-transcriptional regulators, miRNAs have been found in all eukaryotic plants and are involved in response to various environmental stresses (Zhang et al., 2006; Khraiwesh et al., 2012). To identify more miRNAs and those in response to heavy metals from B. napus, high-throughput sequencing was performed. This study identified 84 miRNAs (including new members of miRNAs) and 1731 miRNA homologues from B. napus. Of these, 75 were identified as conserved. This group of miRNAs shares several common features with those from other plant species. First, the conserved miRNAs usually showed higher expression abundance. Taking the Cd-free root and shoot libraries as an example, the average read counts for the conserved miRNA families were 135,284 and 376,393, respectively, whereas those for non-conserved miRNA families were 1657 and 928, respectively (Table 3). Second, the conserved miRNAs had more family members than the non-conserved miRNAs. The average number of family members for the conserved miRNAs was 3.13, whereas for the non-conserved miRNAs was 1.8 (Supplementary Tables S2 and S3). Third, more targets (e.g. category I) were identified for the conserved miRNAs than for the non-conserved miRNAs (Table 7). Also, most targets for conserved miRNAs were associated with developmental processes and transcription regulation, and less were associated with response to environmental stress and signal transduction. These results are consistent with previous reports in A. thaliana, M. truncaula, and other plant species (Rajagopalan et al., 2006; Fahlgren et al., 2007; Lenz et al., 2011; Chen et al., 2012; Zhou et al., 2012).

In addition to identifying small RNAs, the high-throughput sequencing also provides a basis to estimate expression levels of B. napus miRNAs. Identification of millions of sequences allowed the number of reads to be estimated and the miRNA abundances compared between any two libraries. The abundances of the identified miRNAs varied from one library to another. Transcript levels of conserved and non-conserved miRNA families were differentially regulated by Cd exposure (Table 3). Compared with miRNAs in roots, more miRNAs in shoots were significantly regulated by Cd exposure. This suggests that more miRNAs in shoots would be involved in plant response to Cd. This study also found that, under normal conditions, most of the miRNA families (70.27%, 26/37) were differentially expressed in roots and shoots (Table 3). Under Cd stress, the patterns of miRNA expression in shoots and roots were altered. For instance, miR162, miR164, and miR860 showed significant differences in levels of expression in roots and shoots under normal conditions whereas their expression levels were not significantly different under Cd stress. The contrasting situation (i.e. differences in expression between root and shoots with Cd exposure) was observed for miR169, miR390, miR397, and miR403, suggesting that regulation of miRNA biogenesis is most likely to be altered by heavy metals.

In B. napus, most miRNA targets have been predicted, but only a few of them have been identified using the 5'-RACE method (Huang et al., 2010). To accelerate the identification of miRNA targets in B. napus, this study carried out a genome-wide analysis of the degradome and identified numerous target transcripts for conserved and non-conserved miRNAs. For all miRNAs, 802 non-redundant targets were identified. There were 200, 537, and 65 targets that could be grouped to categories I, II, and III, respectively. Importantly, the 200 targets belonging to category I are the most close to the authentic transcripts sliced by miRNAs (Addo-Quaye et al., 2009a). Most are conserved, including transcripts encoding for transcription factors, proteins for development processes, and intermediates in hormone-dependent pathways, all of which are found in other plant species (Addo-Quaye et al., 2009b; Li et al., 2010; Pantaleo et al., 2010; Zhou et al., 2010, 2012; Song et al., 2011; Zheng et al., 2012; Zhang et al., 2012). Unexpectedly, some new transcripts involved in plant response to heavy metals were identified for the conserved miRNAs. These miRNAs target genes encoding critical enzymes or proteins for Cd tolerance (Table 7). miR156 targets a transcript encoding a glutathione-γ-glutamylcysteinyl” transferase (GGT). GGT, along with phytochelatin synthase, constitutes a major mechanism to detoxify heavy metals (e.g. Cd and Hg) in plant cells by chelating them with phytochelatins or tripeptide glutathione (c-Glu–Cys–Gly) to transfer phytochelatin–metal complexes into vacuoles (Cobbett, 2000). The miRNA-mediated GGT gene expression is probably involved in plant tolerance to toxic heavy metals. Glutaredoxins (Grxs) are thiol-disulphide oxidoreductases present in most prokaryotic and eukaryotic organisms (Fernandes and Holmgren, 2004). Recent studies show that monothiol glutaredoxin is able to regulate oxidative stress in higher plants (Cheng et al., 2011). The present study also found a target for miR164 encoding a monothiol glutaredoxin, suggesting that miR164-guided cleavage of monothiol glutaredoxin could be involved in mediation of plant response to Cd-induced oxidative stress. In addition, an ABC transporter and two natural resistance-associated macrophage proteins (NRAMP)-type metal transporters were identified for miR159 and miR167, respectively, which play an important role in metal uptake and translocation in plants; modification of these transporter activities may confer plant tolerance to metal stress. (Bovet et al., 2003; Talke et al., 2006; Krämer et al., 2007).

Although a number of target transcripts were detected for most of the conserved and non-conserved miRNAs in this study, there were several miRNAs for which targets were not identified. This was particularly observed for those non-conserved miRNAs. It is possible that expression of the targets sliced by the non-conserved miRNAs was too low to be detected. Another possibility is that not all plant miRNAs regulate their targets using cleavage. Instead, they may silence their target’s activity via translational repression (Brodersen and Voinnet, 2006). Also, the spatial/temporal differences in expression, or very low expression of a miRNA, may result in insufficient degradation of targets.

In conclusion, this study identified a large number of conserved and non-conserved miRNAs from B. napus seedlings with or without heavy metal exposure. Comparative analysis of four libraries, from treated and control roots and shoots, showed that expression of some miRNAs was differentially regulated by Cd exposure. These miRNAs may be directly or indirectly involved in processes leading to plant tolerance to Cd. This study detected 13 non-conserved miRNAs, some of which being regulated by Cd exposure. No species-specific miRNAs were identified, possibly because only a small proportion (24.45–43.52%) of small RNAs could be mapped to ESTs and TC sequences of B. napus or because of a limitation of the tissues collected for sequencing. With the completion of the sequencing of the B. napus genome in the near future, more non-conserved or species-specific miRNAs may be discovered. Notably, many high-quality target transcripts were identified for the conserved and non-conserved miRNAs, particularly important are those possibly involved in regulation of plant response to Cd stress. Identification of these targets will help uncover the regulatory mechanism for plant tolerance to Cd.

Supplementary material

Supplementary data are available at JXB online.

Supplementary Table S1. Probe sequences used for Northern blotting to validate miRNAs

Supplementary Table S2. All known conserved and non-conserved miRNAs and their transcript abundance

Supplementary Table S3. New conserved and non-conserved miRNAs identified from B. napus

Supplementary Table S4. miRNA homologues with known miRNAs in other plant species in miRBase

Supplementary Table S5. Category I targets for miRNAs in details identified from degradome

Supplementary Table S6. Category II and III targets for miRNAs in details identified from degradome

Supplementary Table S7. Observed frequencies and patterns of degradome reads on the new and known miRNA precursors

Supplementary Fig. S1. Distribution of total and unique small RNAs according to length

Supplementary Fig. S2. Venn diagrams for analysis of total and unique small RNAs between Cd-free roots and shoots or between Cd-treated roots and shoots of B. napus

Supplementary Fig. S3. Venn diagrams for analysis of total and unique reads of degradomes between any two libraries

Supplementary Fig. S4. Distribution of total (A) and unique (B) reads of degradomes

Supplementary Fig. S5. t-plots for category I targets of miRNAs identified from degradome

Supplementary Fig. S6. t-plots for category II and III targets of miRNAs identified from degradome

Supplementary Fig. S7. Degradome signature abundance corresponding to miRNA precursors

Acknowledgements

This research was supported by the National Natural Science Foundation of China (31071343), the China Postdoctoral Science Foundation (special grant: 201003593), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (grant no. 200910).

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