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Genome-wide analysis of miRNAs in Carya cathayensis

Abstract

Background

MicroRNA (miRNA) plays an important role in plant development regulation. Hickory is an economically important plant in which the amount of flowering determines its production.

Results

Here, 51 conserved miRNAs, which belong to 16 families and 195 novel miRNAs were identified in hickory genome. For each conserved miRNA family, we used sequences from hickory and other plants to construct a phylogenetic tree, which shows that each family has members in hickory. Some of the conserved miRNA families (i.e., miR167 and miR397) have more members in hickory than in other plants because of gene expansion. MiR166 exhibited tandem duplication with three copies being observed. Many members of these conserved miRNA families were detected in hickory flowers, and the expression patterns of target genes were opposite to those of the related miRNAs, indicating that miRNAs may have important functions in floral regulation of hickory.

Conclusions

Taken together, a comprehensive analysis was conducted to identify miRNAs produced in hickory flower organs, demonstrating functional conservation and diversity of miRNA families among hickory, Arabidopsis, grape, and poplar.

Background

MicroRNAs (miRNAs) are classified as small non-coding RNA molecules, whose length range from 18 to 24 nucleotides, acting as central regulators of gene expression [1]. They negatively regulate gene expression by complementarily binding to the open reading frames (ORFs) or untranslated regions (UTRs) of target messenger RNAs. Mature miRNAs are derived from primary miRNAs transcribed from specific MIR genes. These precursor molecules are cleaved by the Dicer-Like1 (DCL1) protein, forming a miRNA/miRNA* complex, which is divided into miRNA and miRNA* after transporting to the cytoplasm [2]. MiRNAs are bounded by Argonaute proteins, forming a part of the RNA-induced silencing complex (RISC). RISC then interacts with the target mRNAs at the paired region, cleaving the RNA of target genes [3]. Plant development (i.e., flower development) and its response to environmental stresses are regulated by MiRNAs [4,5,6,7]. Studies have shown that miR156 and miR172 families play important roles in vegetative phase changes in Arabidopsis [8]. Additionally, the miR159, miR319 and miR390 families play roles in controlling the flowering time [9,10,11].

In 1993, the first miRNA (lin-4) was discovered and identified in Caenorhabditis elegans [12]. In 2001, many miRNAs were identified in a number of animal species via cloning and sequencing [13], and many additional miRNA were revealed by bioinformatics prediction and cloning. MiRNAs can be easily identified based on sequences. However, it is difficult to detect species-specific miRNAs. The cloning method is laborious and can only be used to identify miRNAs on a small scale. Alternatively, high-throughput sequencing is a powerful approach for identifying miRNAs [14]. High-throughput sequencing technology can yield abundant reads and detect the expression of minimally abundant small RNAs (sRNAs). This methodology has become the technique of choice for sequencing genomes, transcriptomes and small RNA transcriptomes [15]. The expression of sRNAs at different developmental stages can be profiled by high-throughput sequencing [16].

The evolution and function of miRNAs are revealed by miRNA-based studies from a phylogenetic perspective. Evolutionary conservation enables the identification of miRNAs for which homologs have previously been reported in other species [17]. miRNA genes are frequently expressed in a temporally and spatially regulated manner. Also, they play a fine-tuning role, by which the expressions of protein-coding genes are regulated. miRNA sequences are highly conserved among different plants as well as their functions [9, 10]. In angiosperms, functional identification of miRNAs is less available, so analysis of the miRNA repertoire is necessary to trace out the miRNA targets and the functional diversification in land plants.

Hickory (Carya cathayensis), an important economic woody plant, is mainly distributed in Zhejiang and Anhui provinces of China. Hickory has a long juvenile phase, and females and males present different flowering times, imposing a constraint on breeding and stable annual production. The morphological turning point from vegetative to reproductive stage appears in late March, when male floral buds dehisce and pollen releases. Huang et al., (2007) have observed five distinct stages for hickory female floral development including the floral undifferentiated stage, flower bud differentiation and the stage of formation and development of the inflorescence, of the female involucre, and of the pistil [18,19,20].

Thus, it is necessary to identify miRNAs and analyse sequence divergence of miRNAs in hickory, especially their relation to flower development. In this study, hickory miRNAs were investigated by RNA-seq technology, and those related to March Flower (MF) (floral undifferentiated stage) and April Flower (AF) (flower bud differentiation) were further analysed. Many miRNAs were obtained and compared with homologous sequences from the genomes of other plants. A comprehensive phylogenetic analysis were also conducted for hickory miRNA family members and their homologs from three other land plant species.

Results

Identification and expression analysis of conserved and novel miRNAs in hickory

To identify conserved miRNAs associated with development of female flower, miRNAs were predicted using hickory genome (unpublished) with SOAP software, and their secondary structures were also predicted. 51 conserved mature miRNAs of 16 families and their precursor sequences were identified in hickory genome. The minimal folding energy (MFE) of the precursor sequences ranged from −26.1 to −99.62 kcal.mol−1, with a mean of −56.27 kcal.mol−1. The largest family was the miR167 family consisting of six members, followed by miR156 family, which included five members (Table 1). The expression of miRNAs was calculated with RPKM (Reads Per Kilobase of exon model per Million mapped reads) [21]. The expression of these predicted conserved miRNAs varied from 0.30 to 39,508.53, with means of 832.42 (MF) and 1304.09 (AF) (Additional file 1: Table S4). Among these families, the miR166 family was the most abundantly expressed, while the miR167 family exhibited the second most abundant expression. Thus, miR166 and miR167 may play important roles in flower development of hickory. Several miRNA families (miR160, miR390 and miR168 families) were moderately expressed (Additional file 1: Table S4), whereas only a few read counts were detected for some miRNA families. Thirty miRNAs exhibited uridine at the 5′ end, accounting for 58.82% of all conserved miRNAs, whereas adenine, guanine and cytosine were the first bases in 8 (15.69%), 8 (15.69%), and 5 (9.80%) miRNAs, respectively (Additional file 2: Figure S1a). The presence of uridine as the first base is characteristic of miRNAs, this region interacts with AGO1, together with the miRNA/RISC complex [22,23,24]. We observed a bias toward adenine and guanine at the 5′ end, which coincided with previous studies in flowers [25].

Table 1 The conserved miRNA family in Carya cathayensis and other plant

In total, 195 predicted novel mature miRNAs and precursor sequences were identified from different floral developmental stages in hickory (Additional file 1: Table S4). The average minimal folding energy of the precursor sequences was −54.57 kcal.mol−1, ranging from −18.7 to −128.5 kcal.mol−1 (Additional file 1: Table S4). Uridine was the first nucleotide in nearly half of the novel mature miRNA sequences, which was consistent with results in soybean (Additional file 2: Figure S1b). The expression abundant of novel miRNAs varied from 0.28 to 5825.56, with means of 44.77 (MF) and 122.78 (AF), which was much lower than the conserved miRNAs. Some novel miRNA sequences with tissue-specific expression, including cca-miR27, cca-miR36, cca-miR48, cca-miR113 and cca-miR176, were only detected in the AF library, while cca-miR127 was only expressed in the MF library. Some miRNAs, such as cca-miR87, cca-miR105 and cca-miR122, presented higher expression in the AF library than that in the MF library (Additional file 1: Table S4). These results suggested that these novel miRNAs may play important roles in the development at the flowering stage.

We compared the miRNA expression levels between MF and AF. miRNAs that exhibited AF/MF ratios greater than 2 were considered to indicate differential expression. The expression of twenty-two conserved and twenty-six novel miRNA sequences were different, and most of these miRNAs were up-regulated in AF (Additional file 1: Table S5). In addition, some miRNAs (cca-miR27, cca-miR113, cca-miR176, and miR156j) were only detected in the AF library (Additional file 1: Table S5), showing that certain miRNAs are tissue-specific [26]. No large changes in miRNA expression (expression ratios greater than 10.00) were observed, except for miR160a, which presented a ratio of 10.43. The miRNAs exhibited high expression levels in both AF and MF (expression values of 355.75 and 34.12, respectively). The conserved miR156, miR166, miR169 and miR171 families were differentially up-regulated in AF, which was consistent with the roles they play in floral organ development (Additional file 2: Figure S2, Additional file 1: Table S5). New species-specific miRNAs were considered novel miRNAs if they had evolved recently and were frequently expressed at low levels compared with conserved miRNAs as reported in Arabidopsis and wheat. Conversely, cca-miR27, cca-miR65, cca-miR113, cca-miR164 and cca-miR176 exhibited expression values greater than 100 in the AF libraries (Additional file 1: Table S5).

We used quantitative real-time PCR (qRT-PCR) to further analyze the expression of 15 conserved miRNAs and 12 novel miRNA candidates in different tissues and also different female floral development stages (Additional file 2: Figure S2). Both qRT-PCR and Solexa sequencing demonstrated that the conserved miRNA sequences as well as the novel miRNAs were up-regulated during flower development, except for miR393a and miR408 (Additional file 2: Figure S2, Additional file 1: Table S5). Solexa sequencing indicated that cca-miR27 and cca-miR113 were only detectable at the AF floral stage, whereas qRT-PCR indicated that they were expressed at both floral stages (Additional file 2: Figure S2); this disparity likely occurred because deep sequencing could not detect the entire real distribution of these miRNAs, and some miRNAs were therefore not detected. The expression of most miRNAs was ubiquitous in all studied tissues, suggesting that they might have multiple functions in plant growth and development. Some miRNAs (cca-miR158, miR166b-3p, miR171a-3p, and miR319d) were highly expressed in flowers, while nearly all miRNAs (e.g., cca-miR27, cca-miR67, miR398a, miR408) were highly expressed in leaves. Many miRNAs, including cca-miR129, cca-miR140, cca-miR158, miR169, miR393, miR398, and miR408, were hardly detectable in roots, leaves and fruit (Additional file 2: Figure S3).

Phylogenetic analysis of conserved miRNAs in hickory

miRNA precursors were retrieved from miRBase21.0 for three species (Arabidopsis, grape, poplar) (Additional file 2: Figure S1), and a phylogenetic analysis of the miRNA precursor sequences was conducted. The obtained maximum likelihood (ML) tree (Fig. 1; Additional file 2: Figure S4) indicated that the data could be divided into three categories. Some hickory miRNAs were present in every clade (miR156, miR162, miR167, miR168, miR390, miR397, miR408 and miR482), whereas other hickory miRNAs were observed in most clades (miR166, miR171, miR172 and miR398), and some hickory miRNAs were included in only one clade (miR160, miR169, miR319 and miR395). Among the first group, there were four miR167 (miR167a-d) in Arabidopsis, five (miR167a-e) in grape, eight (miR167a-h) in poplar and six in hickory. The phylogenetic results showed that miR167 was partitioned into four major clades and that hickory miR167 was included in every clade (Fig. 1a). For miR156 and miR397, hickory miRNAs were observed in every clade in the phylogenetic tree (Fig. 1c, f). Among the second group, the phylogenetic results showed that miR171 was partitioned into four major clades. Only one clade did not contain hickory miR171 (Fig. 1b). Among the third group, for miR169, hickory miRNA was found in only one clade of the phylogenetic tree, and three members were found in hickory, while only one miRNA was observed in the other species (Fig. 1e). miR166 exhibited tandem duplication (miR166a and miR166e-3p), with the two miRNAs showing only a one-nucleotide difference but distinct differences in expression (Fig. 2). This tandem arrangement provides a simple explanation for the existence of different functions.

Fig. 1
figure 1

The maximum likelihood (ML) phylogenetic tree reconstruction using precursor miRNA family sequences from Arabidopsis (ath), grape (vvi), popar (ptc), and hickory (cca). MUSCLE alignment and ML were used for tree generation. The phylogenetic tree for miR167 (a), miR171 (b), miR156 (c), miR166 (d), miR169 (e), miR397 (f). The miRBase accession numbers as follows: ath-MIR167a (MI0000208), ath-MIR167b (MI0000209), ath-MIR167c (MI0001088), ath-MIR167d (MI0000975), ptc-MIR167a (MI0002235), ptc-MIR167b (MI0002236), ptc-MIR167c (MI0002237), ptc-MIR167d (MI0002238), ptc-MIR167e (MI0002239), ptc-MIR167f (MI0002240), ptc-MIR167g (MI0002241), ptc-MIR167h (MI0002242), vvi-MIR167a (MI0006515), vvi-MIR167b (MI0006516), vvi-MIR167c (MI0006517), vvi-MIR167d (MI0006518), vvi-MIR167e (MI0006519), ath-MIR171a (MI0000214), ath-MIR171b (MI0000989), ath-MIR171c (MI0000990), ptc-MIR171a (MI0002277), ptc-MIR171b (MI0002278), ptc-MIR171c (MI0002279), ptc-MIR171d (MI0002280), ptc-MIR171e (MI0002281), ptc-MIR171f (MI0002282), ptc-MIR171g (MI0002283), ptc-MIR171h (MI0002284), ptc-MIR171i (MI0002285), ptc-MIR171j (MI0007034), ptc-MIR171k (MI0005114), ptc-MIR171l (MI0007032), ptc-MIR171m (MI0007033), vvi-MIR171a (MI0006536), vvi-MIR171b (MI0006537), vvi-MIR171c (MI0006538), vvi-MIR171d (MI0006539), vvi-MIR171e (MI0006540), vvi-MIR171f (MI0006541), vvi-MIR171g (MI0007950), vvi-MIR171h (MI0006542), vvi-MIR171i (MI0006543), vvi-MIR171j (MI0031743), ptc-MIR156a (MI0002184), ptc-MIR156b (MI0002185), ptc-MIR156c (MI0002186), ptc-MIR156d (MI0002187), ptc-MIR156e (MI0002188), ptc-MIR156f (MI0002189), ptc-MIR156g (MI0002190), ptc-MIR156h (MI0002191), ptc-MIR156i (MI0002192), ptc-MIR156j (MI0002193), ptc-MIR156k (MI0002194), ptc-MIR156l (MI0022040), ath-MIR156a (MI0000178), ath-MIR156b (MI0000179), ath-MIR156c (MI0000180), ath-MIR156d (MI0000181), ath-MIR156e (MI0000182), ath-MIR156f (MI0000183), ath-MIR156g (MI0001082), ath-MIR156h (MI0001083), ath-MIR156i (MI0019232), ath-MIR156j (MI0019234), vvi-MIR156a (MI0006485), vvi-MIR156b (MI0006486), vvi-MIR156c (MI0006487), vvi-MIR156d (MI0006488), vvi-MIR156e (MI0006489), vvi-MIR156f (MI0006490), vvi-MIR156g (MI0006491), vvi-MIR156h (MI0007939), vvi-MIR156i (MI0006492), ptc-MIR166o (MI0002232), ptc-MIR166p (MI0002233), ptc-MIR166q (MI0002234), vvi-MIR166a (MI0006507), vvi-MIR166b (MI0006508), vvi-MIR166c (MI0006509), vvi-MIR166d (MI0006510), vvi-MIR166e (MI0006511), vvi-MIR166f (MI0006512), vvi-MIR166g (MI0006513), vvi-MIR166h (MI0006514), ath-MIR169a (MI0000212), ath-MIR169b (MI0000976), ath-MIR169c (MI0000977), ath-MIR169d (MI0000978), ath-MIR169e (MI0000979), ath-MIR169f (MI0000980), ath-MIR169g (MI0000981), ath-MIR169h (MI0000982), ath-MIR169i (MI0000983), ath-MIR169j (MI0000984), ath-MIR169k (MI0000985), ath-MIR169l (MI0000986), ath-MIR169m (MI0000987), ath-MIR169n (MI0000988), ptc-MIR169a (MI0002245), ptc-MIR169b (MI0002252), ptc-MIR169c (MI0002253), ptc-MIR169d (MI0002254), ptc-MIR169e (MI0002255), ptc-MIR169f (MI0002256), ptc-MIR169g (MI0002257), ptc-MIR169h (MI0002258), ptc-MIR169i (MI0002259), ptc-MIR169j (MI0002260), ptc-MIR169k (MI0002261), ptc-MIR169l (MI0002262), ptc-MIR169m (MI0002263), ptc-MIR169n (MI0002264), ptc-MIR169o (MI0002265), ptc-MIR169p (MI0002266), ptc-MIR169q (MI0002267), ptc-MIR169r (MI0002268), ptc-MIR169s (MI0002269), ptc-MIR169t (MI0002270), ptc-MIR169u (MI0002271), ptc-MIR169v (MI0002272), ptc-MIR169w (MI0002273), ptc-MIR169x (MI0002274), ptc-MIR169y (MI0002275), ptc-MIR169z (MI0002276), ptc-MIR169aa (MI0002246), ptc-MIR169ab (MI0002247), ptc-MIR169ac (MI0002248), ptc-MIR169ad (MI0002249), ptc-MIR169ae (MI0002250), ptc-MIR169af (MI0002251), ptc-MIR169ag (MI0022041), vvi-MIR169a (MI0006521), vvi-MIR169b (MI0007940), vvi-MIR169c (MI0006523), vvi-MIR169d (MI0006524), vvi-MIR169e (MI0006525), vvi-MIR169f (MI0006526), vvi-MIR169g (MI0006527), vvi-MIR169h (MI0007941), vvi-MIR169i (MI0007942), vvi-MIR169j (MI0006528), vvi-MIR169k (MI0006529), vvi-MIR169l (MI0007943), vvi-MIR169m (MI0006530), vvi-MIR169n (MI0007944), vvi-MIR169o (MI0007945), vvi-MIR169p (MI0006531), vvi-MIR169q (MI0007946), vvi-MIR169r (MI0006532), vvi-MIR169s (MI0006533), vvi-MIR169t (MI0006534), vvi-MIR169u (MI0006535), vvi-MIR169v (MI0007947), vvi-MIR169w (MI0007948), vvi-MIR169x (MI0007949), vvi-MIR169y (MI0006522), ath-MIR397a (MI0001015), ath-MIR397b (MI0001016), ptc-MIR397a (MI0002332), ptc-MIR397b (MI0002333), ptc-MIR397c (MI0002334), vvi-MIR397a (MI0007956)

Fig. 2
figure 2

Tandem duplication in the evolution of the miR166 family. a Alignment of mature miR166 of hickory with Arabidopsis. b Showing tandem duplication event of miR166e-5p and miR166a. c Expression of miR166a, miR166e-5p, and miR166e-3p

Sequence conservation and divergence of conserved miRNAs in eudicots

Orthologous and paralogous sequences in the gene structures of miRNA family members in the eudicots Arabidopsis, grape, poplar and hickory were compared (Additional file 2: Figure S2). The sequence alignment of mature miRNAs revealed a conserved consensus, with few variations. We further analyzed the motifs of the conserved miRNAs through a WebLogo analysis. The level and number of degenerate positions indicated by multiple alignments revealed degrees of conservation between the sequences (Fig. 3 and Additional file 2: Figure S5). Notably, nine miRNA families showed highly conserved sequences with 0–3 nucleotide substitutions in homologous regions. The highly conserved sequences were miR160, miR162, miR166, miR167, miR168, miR319, miR390, miR398 and miR408. These highly conserved miRNAs may have the same target mRNAs. The remaining sequences showed variable divergence, as indicated by different target gene products of multiple alignments of sequences. The degree of degeneracy in a miRNA sequence and the number of targets may be correlated. miR169, miR171 and miR482 were assembled according to various strategies and exhibited many variable positions (Fig. 3). However, the miR482 family contained the greatest number of nucleotide substitutions and was observed in woody plants (Fig. 3).

Fig. 3
figure 3

Sequence logo showing a consensus sequence generated from the multiple alignments of miRNA families from four different plant species. a The miR156 and miR167 represent highly conserved miRNAs. b The miR169 and miR397 represent moderately conserved miRNAs. c The miR171, miR172, miR408, and miR482 represent lowly conserved miRNAs

Target prediction and analysis of expression patterns

Based on the investigation of miRNA functions, 10 conserved and 2 novel differentially expressed miRNAs were selected as candidate miRNAs related to flower development (Table 2). In most of the miRNA families, including miR156, miR166, miR167, miR169 and miR171, some targets were involved in male and female flower development. These miRNAs were differentially expressed during flower development, except for miR168, miR319 and miR390 (Additional file 1: Table S5).

Table 2 Information of plant miRNAs and their targets in Carya cathayensis

A class III homeodomain-leucine zipper (HD-ZIPIII) was previously described and validated as a miR166 target in Arabidopsis [27, 28]. Therefore, we analyzed its expression at different times during flower development and in different tissues. The qRT-PCR analysis indicated accumulation of HD-ZIPIII transcripts in early flowers (A2), with similar accumulation patterns in the leaves and stems (Fig. 4 and Additional file 2: Figure S6). The expression of HD-ZIPIII decreased in mature hickory flowers (A3), and reduced accumulation was observed in the leaves and flowers, indicating that HD-ZIPIII is strongly down-regulated along with the flower development in hickory. This observation is in agreement with the functional role of this transcription factor in regulating hickory flower development [29]. HD-ZIPIII expression is inversely correlated with the expression pattern of miR166 (Fig. 4), suggesting a regulatory role of this miRNA associated with HD-ZIPIII in hickory plants during flower development.

Fig. 4
figure 4

RT-PCR analysis of miRNA and its targets expression. RT-PCR was performed with different flower developmental stages. Each bar represents an average of three independent reactions, including both biological and technical replicates. Error bars indicate SD

miR171 has been reported to down-regulate lost meristem (LOMs) genes during phase transition in Arabidopsis [30]. The miR171-targeted LOM genes, which encode GRAS family members known to maintain meristem cell polarity, are involved in the regulation of SPL activity [30]. In hickory, the transcripts of LOM genes preferentially accumulated in early flowers (A2), which showed higher expression levels than mature flowers (A3) (Fig. 4), whereas LOM gene expression was markedly decreased in mature flowers (A3) (Fig. 4). This expression pattern was inversely correlated with up-regulation of miR171 in the same developmental stages (Fig. 4), suggesting that miR171 regulates LOM genes during flower development in hickory.

Expression analysis indicated that miRNA targets exhibited distinct expression patterns during flower development. We also determined that several miRNAs regulated their targets in the same manner. For example, the targets of cca-miR27, cca-miR38, miR166b and miR171a were all down-regulated to different extents (A2-A3) in the flowering stage (Fig. 4), showing opposite expression patterns to the related miRNAs, indicating that the cca-miR27, cca-miR38, miR166b and miR171a families negatively regulate their targets.

Discussion

In recent years, a large number of conserved miRNAs and species-specific miRNAs have been identified using high-throughput sequencing [5]. This method presents a high-throughput capacity, allowing large-scale detection of miRNAs and high-sensitivity detection of minimally expressed miRNAs [5, 31, 32]. Here, we identified 51 conserved miRNAs belonging to 16 families and 195 novel miRNAs (Additional file 1: Table S4). Through miRNA-seq, we identified more miRNA copies than have been found in other sequenced species, with several copies being observed in some families. Furthermore, certain miRNAs exhibited gene expansion in hickory. Previous studies have indicated that the morphological turning point between vegetative and reproductive stages of hickory emerges during late March, when male floral buds are dehiscent [19]. Expression analysis suggested that some miRNAs exhibited higher expression in mature flowers (A3) compared with early flowers (A2), and the expression patterns of their target genes were in contrast to those of the miRNAs. Analysis of the Arabidopsis floral transcriptome indicated that many genes encoding transcription factors were preferentially expressed during early flower development compared with other stages [29]. These early-expressed genes have functions that are associated with reproductive development, suggesting that early flower development requires many more abundantly expressed genes than in mature flowers [29]. Overall, our findings suggest that these miRNAs may be related to flower development.

We analyzed the hickory miRNA families and compared their members with representatives from Arabidopsis, grape and poplar. Most of the mature miRNA sequences exhibited high sequence identity and conservation (Fig. 4, Additional file 2: Figure S4), but all of the mature sequences presented some degree of divergence. Multiple alignments enabled the identification of nine highly conserved miRNA families (miR160, miR162, miR166, miR167, miR168, miR319, miR390, miR398 and miR408) and four moderately conserved miRNA families (miR156, miR172, miR395 and miR397). miR169, miR171 and miR482 were belonged to miRNA families with low conservation (Fig. 3, Additional file 2: Figure S4).

The phylogenetic analysis of precursors of different miRNA families from the selected species showed a distinct clustering pattern. The phylogenetic tree for the miRNAs suggested that although the miRNA families were conserved among the four plant species, some miRNA members exhibited new functions because of additional mutation events in the mature miRNA region of the miRNA genes. Overall, these analyses revealed a combination of ancestral relationships and recent lineage-specific diversification. In the phylogenetic analysis, the ML trees were classified into three types. Hickory miR156 and miR167 family members were observed in every clade and belonged to the moderately and highly conserved miRNA groups, respectively (Fig. 1). However, mature miR156s, exhibiting little sequence diversification and differentiated expression, are expected to play a different functional role in hickory flower development. These conserved miRNAs and their conserved target transcription factors highlight the versatile functions of miRNAs and provide further evidence of the phylogenetic distribution of miRNA families, regardless of species boundaries. Additionally, both mature miR156 and miR167, which showed minor sequence variations, can still target similar genes (Fig. 3; Table 1). Thus, the functions of miR157 and miR167 are expected to be conserved among the four species.

Tandem duplication events in miRNA genes result in the formation of paralogous miRNA gene copies located in close proximity to each other on the same chromosome, thus forming miRNA clusters. It was recently demonstrated that miRNAs have been expanded through tandem duplication in the Arabidopsis, poplar and grape genomes, with 248 miRNAs belonging to 51 miRNA families being demonstrated to have originated via tandem duplication, including the miR166 family [33]. The clustering of cca-miR166a and cca-miR166e suggests that they originated from recent duplication event, without major sequence changes. The expression of these two mature miRNAs exhibits significant variation (Fig. 2). Some evidence shows that the miR166 family has undergone more intensive diversification through multiple duplication and expansion events since separation from an ancestor. miR166 regulates shoot apical meristem and flower development in Arabidopsis by targeting the transcription of HD-ZipIII transcription factors [34]. Over-expression of miR166 may destroy the flower structure and could result in a decreased number of pistils and carpels [28]. Pistillate flowers are naked without a perianth in hickory. Regarding biological characteristics, the pistillate flowers of hickory are initiated from a terminal bud that grows on short pod-branches in young hickory trees and persists until reproductive age. Thus, the miR166 family may regulate the pistillate flower structure and floral meristem determination in hickory.

Conclusions

We conducted a comprehensive analysis of hickory miRNAs produced in flower organs and computationally predicted their putative targets. We further performed bioinformatics analyses of 16 families of conserved miRNAs selected from the most conserved families, according to the biological processes in which they are involved. Our observations demonstrated the functional conservation and diversity of miRNA families among hickory, Arabidopsis, grape and poplar. This study provides data on the functional diversification and conservation of miRNA genes and constitutes a basis for further experimental studies of miRNA function in hickory. Some targets of hickory miRNAs have counterparts that have been previously identified and validated in other species, such as A. thaliana, V. vinifera and O. sativa [35,36,37]. Several known targets of specific miRNAs (primarily transcription factors) control various physiological processes and genetic programs associated with plant metabolism, flowering, hormone signaling and stress responses, as reflected by our data. This dataset is useful for identifying functional miRNA genes involved in hickory flower development and provides clues regarding miRNA evolution in various species.

Methods

Materials

Five 15-year-old clones of hickory trees planted at Lin’an, China were used as plant materials. Healthy plants were selected, and samples of the roots, stems, leaves, female and fruits were collected. Apart from different sample tissue collection, the various stages of female floral development were also collected including A1 stage (floral undifferentiated stage 1), A2 stage (floral undifferentiated stage 2), A3 stage (flower bud differentiation), and A4 stage (flower bud formation).

Conserved and novel miRNAs in hickory

The Raw data were generated from MF and AF sRNA libraries of female flowers [5]. Clean RNAs were mapped to hickory genome (unpublished) using SOAP software. The sRNAs with a perfect match were further analyzed. Sequences matching noncoding RNAs including rRNAs, scRNAs, snoRNAs, snRNAs, and tRNAs were annotated by comparing with sequences in the NCBI GenBank (http://0-www-ncbi-nlm-nih-gov.brum.beds.ac.uk/blast/Blast.cgi) and Rfam databases (http://www.sanger.ac.uk/Software/Rfam). The conserved miRNAs were subsequently annotated via alignment with miRBase 21.0 (http://www.mirbase.org/index.shtml), allowing two mismatches. The remaining unknown sRNAs were analyzed to predict novel miRNAs using Mireap (http://sourceforge.net/projects/mirea p/). According to recently published criteria, novel miRNAs were screened [38]. The mapped sequences were employed to predict secondary structures with RNAfold software (http://www.tbi.univie.ac.at/*ivo/RNA).

Alignment of sequences and phylogenetic analysis

Precursor and mature sequences of miRNAs from Arabidopsis, grape and poplar were obtained from miRBase, Release 21 (http://www.mirbase.org/index.shtml). ClustalW was used to generate multiple alignments of nucleotide acid sequences and MEGA5 was used to generate phylogenetic analyses using the ML method [39]. ML phylogenetic trees were produced with 1000 bootstrap replications. Multiple sequence alignments of mature miRNAs were employed to generate a graphical representation of the consensus pattern using the web-based tool WebLogo (http://weblogo.berkeley.edu/logo.cgi, accessed 25 Feb. 2015).

Cloning hickory miRNA precursors

A modified CTAB method was used to extract total RNA from hickory tissues [40]. The total RNA from hickory was transcribed into cDNA using an M-MLV reverse transcriptase (RNase H-) kit (Takara, China). The cDNA was amplified via PCR using primer pairs designed based on predicted hickory miRNA precursors with Primer Premier 5.0. The PCR products were then cloned into the pMD19-T (simple) vector (Takara, China), and further sequencing was conducted at Sangon Biotech (Shanghai, China) (Additional file 1: Table S1).

qRT-PCR of miRNAs and their target mRNAs

A comparative qRT-PCR expression analysis for different tissues (roots, stems, leaves, female and fruits) and also for different female floral development stages (A1, A2, A3, and A4) were performed. As previous described [41], miRNAs were chosen for stem-loop RT-PCR. Briefly, total RNA was hybridized with a miRNA-specific stem-loop primer. About 500 ng total RNA was reverse-transcribed into cDNA in a 10-μl reaction volume using M-MLV Reverse Transcriptase (D2639A, Takara). qRT-PCR was performed with Platinum® SYBR® Green qPCR SuperMix-UDG (Invitrogen, C11744500). The 20-μl reaction system included 1 Î¼l of the RT product, 4 Î¼l of each primer (5 Î¼M), 10 Î¼l of 2× SYBR Green reaction mix and 5 Î¼l of ddH2O. All cDNA samples were assayed in triplicate. The primers employed for these assays are listed in Additional file 2: Table S2 and Additional file 2: Table S3. 5.8S rRNA was used as a reference gene. The fold changes of each gene were calculated using the 2−△△Ct method [42].

Statistics

Least-square means (LS means) and analysis of variance (ANOVA; GLM procedure) were performed using Microsoft Office Excel 2007.

Abbreviations

AF:

April Flower

AGO :

Argonaute

AP2 :

Apetala2

ARF :

Auxin response factors

DCL1 :

Dicer-Like1

EST:

Sequenced tag

HD-ZIPIII :

Class III homeodomain-leucine zipper

LOM :

Lost meristems

MF:

March Flower

miRNA:

microRNA

ML:

Maximum likelihood

NF-YA1 :

Nuclear Factor Y, Subunit A1

ORF:

Open reading frame

qRT-PCR:

Quantitative real-time PCR

RISC:

RNA-induced silencing complex

SBP :

Squamosa promoter-binding protein

sRNA:

Small RNA

UTR:

Untranslated regions

References

  1. Yamaguchi A, Abe M. Regulation of reproductive development by non-coding RNA in Arabidopsis: to flower or not to flower. J Plant Res. 2012;125(6):693–704.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281–97.

    Article  CAS  PubMed  Google Scholar 

  3. Llave C, Xie Z, Kasschau KD, Carrington JC. Cleavage of scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science. 2002;297(5589):2053–6.

    Article  CAS  PubMed  Google Scholar 

  4. Axtell MJ, Snyder JA, Bartel DP. Common functions for diverse small RNAs of land plants. Plant Cell. 2007;19(6):1750–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wang ZJ, Huang JQ, Huang YJ, Li Z, Zheng BS. Discovery and profiling of novel and conserved microRNAs during flower development in Carya cathayensis via deep sequencing. Planta. 2012;236(2):613–21.

    Article  CAS  PubMed  Google Scholar 

  6. Wang Z, Huang J, Sun Z, Zheng B. Identification of microRNAs differentially expressed involved in male flower development. Funct Integr Genomics. 2015;15(2):225–32.

    Article  CAS  PubMed  Google Scholar 

  7. Wang Z, Huang R, Sun Z, Tong Z, Huang J. Identification and profiling of conserved and novel microRNAs involved in oil and oleic acid production during embryogenesis in Carya cathayensis Sarg. Funct Integr Genomics. 2017;17:365–73.

    Article  CAS  PubMed  Google Scholar 

  8. Aukerman MJ, Sakai H. Regulation of flowering time and floral organ identity by a microRNA and its APETALA2-like target genes. Plant Cell. 2003;15(11):2730–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jin D, Wang Y, Zhao Y, Chen M. MicroRNAs and their cross-talks in plant development. J Genet Genomics. 2013;40(4):161–70.

    Article  CAS  PubMed  Google Scholar 

  10. Jones-Rhoades MW, Bartel DP, Bartel B. MicroRNAs and their regulatory roles in plants. Annu Rev Plant Biol. 2006;57:19–53.

    Article  CAS  PubMed  Google Scholar 

  11. Kim W, Ahn HJ, Chiou T-J, Ahn JH. The role of the miR399-PHO2 module in the regulation of flowering time in response to different ambient temperatures in Arabidopsis thaliana. Mol Cells. 2011;32(1):83–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843–54.

    Article  CAS  PubMed  Google Scholar 

  13. Lau NC, Lim LP, Weinstein EG, Bartel DP. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science. 2001;294(5543):858–62.

    Article  CAS  PubMed  Google Scholar 

  14. Rajagopalan R, Vaucheret H, Trejo J, Bartel DP. A diverse and evolutionarily fluid set of microRNAs in Arabidopsis thaliana. Genes Dev. 2006;20(24):3407–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. He N, Zhang C, Qi X, Zhao S, Tao Y, Yang G, et al. Draft genome sequence of the mulberry tree Morus Notabilis. Nat Commun. 2013;4:2445.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Pant BD, Musialak-Lange M, Nuc P, May P, Buhtz A, Kehr J, et al. Identification of nutrient-responsive Arabidopsis and rapeseed microRNAs by comprehensive real-time polymerase chain reaction profiling and small RNA sequencing. Plant Physiol. 2009;150(3):1541–55.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Fattash I, Voß B, Reski R, Hess WR, Frank W. Evidence for the rapid expansion of microRNA-mediated regulation in early land plant evolution. BMC Plant Biol. 2007;7(1):1.

    Article  Google Scholar 

  18. Wang Z, Huang J, Huang Y, Chen F, Zheng B. Cloning and characterization of a homologue of the FLORICAULA/LEAFY gene in hickory (Carya cathayensis Sarg). Plant Mol Biol Report. 2012;30(30):794–805.

    Article  CAS  Google Scholar 

  19. Huang YJ, Liu LL, Huang JQ, Wang ZJ, Chen FF, Zhang QX, et al. Use of transcriptome sequencing to understand the pistillate flowering in hickory (Carya cathayensis Sarg.). BMC Genomics. 2013;14(1):691.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Sun Z, Li Z, Huang J, Zheng B, Zhang L, Wang Z. Genome-wide comparative analysis of LEAFY promoter sequence in angiosperms. Physiol Mol Biol Plants. 2016;23:1–11.

    Google Scholar 

  21. Mortazavi A, Williams BA, Mccue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5(7):621–8.

    Article  CAS  PubMed  Google Scholar 

  22. Kim VN. Sorting out small RNAs. Cell. 2008;133(1):25–6.

    Article  CAS  PubMed  Google Scholar 

  23. Mi S, Cai T, Hu Y, Chen Y, Hodges E, Ni F, et al. Sorting of small RNAs into Arabidopsis argonaute complexes is directed by the 5′ terminal nucleotide. Cell. 2008;133(1):116–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Takeda A, Iwasaki S, Watanabe T, Utsumi M, Watanabe Y. The mechanism selecting the guide strand from small RNA duplexes is different among argonaute proteins. Plant Cell Physiol. 2008;49(4):493–500.

    Article  CAS  PubMed  Google Scholar 

  25. Baumberger N, Baulcombe D. Arabidopsis ARGONAUTE1 is an RNA slicer that selectively recruits microRNAs and short interfering RNAs. Proc Natl Acad Sci USA. 2005;102(33):11928–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Nag A, King S, Jack T. miR319a targeting of TCP4 is critical for petal growth and development in Arabidopsis. Proc Natl A Sci. 2009;106(52):22534–9.

    Article  CAS  Google Scholar 

  27. Juarez MT, Kui JS, Thomas J, Heller BA, Timmermans MC. microRNA-mediated repression of rolled leaf1 specifies maize leaf polarity. Nature. 2004;428(6978):84–8.

    Article  CAS  PubMed  Google Scholar 

  28. Williams L, Grigg SP, Xie M, Christensen S, Fletcher JC. Regulation of Arabidopsis shoot apical meristem and lateral organ formation by microRNA miR166g and its AtHD-ZIP target genes. Development. 2005;132(16):3657–68.

    Article  CAS  PubMed  Google Scholar 

  29. Zhang L, Wang L, Yang Y, Cui J, Chang F, Wang Y, et al. Analysis of Arabidopsis floral transcriptome: detection of new florally expressed genes and expansion of Brassicaceae-specific gene families. Front Plant Sci. 2014;5:802.

    PubMed  Google Scholar 

  30. Xue XY, Zhao B, Chao LM, Chen DY, Cui WR, Mao YB, et al. Interaction between two timing microRNAs controls trichome distribution in Arabidopsis. PLoS Genet. 2014;10(4):e1004266.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Wang T, Pan H, Wang J, Yang W, Cheng T, Zhang Q. Identification and profiling of novel and conserved microRNAs during the flower opening process in Prunus mume via deep sequencing. Mol Gen Genomics. 2014;289(2):169–83.

    Article  CAS  Google Scholar 

  32. Wu MF, Tian Q, Reed JW. Arabidopsis microRNA167 controls patterns of ARF6 and ARF8 expression, and regulates both female and male reproduction. Development. 2006;133(21):4211–8.

    Article  CAS  PubMed  Google Scholar 

  33. Sun J, Zhou M, Mao Z, Li C. Characterization and evolution of microRNA genes derived from repetitive elements and duplication events in plants. PLoS One. 2012;7(4):e34092.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Hawker NP, Bowman JL. Roles for class III HD-Zip and KANADI genes in Arabidopsis root development. Plant Physiol. 2004;135(4):2261–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Addo-Quaye C, Eshoo TW, Bartel DP, Axtell MJ. Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome. Curr Biol. 2008;18(10):758–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Pantaleo V, Szittya G, Moxon S, Miozzi L, Moulton V, Dalmay T, et al. Identification of grapevine microRNAs and their targets using high-throughput sequencing and degradome analysis. Plant J. 2010;62(6):960–76.

    CAS  PubMed  Google Scholar 

  37. Wu L, Zhang Q, Zhou H, Ni F, Wu X, Qi Y. Rice MicroRNA effector complexes and targets. Plant Cell. 2009;21(11):3421–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, et al. Criteria for annotation of plant MicroRNAs. Plant Cell. 2008;20(12):3186–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Guindon S, Lethiec F, Duroux P, Gascuel O. PHYML online—a web server for fast maximum likelihood-based phylogenetic inference. Nucleic Acids Res. 2005;33(suppl 2):W557–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Chang S, Puryear J, Cairney J. A simple and efficient method for isolating RNA from pine trees. Plant Mol Biol Rep. 1993;11(2):113–6.

    Article  CAS  Google Scholar 

  41. Chen C, Ridzon DA, Broomer AJ, Zhou Z, Lee DH, et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res. 2005;33:e179.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method[J]. Methods. 2001;25(4):402–8.

    Article  CAS  PubMed  Google Scholar 

  43. Wu G, Poethig RS. Temporal regulation of shoot development in Arabidopsis thaliana by miR156 and its target SPL3. Development. 2006;133(18):3539–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Liu PP, Montgomery TA, Fahlgren N, Kasschau KD, Nonogaki H, Carrington JC. Repression of AUXIN RESPONSE FACTOR10 by microRNA160 is critical for seed germination and post-germination stages. Plant J. 2007;52(1):133–46.

    Article  CAS  PubMed  Google Scholar 

  45. Vaucheret H, Vazquez F, Crété P, Bartel DP. The action of ARGONAUTE1 in the miRNA pathway and its regulation by the miRNA pathway are crucial for plant development. Genes Dev. 2004;18(10):1187–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Li WX, Oono Y, Zhu J, He XJ, Wu JM, Iida K, et al. The Arabidopsis NFYA5 transcription factor is regulated transcriptionally and posttranscriptionally to promote drought resistance. Plant Cell. 2008;20(8):2238–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Palatnik JF, Wollmann H, Schommer C, Schwab R, Boisbouvier J, Rodriguez R, et al. Sequence and expression differences underlie functional specialization of Arabidopsis microRNAs miR159 and miR319. Dev Cell. 2007;13(1):115–25.

    Article  CAS  PubMed  Google Scholar 

  48. Fahlgren N, Montgomery TA, Howell MD, Allen E, Dvorak SK, Alexander AL, et al. Regulation of AUXIN RESPONSE FACTOR3 by TAS3 ta-siRNA affects developmental timing and patterning in Arabidopsis. Curr Biol. 2006;16(9):939–44.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

We thank Kumar and Hikmet for critical reading and insightful comments and Nature Research Editing Service for editing the manuscript.

Funding

This work was supported by the Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR14C160002), the National High-Tech Research and Development Program of China (863 Program) (2013AA102605), the National Natural Science Foundation of China (31170637), the Zhejiang Provincial New Varieties Breeding Major Agricultural Science and Technology Projects (2012C12904), and the Zhejiang Forestry of Graduate Innovation Projects Priority Level (201529). The funding bodies did not play a role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript, but just provide the financial support.

Availability of data and materials

The data sets supporting the results of this article are available in the NCBI Sequence Read Archive and Treebase. Accession numbers of raw data for the MF (FA-SHA) and AF (FA-SHB) data are SRR5252339 and SRR5275057, respectively. Accession numbers of sequence and phylogeny data is 21,861.

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Contributions

ZS carried out qRT-PCR studies and the manuscript drafting. ZW and LZ participated in the design of the study and analysis. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Liang-sheng Zhang or Zheng-jia Wang.

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Not applicable. The hickory trees used in this study were planted in Zhejiang A and F University. The samples collected from hickory were for research use with permissions.

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Additional files

Additional file 1:

Table S1. Cloning of hickory miRNA precursors primers. Table S2. Real-Time PCR of hickory miRNA primers. Table S3. Real-Time PCR of hickory miRNA targets primers and target sequencses. Table S4. Hickory miRNA sequences. Table S5. Conserved and Novel different expression miRNAs identified in Carya cathayensis. (XLS 259 kb)

Additional file 2:

Figure S1. Conserved and Novel miRNA nucleotide bias at each position. a, Represent conserved miRNA nucleotide bias. b, Represent novel miRNA nucleotide bias. Figure S2. Real-Time PCR analysis of miRNA expression. Real-time PCR was performed with different flower timing. Each bar represents an average of three independent reactions, including both biological and technical replicates. Error bars indicate SD. Figure S3. Real-Time PCR analysis of miRNA expression. Real-time PCR was performed with different tissues. Each bar represents an average of three independent reactions, including both biological and technical replicates. Error bars indicate SD. Figure S4. The maximum likelihood (ML) phylogenetic tree reconstruction using precursor miRNA family sequences from Arabidopsis (ath), grape (vvi), poplar (ptc), and hickort (cca). MUSCLE alignment and ML were used for tree generation. Figure S5. Sequence logo showing a consensus sequence generated from the multiple alignments of miRNA families from four different plant species. a, The miR160, miR162, miR168, miR319, miR390, miR398 and miR408 represent highly conserved miRNAs. b, The miR172 and miR397 represent moderately conserved miRNAs. c, The miR169 represent lowly conserved miRNAs. Figure S6. RT-PCR analysis of miRNA and its targets expression. RT-PCR was performed with different tissues. Each bar represents an average of three independent reactions, including both biological and technical replicates. Error bars indicate SD.(DOC 3078 kb)

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Sun, Zc., Zhang, Ls. & Wang, Zj. Genome-wide analysis of miRNAs in Carya cathayensis . BMC Plant Biol 17, 228 (2017). https://0-doi-org.brum.beds.ac.uk/10.1186/s12870-017-1180-6

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