Identification and functional analysis of miRNAs in developing kernels of a viviparous mutant in maize

Identification and functional analysis of miRNAs in developing

kernels of a viviparous mutant in maize

Haiping Ding

, Jian Gao

, Mao Luo

, Hua Peng

, Haijian Lin

, Guangsheng Yuan

,

Yaou Shen

, Maojun Zhao

, Guangtang Pan

⁎, Zhiming Zhang

⁎

a_{Institute of Maize Research, Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture,}

Sichuan Agricultural University, Wenjiang 611130, China

b_{Drug Discovery Research Center of Luzhou Medical College, Luzhou Medical College, Luzhou 3344789, China} c

Sichuan Tourism University, Chengdu 610041, China

d

College of Life and Basic Science, Sichuan Agricultural University, Ya'an 625014, China

A R T I C L E I N F O

A B S T R A C T

Article history: Received 18 April 2013 Revised 3 May 2013 Accepted 17 July 2013

Available online 6 August 2013

Given the important roles of miRNAs in post-transcriptional gene regulation, identification of differentially expressed miRNAs will facilitate the elucidation of molecular mechanisms underlying kernel development. In this study, we constructed a small RNA library to comprehensively represent the full complement of individual small RNAs and to characterize miRNA expression profiles in pooled ears of maize (Zea mays L.) at 10, 15, 20, 22, 25 and 30 days after pollination (DAP). At least 21 miRNAs were differentially expressed. The differential expression of three of these miRNAs, i.e., miR528a, miR167a and miR160b, at each stage was verified by qRT-PCR. The results indicated that these miRNAs might be involved in kernel development. In addition, the predicted functions of target genes indicated that most of the target genes are involved in signal transduction and cell communication pathways, particularly the auxin signaling pathway. The expression of candidate germination-associated miRNAs was analyzed by hybridization to a maize genome microarray, and revealed differential expression of genes involved in plant hormone signaling pathways. This finding suggests that phytohormones play a critical role in the development of maize kernels. We found that in combination with other miRNAs, miR528a regulated a putative laccase, a Ring-H2 zinc finger protein and a MADS box-like protein, whereas miR167a and miR160b regulated multiple target genes, including ARF (auxin response factor), a member of the B3 transcription factor family. All three miRNAs are important for ear germination, development and physiology. The small RNA transcriptomes and mRNA obtained in this study will help us gain a better Keywords:

Ear germination-associated miRNAs Microarray hybridization

qRT-PCR Zea mays

⁎ Corresponding authors. Tel.: +86 835 2882714; fax: +86 835 2882154.

E-mail addresses:[email protected](G. Pan),[email protected](Z. Zhang).

1_{These authors contributed equally to this work.}

Peer review under responsibility of Crop Science Society of China and Institute of Crop Science, CAAS.

2214-5141/$– see front matter. Crown Copyright © 2013 Production and hosting by Elsevier B.V. on behalf of Crop Science Society of China and Institute of Crop Science, CAAS. All rights reserved.

http://dx.doi.org/10.1016/j.cj.2013.07.013

A v a i l a b l e o n l i n e a t w w w . s c i e n c e d i r e c t . c o m

understanding of the expression and function of small RNAs in the development of maize kernel.

Crown Copyright © 2013 Production and hosting by Elsevier B.V. on behalf of Crop Science Society of China and Institute of Crop Science, CAAS. All rights reserved.

1.

Introduction

Seed dormancy and germination are controlled by intrinsic hormonal and metabolic pathways, the components of which are influenced by external environmental cues[1–3]. Germi-nation is a key process that allows a seed embryo to grow and develop into a photosynthetic organism. The process of germination starts with the hydration of quiescent seed and ends with the onset of elongation of the embryo axis, which corresponds to the emergence of the radicle from the seed

[4,5]. Despite the impressive amount of information on the physiology of germination[4]and advances in understanding its molecular basis[5,6], recent transcriptome analyses have shown that dormancy in Arabidopsis (Arabidopsis thaliana) is associated with specific patterns of gene expression that are different from those in germinating seeds[7,8]. Recently, a new paradigm of post-transcriptional gene regulation has evolved as a result of the discovery of hundreds of miRNAs in maize (Zea mays L.). The diverse expression patterns of miRNAs and the large number of potential target mRNAs suggest their involvement in the regulation of a variety of developmen-tally related genes at the post-transcriptional level. Accumulating evidence indicates that miRNAs may function as ear germination suppressors during maize ear development and that they may have critical functions in growth, development, and responses to biotic and abiotic stresses. In plants, miRNAs regulate diverse genes and pathways such as those for development, hor-mone signaling, stress response and trans-acting siRNAs

[9,10]. Interestingly, phytohormones regulate plant develop-ment via a complex signal response network. Five major plant hormone genes are involved in the signaling pathway: auxin, cytokinin, gibberellin, abscisic acid, and ethylene. Many of the target genes associated with auxin are involved in ear development[1,11–13]. This finding led to the hypoth-esis that miRNAs play an important role in regulation of target genes during ear germination. The key roles played by GA (gibberellins) and ABA (abscisic acid) in ear germination and early development have long been established[14]. Further-more, previous research determined that in viviparous (vp) mutants in maize and other cereal grains, the embryo fails to become dormant and undergoes precocious germination on the mother plant.

miRNAs are a class of small single-stranded non-coding RNAs ranging in length from 20 to 24 nucleotides (nt)[15,16]. Most miRNA targets are mRNAs of protein-coding genes, which, upon targeting, are cleaved or repressed at the translational level[16–19]. Thus, miRNAs act as negative regulators of gene expression. In plants, most miRNAs regulate target gene

expression via mRNA degradation [20]. MiRNAs recognize

completely or partially complementary sequences in their target mRNAs and guide them to cleavage or translational arrest. Plant miRNAs usually recognize one motif in the coding region of their targets and affect their stability. It is thought that better complementarity between plant miRNAs and their

targets favors translational arrest rather than cleavage. The high degree of complementarity between plant miRNAs and their target mRNAs has allowed the identification of targets

using algorithms that scan the genome for mRNA–miRNA

complementarity [21]. Refinements in this method have in-creased the reliability of predictions[22]. When a miRNA targets multiple mRNAs, the targeted genes are often members of a gene family, and miRNAs that are conserved between Arabidopsis and rice (Oryza sativa L.) also tend to have conserved targets[21]. Intriguingly, plant miRNAs display a striking propensity to target the mRNAs of transcription factors that have already been established as key developmental regulators or their closely related factors. A number of computational methods have been reported for the identification of plant miRNAs

[23–26]. Research on plants revealed that short sequences of mature miRNAs are conserved and exhibit high complementar-ity to their target mRNAs[24]. Hence, candidate miRNAs can be detected using their conserved complementarities to target mRNA if the mRNA target sequence is known. Conversely, it has also been shown that the secondary structures of miRNA precursors (pre-miRNAs) are relatively more conserved than pri-miRNA sequences (the precursors of pre-miRNAs)[27]. For instance, through sequence homology analysis, 30 potential miRNAs were predicted in cotton (Gossypium spp.)[28], and an additional 58 miRNAs were identified in wheat (Triticum aestivum L.)[29]. The majority of plant miRNAs studied to date are involved in regulating developmental processes[30,31]and they negatively regulate expression of their target genes at the post-transcriptional level. Computational methods for identi-fying miRNAs in plants are more rapid, less expensive, and easier than experimental procedures. However, these bioinfor-matics approaches can only identify miRNAs that are conserved across organisms, and any computationally predicted miRNAs should also be confirmed via experimental methods. The direct cloning of small RNAs from plants is one of the basic approaches of miRNA discovery and has been used to isolate and clone small RNAs from various plant species such as Arabidopsis and rice

[32–34]. Many miRNAs are broadly expressed but can be detected only under certain environmental conditions, at different plant developmental stages, or in particular tissues. Therefore, plant samples from specific times, different tissues, and different stress conditions (biotic and abiotic stress-induced) are used for miRNA cloning. The most common plant species used for direct cloning are Arabidopsis[31,34,35], rice[36], cottonwood (Hibiscus tiliaceus)[37]and wheat[38]. The most important advantage of cloning small RNAs compared to computational approaches is the opportunity to find non-conserved and species-specific miRNAs. Efficient and appropriate miRNA detection and quan-tification methods are essential for understanding the function of a given miRNA under different conditions or in different tissues. In this study, we constructed a small RNA library to represent the full complement of individual small RNAs and characterized miRNA expression profiles in pooled developing ears of maize (Z. mays L.). In addition, we carried out functional

predictions of the target genes of candidate miRNAs. The small RNA transcriptomes and mRNAs obtained in the study will help us gain a better understanding of the expression and function of small RNAs in developing maize kernels.

2.

Materials and methods

The inbred maize line A318 is a viviparous mutant developed from the tropical germplasm S37 by spaceflight breeding (Fig. 1). Ears at 10, 15, 20, 22, 25 and 30 days after pollination (DAP) were collected from plants grown under standard green-house conditions. Kernels were dissected from the ears, imme-diately frozen in liquid nitrogen, and stored at−80 °C until RNA extraction.

Isolated total RNA was size-fractionated on a 15% Tris– borate–EDTA (TBE) urea polyacrylamide gel to enrich mole-cules of 15–30 nt. The small RNA was ligated with adapters

(5′-GTCTCTAGCCTGCAGGATCGATG-3′) and (5′-AAAGATCC

TGCAGGTGCGTCA-3′), and (5′-GTCTCTAGCCTGCAGGATCG

ATG-3′) and (5′-AAAGATCCTGCAGGTGCGTCA-3′) using T4

RNA ligase and size-fractionated on a 15% TBE urea poly-acrylamide gel. The resultant RNA was reversely transcribed

to cDNA with a small RNA RT-primer (5′-CAAGCAGAAGAC

GGCATACGA-3′), and the cDNA was then directly subcloned

into vector pMD18-T (TaKaRa). These tandem cDNA frag-ments were transformed into Escherichia coli strain DH5 by electroporation. Colony PCR was performed using 5′ and 3′ primers, and clones with lengths of 60–80 bp were used for sequencing according to the manufacturer's protocols (Colony PCR Made Easy,http://www.lucigen.com/colonyPCR).

Small RNAs (200 nt) were isolated with the mirVana PARIS Kit (Ambion) according to the manufacturer's instructions. For reverse transcription (RT), 1μg of small RNA was treated with the miScript Reverse Transcription Kit (Qiagen) at 37 °C for 60 min and a final incubation at 95 °C for 5 min. Real-time PCR of miRNAs was carried out using the miScript SYBR Green PCR kit (Qiagen) in an Applied Biosystems 7500 real-time PCR machine (ABI). PCR was conducted at 95 °C for 15 min, followed by 40 cycles of incubation at 94 °C for 15 s, 55 °C for 30 s, and

then 70 °C for 30 s. Each PCR was repeated at least three times. All samples were normalized to 5S rRNA expression and fold change expression was calculated according to the 2−ΔΔCtmethod as described previously[39].

High-quality small RNA reads larger than 18 nt were extracted from the raw reads and mapped to maize genome sequences (http://www.maizesequence.org) using SOAPaligner/ soap2 (http://soap.genomics.org.cn/soapaligner.html) [40]. Matched sequences were then queried against non-coding

RNAs from the Rfam database (http://www.sanger.ac.uk/

Software/Rfam) and the ncRNA database (http://www.ncrna. org/frnadb/blast/fRNAdb). Most non-miRNAs, non-siRNAs and mRNA degradation fragments were removed by a BLASTn search of the NCBI GenBank database (http://www.ncbi.nlm.nih. gov/blast/Blast.cgi)[41]. Any small RNAs with exact matches to these sequences were excluded from further analysis. miRNAs were predicted with Mireap (https://sourceforge.net/projects/ mireap/). Secondary structures of the predicted miRNAs were confirmed using the RNAfold online tool (http://rna.tbi.univie. ac.at/cgi-bin/RNAfold.cgi). miRNA target candidates were

pre-dicted using the PatScan program [42] based on methods

described by Lu[37], with penalty scores≤3 for mismatched patterns in the miRNA/mRNA duplexes. Putative target genes were manually selected from these candidates based on their location in the maize genome. Functions of the predicted target genes were assigned manually according to the functions of the

best hits from the BLAST search [41,43] against the NCBI

database (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi). For the predicted novel miRNA sequences, conservation in other plant species was examined by searching the nucleotide databases with BLASTn[41]to identify their homologs and

surrounding sequences. These germination-related

miRNAs were also aligned with the maize genome using

PatScan [42]. To analyze whether the matched sequence

could form a suitable hairpin, the sequences of candidate precursors were analyzed using RepeatMasker (http://www. repeatmasker.org/) to eliminate repetitive sequences. Se-quences surrounding the matched sequence (100–200 nt to either side) were extracted and run through RNAfold (http://rna. tbi.univie.ac.at/cgi-bin/RNAfold.cgi).

A

B

Most targets of miRNAs in plants have one miRNA-complementary site located in the coding region and occasion-ally in the 3′ or 5′ un-translated regions (UTRs)[21,36,38,44,45], and plant miRNAs exhibit perfect or near-perfect comple-mentarity with their target mRNAs[46]. We adopted a set of previously reported rules to predict miRNA targets[36,47]. These rules allow one mismatch in the region complementary to nucleotide positions 2 to 12 of the miRNA, do not allow a mismatch at position 10/11, which is a predicted cleavage site, and allow three additional mismatches between positions 12 and 22, but with no more than two continuous mismatches. Therefore, candidate miRNA target genes were determined using publicly available prediction algorithms, including miRU

[48], the target search in WMD web[49], and the prediction tool in the UEA plant sRNA toolkit. These programs were used with their default settings. The microarrays used in this study were obtained from GSE9386, entitled“Genome-wide analysis of gene expression profiles during the kernel development of maize (Z. mays L.)”. The raw data from microarray hybridization was exported from GenePix suites 6.0 (Axon, USA) and imported into LIMMA with annotation and spot types[50]. Spots with a negative flag value were assigned a weighting of 0.1 in the subsequent analysis. Background-subtracted signal in-tensities were normalized using two-step normalization, consisting of print-tip group loss (within-array normaliza-tion) and between-array scale normalization. The adjusted p value was then assessed using the false discovery rate. To identify a statistically significant differential expression of genes, p = 0.01 was used as a criterion. To obtain probe annotations, the consensus representative sequences of all probes were searched using BLAST against the TIGR rice protein database (http://www.tigr.org/), the TAIR Arabidopsis protein database (http://www.arabidopsis.org/), and the UniProt Knowledgebase (http://www.ebi.ac.uk/). Functional annotations were then assigned based on sequence similarity (with E-value of 10−5) with manual adjustment when necessary. All of the probes were grouped into functional categories and metabolic path-ways based on the Mips Functional Catalogue (http://mips.gsf. de/) and KEGG[51–53]. Adhering to the established method

[54,55], we identified statistically enriched KEGG pathways and gene families of transcription factors in differentially expressed genes based on a background distribution from the whole chip. The expression levels of genes were measured by detection calls and signal intensities using Micro Array Suite 5.0 software with a target signal of 100. All pair-wise differentially expressed genes were identified using SAM software (http://www-stat.stanford.edu/~tibs/SAM/) to analyze data from all remaining maize probe sets. A false discovery rate parameter of 1% was set for the SAM analysis. Genes that were called absent more than twice among the three replicates in both the control and treatment arrays were then considered to be not unexpressed under both conditions and were excluded from the list.

A 5μg sample of total RNA was used for cDNA synthesis using the Invitrogen Reverse Transcription Reagents Kit (Invitrogen). Gene-specific primers were designed using Primer Express 2.0 software (Applied Biosystems) and synthesized by Sangon Biotech Co. Ltd. (Shanghai). Relative quantitative analysis was performed using an Applied Biosystems 7900HT real-time PCR system (Applied Biosystems) under the following conditions:

94 °C for 3 min (1 cycle); 94 °C for 30 s, 60 °C for 30 s, and 72 °C for 30 s (40 cycles). Transcript abundance was identified using SYBR Green PCR Master Mix (Applied Biosystems). Each reaction contained 1× buffer, 0.25μmol L−1_{of each primer, and}

approx-imately 2 ng of cDNA in a final volume of 20μL. Three replicates were employed for each tested sample and template-free negative control. Mitochondrial 5S RNA was used as an internal control to normalize all data. Melting curves were performed on the product to test whether only a single product was amplified without primer-dimers and other bands. The resultant products with all primer combinations were initially visualized on 2% agarose gels to confirm the generation of a single product of the correct size.

3.

Results

To identify miRNAs in developing kernel of a maize viviparous mutant at different developmental stages, RNAs of 18 to 26 nt in length were purified and cloned from small RNAs (~ 200 nt) isolated from germinating maize kernels for subsequent sequence analysis. Approximately 64 concatamer clones were sequenced to generate 540 sequences after discarding low-quality and self-ligated linker sequences. Of these, 56 small RNA-cDNA sequences were outside the expected range of nucleotide lengths (18–26 nt). Only the nucleotide sequences that were longer than 18 nt were subjected to detailed analysis. The distribution of different lengths of nucleotide sequences found in this library is shown inFig. 2.

We categorized all identified sequences according to their properties using criteria reported elsewhere for different types of small RNAs. The 540 sequences identified in the library consisted of approximately 19.0% miRNA, 13.0% mRNA, 12.0% rRNA, 9% tRNA, 8.0% repeat-associated siRNA, 5.7% small antisense RNA, 6.0% tiny noncoding RNA, 2.3% small nuclear RNA and 25.0% of sequences that had no matches in the maize genome.

In the cDNA library, a total of 108 sequences were found to be miRNA-like molecules. Twenty-six newly identified se-quences perfectly matched the maize genome and were able to adopt hairpin structures. The lengths of these newly identified miRNAs ranged from 19 to 24 nt, and 10 of them began with a 5′ uridine, a characteristic feature of miRNAs. Twenty-one of these miRNAs were reported in miRBase 12.0 for different species, including maize, 16 were registered for other species, and 5 were new.

For each miRNA, the corresponding ear genomic DNA sequences and their locations were identified. The 5′ or 3′ flanking genomic sequences were then tested for ability to fold into miRNA precursor hairpin structures of approximate-ly 70 nt using the Mfold web server[56]. The presence of small RNA clones with the proper positioning within an arm of the hairpin suggested that they could have been excised during dicer processing in the cells. In nearly all of those cases, the sequences were found to be conserved in different species, including the predicted precursors. Moreover, 5 miRNA families (i.e., Zma-miR160, Zma-miR164, Zma-miR167, Zma-miR171 and Zma-miR528) were conserved in at least three species and 5 miRNA loci were specific to the maize ear (Table 1). To determine whether our new miRNAs are conserved among closely related

species, we searched for homology of their precursor sequences in the ENSEMBL genome databases. The results revealed that 16 precursor loci were conserved in at least six species. All of the newly cloned miRNAs were conserved as mature sequences in the genomes of different species. Thermo-dynamically stable hairpin structures were found for these new conserved miRNAs (Fig. 3).

It was shown that plant miRNAs exhibit a high degree of sequence complementarity to their targets, allowing for effective target prediction[57]. Target prediction analysis, there-fore, was performed for the germination-related zma-miRNAs (Tables 2 to 4).

The expression patterns of three annotated miRNAs (i.e., miR528a, miR167a and miR160b) at all six sampling times were analyzed using qRT-PCR (Fig. 4). Because the small RNAs were cloned with a library derived from different times of maize ear development, they were able to resolve the expres-sion profiles of the new miRNAs. Because of the distinct nature and function of germination, the cells and tissue compartments in the ear showed continuous change throughout the process of development.

We sought to identify the major biological processes and signaling pathways that are most likely affected by a group of miRNAs during development of the maize ear. Several potential target genes were predicted to be associated with cloned miRNAs based on our filtering and screening procedures. The miRNAs encoding proteins involved in regulation of mating were repre-sented at higher frequencies in our library. Furthermore, detailed gene ontology (GO) analysis showed that screened sub-sets of miRNA target genes were associated with ear development, function, and regulation (Fig. 5) involved in primary and

secondary metabolism, signal transduction, transcription and regulation, and protein processing and destination

To identify the target genes associated with ear germination identified in our research, identical genes were extracted from GSE9386 raw data. We detected 92 differentially expressed genes (P = 0.05) associated with germination during the process of ear development. Most of the changes in differentially expressed genes were observed between 10 and 15 DAP, while 23 genes had significant fold changes between 25 and 35 DAP. To elucidate the expression profiles of the differentially expressed genes, we transformed comparisons of two consecutive time points into a comparison using expression levels at 10 DAP as a common reference. A selection of differentially expressed genes associated with the candidate miRNA in ear germina-tion listed inTable 5includes genes related to cell division, starch metabolism, storage proteins, and hormone signaling pathways. Both up- and down-regulation occurred during the ear germination process.

Down-regulated gene expression predominated during the periods 15 to 25 and 25 to 35 DAP, whereas up-regulated gene expression predominated from 10 to 15 DAP. Thus, we added 20 and 22 DAP, which lie within the period from 15 to 25 DAP, and 30 DAP, which lies between the 25 and 35 DAP, to study the mechanism in more detail. The genes related to the ABA signaling pathway (e.g., serine/threonine protein kinase and transcription factor MYB30) and the gibberellin (GA) signaling pathway were also included in these two clusters. These genes were associated with ear germination and the candi-date miRNAs. Through analysis of gene expression patterns, we found that these genes may be involved in the entire germination process in the maize ear, and we concluded that miR167a/miR160b and miR528a might play major roles in ear germination by modifying their target genes, in combination with other miRNAs (Fig. 6).

To confirm the accuracy and reproducibility of the micro-array results, real-time PCR was carried out using 8 differen-tially expressed genes associated with miR167a/160b and miR528a (Table 6). We added 20 DAP and 22 DAP in the period between 15 and 25 DAP and 30 DAP between 25 and 35 DAP to study the detailed mechanism by real-time PCR. The results showed that the expression patterns of these genes were well correlated with the results from microarray analysis. However, given the wider dynamic range and greater sensitivity of real-time PCR, the variation of differentially expressed genes from real-time PCR was more significant than that from the microar-ray analysis; we found that 22 DAP is an important turning point in ear germination.

4.

Discussion

MicroRNAs play integral roles in gene regulatory networks as one of the most abundant classes of gene regulators. The expression and activity of plant miRNAs can be regulated in many ways, including transcriptional control, as well as regula-tion imposed at the levels of miRNA processing and acregula-tion. Moreover, changes in the expression of even a single miRNA could have a significant impact on the outcome of diverse cellular activities regulated by the product of that mRNA. Repression of the target transcript by miRNAs may occur

Table 1– Comparison of numbers of miRNA family members in maize, rice, Arabidopsis and soybean.

miRNA family Maize Rice Arabidopsis Soybean

Zma-miR160b/g (miR-96) 6 6 3 5 Zma-miR164e (miR-29) 4 6 3 3 zma-miR167a/b/c/d/e/f/ g/h/i/j (miR-25) 9 10 4 7 Zma-miR171a/b/c/d/e/f/ g/h/i/j/k/l/m/n (miR-99) 11 9 4 6 Zma-miR528a/b (miR-28) 2 2 0 0

Fig. 2– Size distribution of 540 small RNA sequences cloned from maize kernels.

through translational inhibition, accelerated exonucleolytic mRNA decay, or slice within miRNA–mRNA base pairing[58]. Beyond the strict conservation of miRNAs across different species, some miRNAs appear to be species-specific. Compared with computational or heterologous approaches, direct miRNA cloning has the advantage of identifying non-conserved and new miRNAs.

There are a number of highly conserved miRNA families in maize. In the present study, cloning and expression analysis led to the identification of 26 miRNA variants belonging to 21 miRNA families, as well as 5 new miRNAs and 16 putatively new miRNAs. Non-conserved plant miRNAs presumably emerge

and dissipate in short evolutionary time scales. Representation of many known and novel miRNAs in this single library indicates the presence of miRNAs that are not yet discovered. The identification of a large number of miRNAs that are not previously reported in maize, at least 10 of which are conserved in monocots, suggests that many more monocot-or maize-specific miRNAs are yet to be identified. Certainly, additional tissues should be evaluated for further discovery of miRNAs in maize, coupled with similar studies in related monocots. This will help establish how many of the currently maize-specific miRNAs are conserved in other monocot species. Moreover, both in-depth analysis of the existing library and

Zm-miR-21 GGAUGGGUGACCUCCUGGGAA (Intragenic)

Zma-miR-29 AUAUAUGGAUAUGGAUGUCUC (5′ region)

Zm-miR-89 UGGAUCGUUACCACUAGACGUGC (5′ region)

Fig. 3– Predicted secondary structure of three selected miRNA hairpins.

Table 2– Non-conserved miRNAs in maize kernel germination.

miRNA ID Predicted function Target genes in the maize kernel

Zma-miR160b/g Auxin response factor; transcriptional factor B3

GRMZM2G153233, AC207656.3_FG002 GRMZM2G159399, GRMZM2G005284 GRMZM2G390641, GRMZM2G369356 Zma-miR164e No apical meristem (NAM) protein; helix–loop–helix

DNA-binding; basic helix–loop–helix dimerization region bHLH

GRMZM2G146380 GRMZM2G163975 Zma-miR167a/b/c/d/e/f/g/h/i/j Auxin response factor

transcriptional factor B3 GRMZM2G475882 GRMZM2G073750 GRMZM2G028980 GRMZM2G035405 GRMZM2G068328 GRMZM2G081158 GRMZM2G078274 GRMZM2G035405 Zma-miR171a/b/c/d/e/f/g/h/i/j/k/l/m/n GRAS transcription factor

zinc finger, DHHC-type armadillo-type fold

GRMZM2G051785 GRMZM2G418899 GRMZM2G111191 GRMZM2G139018 Zma-miR528a/b Alkaline phosphatase

multi antimicrobial extrusion protein MatE laccase,

homeodomain-like; homeobox; homeobox, conserved site;

leucine zipper, homeobox-associated; helix–turn–helix motif, lambda-like repressor

GRMZM2G148937 GRMZM2G169033 GRMZM2G178741 GRMZM2G367668 GRMZM2G004106

organ-specific analysis of individual miRNAs will give insights into the functional mechanisms and pathways involved in particular in ear germination and ear development in general.

Recent studies have demonstrated that miRNAs in Arabidopsis, rice, and other plant species target transcripts that encode proteins involved in diverse physiological processes by predominantly targeting transcription factors [25,37,44,59]. In this study, we predicted 90 unigenes as putative miRNA targets in maize ears, with one-third of the predicted targets of miRNAs being mRNAs of transcription factors, including AUX_IAA, MYB, ARF, bZIP, bHLH and MADS. Other target genes include those encoding putative NADH dehydrogenase (ubiquinone oxidoreductase), a putative laccase, ethylene-responsive factor-like protein 1, pyruvate, phosphate dikinase, a chloroplast precursor, thymidine kinase, a cytochrome P450-like protein, and a transposase, suggesting that miRNAs in maize ears are involved in a broad range of physiological functions. Further analysis indicated that the targets of 16 conserved miRNAs from maize ears are also conserved among other plant species, implying that conserved miRNAs serve

conserved biological roles. Moreover, these targets were distinct from their Arabidopsis and rice homologs (especially the targets of the non-conserved miRNAs), indicating that they may be involved in ear-specific processes in maize. It will be interesting to identify the functions of these predicted target genes in maize.

Most target mRNAs of plant miRNAs have only a single miRNA-complementary site located in the coding regions or occasionally in the 3′ or 5′ UTR[21,25,44,60]. Consistent with these reports, maize ear miRNAs are predicted to target coding regions. Although 3′ UTRs were predicted to be target sites for plant miRNAs in only a few previously reported cases, 3 of the 16 targets of novel maize miRNAs reported in this study had target sites within the 3′ UTR, four were within a coding region, and 9 were in the 5′ UTR. This bias might reflect a mechanistic preference for translational repression. The fate of an mRNA may depend on the degree of complemen-tarity between a miRNA and its target mRNA; it appears that perfectly base-paired miRNAs mediate cleavage, whereas imper-fectly base-paired miRNAs mediate translation repression[61].

Table 3– Conserved miRNAs in maize kernel germination.

miRNA ID Predicted function Target genes in the maize

kernel

Zma-miR-33 Enolase 2 (2-phosphoglycerate dehydratase 2) N6-adenosine-methyltransferaseMT-A70-like TC259095, TC483134 Zma-miR-99 Zinc finger-like, Ring-H2 finger protein RHC1a, NF protein, protein kinase domain containing

protein; expressed protein

TC260780, TC260781, TC260779, TC272191

Zma-miR-47 Brassinosteroid insensitive 1-associated receptor kinase 1 precursor, putative, expressed TC313437 Zma-miR-89 MYB domain transcription factor; f-box domain containing protein; home domain-like; SANT,

DNA-binding

TC290993, CO459446 Zma-miR-61 ERFS (HBS1-like)

Zma-miR-16 Signal recognition particle 9 kDa protein (SRP9), SET domain-containing protein SET118, cytosolic glyceraldehyde-3-phosphate dehydrogenase GAPC4 BRI1-KD interacting protein 112

TC269890, TC262587, CD987251, CD942822 Zma-miR-30 Protein kinase, mitochondrial precursor, putative, expressed; ATP binding protein, putative,

expressed; cytochrome c, putative, expressed

TC332889, TC286407 Zma-miR-29 Chlorophyll a–b binding protein 2, chloroplast precursor (LHCII type I CAB-2), Zinc-finger

protein C60910-like, TOM (target of myb1)-like protein, ubiquitin-protein ligase, putative, expressed, receptor-like protein kinase 5 precursor, putative, expressed

TC248236, TC252275, TC270240

Zma-miR-21 Beta-ketoacyl-CoA synthase, helix–loop–helix DNA-binding domain containing protein, expressed, OsIAA6— auxin-responsive Aux/IAA gene family member, expressed

TC250204 Zma-miR-51 NADH-ubiquinone oxidoreductase chain 1

SCAN domain-containing protein 1

ZIP zinc/iron transport family protein, expressed

TC254551, TC278557

Zma-miR-87 Leucine-rich repeat-like protein TC272783 Zma-miR-77 Triosephosphate isomerase, cytosolic Acyl-CoA synthetase TC248390 TC273201 Zma-miR-70 Serine/threonine protein phosphatase PP1

exonuclease-like protein

TC270048, TC273304 Zma-miR-96 GTT1 glutathione S-transferase proline rich protein BE640624, TC251180 Zma-miR-28 Ethylene-responsive factor-like protein TC313437

Zma-miR-25 AP2 domain containing protein, expressed, zinc finger CCCH type domain-containing protein ZFN-like, putative, expressed, DNA binding protein, putative, expressed

TC252270, TC260832, TC270317, TC270318, TC322117

Table 4– Novel miRNAs in maize kernel germination.

miRNA Predicted function Target genes in the maize ear

kernel

Zma-miR-69 Transporter-related-like; Prpol; protein kinase domain containing protein; expressed protein TC261621, TC259769, TC259765 Zma-miR-41 Beta-galactosidase-like protein; 60S ribosomal protein L37a TC248580, TC269092, TC248552 zma-miR-42 Glucose-6-phosphate TC270622

Zma-miR-52 D-Lactate dehydrogenase-like protein TC265453

We found that half of the miRNAs targeting 5′ UTRs were perfectly base-paired, indicating that they might cleave their target mRNAs to down-regulate expression. Future experiments will reveal whether these target genes are destined for degrada-tion or transladegrada-tional repression.

Phytohormones regulate plant development via a complex signal response network, especially auxin, cytokinin, gibber-ellin, abscisic acid, and ethylene. In our study, 15 differentially expressed genes were involved in the auxin-signaling path-way in the course of the total developmental process (Table 2). MiR167 and miR160 were down-regulated after 22 DAP in developing viviparous kernels, implying that these miRNAs might be involved in receiving a phytohormone signal during the final stages of ear development. Auxin-responsive factor genes ARF3 and ARF6b were predicted to be targets of zma-miR167 and miR160. However, ARF3 and ARF6b were up-regulated after 22 DAP by microarray hybridization, and variation of differentially expressed genes from real-time PCR was more significant than that observed in the microarray analysis. Auxin response is regulated by various positive and negative feedback mechanisms during plant growth. ARFs regulate the transcrip-tion of early auxin-responsive genes, including AUX/IAA genes

[62], whereas AUX/IAA proteins interact with ARFs and repress their activities[63]. Auxin induces the targeted ubiquitination/ degradation of specific AUX/IAA proteins[64]and frees ARFs

from repression by AUX/IAA proteins. ARFs are bound to AUX/IAA negative regulators, thus maintaining the ARFs in an inactive state. The binding of auxin to TIR1-related F-box proteins enhances AUX/IAA destruction via the proteasome, liberating ARF activity[65–67]. We also found that the accumu-lation of ARF transcripts resulting from down-reguaccumu-lation of miR167/miR160 might enhance auxin response and thus en-hance maize germination. Moreover, Liu et al.[68]reported that the regulation of ARF10 mRNA stability by the miR160 miRNA implicated ARF10 in modulating ABA responsiveness during ear germination. More recently, it was shown that miR167 and miR160 are also regulated by ABA in rice, suggesting that they may also be involved in plant growth[69]. ABA down-regulation of miR167, which regulates auxin response factor 3 (ARF3) mRNA, suggests that ABA may cause increased ARF3 mRNA accumula-tion or translaaccumula-tional promoaccumula-tion. Because ARF3 is a positive regulator in both female and male reproductive functions[70,71], the accumulation of ARF3 by alleviating miR167/miR160 regula-tion would lead to earlier female and male development and, consequently, earlier plant maturation. We also deduced that miR167 may interact with miR160 via the common target genes to promote maize ear development. Our study elucidated the importance of the auxin-signaling pathway in ear development in maize. The results point to a role of auxin in germination-associated pathways and suggest that the interactions between Fig. 4– Detection and expression of candidate miRNAs miR167a (A), miR160b (B), and miR528a (C) at six developmental stages (days after pollination).

both auxin and ABA signaling pathways may contribute to the germination potential of seeds. An analysis of the function of key components of auxin signaling in relation to after-ripening, germination potential, and vigor may reveal novel roles for auxin in these processes. However, further research is warranted to elucidate the interactions of these pathways in ear development. Among the differentially expressed transcription factors related to the candidate miRNAs in maize ear germination (Table 3), there are 3 bZIP transcription factors, which regulate the expression of zeins. A gene encoding Ring-H2 zinc finger protein MZ00003207, which was up-regulated from 22 to 30 DAP, may mediate auxin- and salicylic-acid-inducible transcription

[72]. Furthermore, the MADS box-like protein MZ00022813, which had the lowest expression at 22 DAP, may bind to the promoters of genes regulated by multiple stimuli, such as light and hormones[73,74]. At 22 DAP, miR528 was up-regulated in maize germination, indicating that these miRNAs might be involved in receiving phytohormone signals. The homeobox–

leucine zipper family protein MZ00030111, a Ring-H2 zinc finger protein, a MADS box-like protein, and the putative laccase MZ00049071 were predicted as the targets of zma-miR528. It was concluded, therefore, that the bZIP transcription factors might play a significant role in kernel filling and response to hormones. In our study, a gene encoding ARF was up-regulated during kernel development, suggesting that it also plays a similar role in differentiation during maize embryogenesis. Moreover, many putative protein kinase genes were differentially expressed at various times, which were involved in signaling transduction pathway during maize ear development. For example, homeobox–leucine zipper family protein, a member of the LRR (leucine-rich repeat family protein) subfamily, might be required to increase cell size and the rate of embryonic

development. A gene encoding a homeobox–leucine zipper

family protein was up-regulated from 15 to 25 DAP, suggesting that this kinase might function in forming organs in the maize embryo. Therefore, we deduced that the accumulation of bZIP

Table 5– Differential expression of genes related to candidate miRNAs (miR167a/160b and miR528a) in maize ear germination.

ID Target gene DAP15/DAP10 DAP25/DAP10 DAP35/DAP10

MZ00014411 Putative auxin-responsive factor (ARF3) −0.500 0.200 1.300 MZ00028381 Auxin response factor 6b (Oryza sativa) 0.100 −0.800 −2.200 MZ00051866 Putative auxin response factor −0.100 −1.400 −1.400 MZ00013019 Homeobox protein (HAT3.1) −1.900 −0.075 0.280 MZ00030111 Homeobox–leucine zipper family protein −2.000 −0.200 0.750 MZ00034703 Putative NADH dehydrogenase −4.800 1.400 −0.200 MZ00005464 Cytochrome P450-like protein −1.800 0.030 −15.400 MZ00038106 Putative serine/threonine-protein kinase ASK2 −0.500 −0.900 −0.200 MZ00040613 Putative transcription factor MYB30 −0.500 −0.600 −0.600 MZ00001715 Transposase related −0.360 5.800 −3.200 MZ00047493 Ring-H2 zinc finger protein −0.070 −2.800 −19.800 MZ00022813 MADS box-like protein 3.000 0.200 −3.300 MZ00035616 Pyruvate, phosphate dikinase, chloroplast precursor −8.000 0.500 −0.300 MZ00049071 Putative laccase 1.560 2.300 −0.140 MZ00036850 Ethylene-responsive factor-like protein 1 0.560 −12.800 0.140

The ratio value (log

2

scale) of expression

A

B

C

D

E

F

G

H

I

Fig. 6– Patterns of gene expression in developing maize kernels. The blue line denotes all the candidate genes in developing maize kernels. The red line denotes the entire candidate genes based on the whole gene set of ZmB73.

transcripts, MADS box-like proteins, and putative laccase resulting from the down-regulation of miR528 might enhance auxin response and, in turn, seed germination in the final stage of seed development (after 22 DAP). However, further work is required to elucidate the functions of these protein kinases.

5.

Conclusions

By constructing a small RNA library and characterizing miRNA expression profiles in pooled maize ears at 10, 15, 20, 22, 25 and 30 DAP, at least 21 miRNAs were differentially expressed. qRT-PCR verification for miR528a and miR167a/miR160b indicat-ed that these miRNAs might be involvindicat-ed in ear development and germination. In addition, functional predictions of target genes indicated that most of these differentially expressed miRNAs tended to have target genes that were involved in signal transduction and cell communication, particularly those involved in the auxin-signaling pathway. The results of gene expression analysis of candidate germination-associated miRNAs performed by microarray hybridization with a maize genome array demonstrated the differential expression of genes involved in plant hormone signaling pathways. This suggested that phytohormones might play a critical role in the maize ear developmental process. We showed that in combina-tion with other miRNAs, miR528a regulates a putative laccase, a Ring-H2 zinc finger protein and a MADS box-like protein, whereas miR167a and miR160b regulate target genes including ARF (auxin response factor), a member of the B3 transcription factor family that is important for ear germination and physiology. Thus the small RNA transcriptomes and mRNA obtained in this study provide considerable insight into the expression and function of small RNAs in the development of viviparous kernels.

Acknowledgments

This study was supported by grants from the Educational Commission of Sichuan Province (No. 2006J13-039), the Doctoral Program Foundation of Institutions of Higher Education of China (No. 20095103120002), and the National Natural Science Founda-tion of China (No. 30900901).

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a _{No expression detected by real-time PCR.}

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