Genome-Wide Identification and Characterization of microRNAs in Developing Grains of Zea mays L.
Genome-Wide Identification and Characterization of microRNAs in Developing Grains of Zea mays L.
Dandan Li 0 1
Zongcai Liu 0 1
Lei Gao 0
Lifang Wang 0 1
Meijuan Gao 0 1
Zhujin Jiao 0 1
Huili Qiao 0 1
Jianwei Yang 0 1
Min Chen 0 1
Lunguang Yao 0 1
Renyi Liu 0
Yunchao Kan 0 1
0 Research Projects of Science and Technology Department of Henan Province , 112102110158
1 China-UK-NYNU-RRes Joint Libratory of insect biology, Nanyang Normal University , Nanyang, Henan , China , 2 Department of Botany and Plant Sciences, University of California , Riverside, California , United States of America
Editor: Heping Cao, USDA-ARS, UNITED STATES
Competing Interests: The authors have declared
that no competing interests exist.
The development and maturation of maize kernel involves meticulous and fine gene
regulation at transcriptional and post-transcriptional levels, and miRNAs play important roles
during this process. Although a number of miRNAs have been identified in maize seed, the
ones involved in the early development of grains and in different lines of maize have not
been well studied. Here, we profiled four small RNA libraries, each constructed from groups
of immature grains of Zea mays inbred line Chang 7–2 collected 4–6, 7–9, 12–14, and 18–
23 days after pollination (DAP). A total of 40 known (containing 111 unique miRNAs) and
162 novel (containing 196 unique miRNA candidates) miRNA families were identified. For
conserved and novel miRNAs with over 100 total reads, 44% had higher accumulation
before the 9th DAP, especially miR166 family members. 42% of miRNAs had highest
accumulation during 12–14 DAP (which is the transition stage from embryogenesis to nutrient
storage). Only 14% of miRNAs had higher expression 18–23 DAP. Prediction of potential
targets of all miRNAs showed that 165 miRNA families had 377 target genes. For miR164
and miR166, we showed that the transcriptional levels of their target genes were
significantly decreased when co-expressed with their cognate miRNA precursors in vivo. Further
analysis shows miR159, miR164, miR166, miR171, miR390, miR399, and miR529 families
have putative roles in the embryogenesis of maize grain development by participating in
transcriptional regulation and morphogenesis, while miR167 and miR528 families
participate in metabolism process and stress response during nutrient storage. Our study is the
first to present an integrated dynamic expression pattern of miRNAs during maize kernel
formation and maturation.
Maize kernel is one of the most important global staple foods. Elucidation of the molecular
mechanism of maize kernel development will be helpful not only to the production of
improved varieties of maize, but also for providing insight into seed development of other crop
angiosperms. Many genes are involved in the process of kernel maturation: ZmHOX,
ZmOCL1, KN1, ESR, BETL, and BAP are associated with the development of embryos and
]; BT, DU, SH, SU, and WX are involved in starch synthesis ; while O2,
FL2, and MC participate in storage proteins formation [
]. Development and maturation of
maize kernel involves meticulous and fine gene regulation at transcriptional and
post-transcriptional levels. Although genome-wide analysis of gene expression profiles during maize
kernel development has been performed, and different categories of genes have been identified
at various developmental stages, the mechanisms of kernel maturation remains elusive [
Small RNAs (sRNAs) are widely recognized as important and effective regulators of gene
expression in many eukaryotic organisms [
]. MicroRNAs (miRNAs) have attracted
much attention for their various roles in post-transcriptional regulation of protein coding
genes and their importance in many different pathways [
], such as in the development of
], shoots [
], leaves [
] and flowers [
], as well as cell fate [
Additionally, they were also found to play roles in responses to phytohormones [
], and environmental stresses [
Many studies have profiled maize miRNAs from different tissues as well as in plant under
different stress conditions [
12, 36, 45, 48–71
]. So far, 172 precursors and 321 mature miRNA
sequences of maize have been added to the miRNA database miRbase (Release 21; July 2014). No
study has yet investigated miRNAs that are involved in very early seed development, such as the
time after pollination to 10 days, or miRNAs with low abundance levels. Kang et al. studied
miRNAs in immature seeds by constructing a mixed RNA library from maize inbred line B73 seeds
collected 10–30 days after pollination (DAP) [
], Another recent study revealed miRNA
dynamics during maize grain filling in hybrid line Zhengdan 958 [
], which originated from Zheng 58
(maternal parent) and Chang 7–2 (paternal parent), but they focused on the miRNAs expressed
after the 17th DAP and miRNAs accumulating during the early stage were not included. In order
to identify miRNAs that participate in the early stage of kernel development and miRNAs present
in different lines of maize, we constructed four miRNA libraries from respective groups of maize
inbred line Chang 7–2 immature seeds collected 4–6, 7–9, 12–14, and 18–23 DAP. Our results
show a dynamic expression profile of miRNAs during maize seed development, giving us insight
into the roles of miRNAs during the formation and maturation of maize kernel.
Materials and Methods
Small RNA library construction and RNA sequencing
Maize (Zea mays L.) inbred line Chang 7–2 was planted at the farmland of Henan Agricultural
University (Zhengzhou, China). Immature seeds were collected 4, 5, 6, 7, 8, 9, 12, 14, 18, 20,
and 23 DAP, and ground into a fine powder in liquid nitrogen and processed using RNA
extraction buffer (100mM Tris-HCl, pH 8.0, 20mM EDTA, pH 8.0, 1.4M NaCl, 2.5% CTAB,
2% 2-mercaptoethanol) and an equal volume of phenol/chloroform/isoamyl alcohol (25:24:1).
The aqueous fraction was subsequently extracted two times using equal volumes of phenol/
chloroform/isoamyl alcohol (25:24:1) and chloroform. Total RNA was then precipitated in 5M
NaCl (2.5M final concentration) and equal volumes of isopropanol overnight at –80°C. The
integrity of the RNAs was verified on 1% agarose gel. Equal amounts of RNAs from each
sample were then mixed into these pools: 4–6 DAP, 7–9 DAP, 12–14 DAP, and 18–23 DAP. sRNA
library construction was carried out as previously described [
]. Briefly, 16- to 28-nt small
RNAs were gel-purified from 15% PAGE gel, 5’ and 3’ adaptors were added, and amplified by
RT-PCR using adaptor-specific primers. The PCR products were isolated and gel-purified.
Sequencing was performed on the Illumina platform (BGI Inc., China).
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Bioinformatic analysis of small RNAs and miRNA identification
Analysis of small RNA data was carried out as previously described [
]. Briefly, after
adapter sequences and low quality reads were removed, clean small RNA reads at least 18-nt or
longer were clustered into unique reads in each library. Unique reads that matched known
plant structural RNAs (rRNAs, tRNAs, snRNAs, and snoRNAs) were removed from further
consideration. Small RNA reads were then mapped to the maize genome sequence (release-5b
+ from ftp.maizesequence.org)  using SOAP2 [
]. Perfect matches were required. Unique
reads that had a redundancy of at least 10 copies in all libraries and were non-repetitive
(mapped to less than 20 positions in the genome) were used as anchor sequences. DNA
segments surrounding the anchor sequences were extracted in a stepwise fashion and were then
evaluated for the potential of being a miRNA precursor based on structural characteristics and
expression patterns [
]. A small RNA was deemed to be a novel miRNA only if it met the
strict criteria described by Ding et al. . Only those candidates with a minimal folding free
energy index (MFEI) > 0.85 were treated as novel miRNAs [
]. Candidate mature
miRNAs were classified into miRNA families based on their similarity to known plant miRNAs in
miRBase (Release 21)  and to each other. Target genes of candidate miRNAs were
predicted by using the predicted mature miRNAs as query to search annotated maize cDNAs with
]. The alignments between miRNAs and potential targets were calculated using a
position-dependent, mispair penalty system [
]. Each alignment was divided into two
regions: a core region that included positions 2–13 from the 5’ end of the miRNA and a general
region that contained other positions. In the general region, a penalty score of 1 was given to a
mismatch or a single nucleotide bulge or gap, and 0.5 to a G:U pair. Penalty scores were
doubled in the core region. A gene was considered a valid target if the alignment between the
miRNA and target met two conditions: (1) the penalty score is 4 or less; (2) the total number of
bulges and gaps is less than 2 [
Northern blot hybridization
Northern blot was performed as previously described [
]. Approximately 4 μg of low
molecular weight RNAs was separated on 15% polyacrylamide denaturing gels and then
transferred electrophoretically to Hybond-N+ membranes. Membranes were UV cross-linked and
baked for 2 hours at 80°C. DNA oligonucleotides complementary to miRNA sequences were
end labeled with γ-32P-ATP using T4 polynucleotide kinase (New England Biolabs,
Massachusetts, USA). Membranes were prehybridized for at least 1 hour and hybridized overnight using
Perfect hybridization buffer (Sigma-Aldrich, Missouri, USA) at 38°C. Blots were washed three
times (two times with 2 × SSC + 1% SDS and one time with 1 × SSC + 0.5% SDS) at 50°C. The
membranes were briefly air dried and then exposed to phosphorscreen and images were
acquired by scanning the films with a Typhoon phosphorimage analyzer (GE, Connecticut,
USA). Blots were reprobed with an RNA probe complementary to U6 snRNA to confirm
uniform loading. The Northern blot images were not quantified.
Validation of miRNA targets by using a transient expression system
The coding sequence (CDS) or 3’- Untranslated Regions (UTR) of target genes were cloned
from the cDNAs of Chang 7–2 seeds with oligo d(T)15 primers (PrimeScriptTM 21st Strand
cDNA Synthesis Kit, TaKaRa Dalian, China). The precursors of miRNAs were cloned from the
Chang 7–2 maize genome. pCAMBIA 2300S vector with a 35S promoter was used for
construction of overexpression vectors of miRNAs and their target genes.
The various constructs of target genes together with their putative miRNA precursors were
transiently coexpressed in N. benthamiana according to the method by Qikun Liu and Mingda
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]. The Agrobacterium tumefaciens (Agrobacterium) strain EHA105 was
transformed with the constructs pCAMBIA 2300S: miR166, pCAMBIA 2300S: Unknown CDS,
pCAMBIA 2300S: Unknown CDS+3’UTR, pCAMBIA 2300S: miR164, pCAMBIA 2300S:
NAM CDS, pCAMBIA 2300S: GFP. The transformed Agrobacterium suspension was
infiltrated into 3-week-old N. benthamiana leaves. 48 h after transfection, leaves of N. benthamiana
were washed three times with Diethy pyrocarbonate (DEPC)-treated water and dried with filter
papers, RNAs were extracted using TRIzol (Thermo Fisher Scientific, MA USA). The relative
expression levels of the target genes were measured with quantitative real-time PCR. N.
benthamiana 18S rRNA was used as an internal control for normalization. The primers used in
qRT-PCR are listed in S4 Table.
Quantitative Real-time PCR of miRNAs and target genes
RNAs were extracted from immature maize seeds collected 6, 9, 14, and 20 DAP. Genomic
DNA was digested using RNase-free DNaseI(Fermentas, Ontario, Canada). cDNA synthesis
and quantitative real-time PCR (qRT-PCR) of miRNAs were performed using the All-in-One™
miRNA qRT-PCR Detection Kit (GeneCopoeia, Maryland, USA). U6 was used as an internal
control. For qRT-PCR of coding genes, PrimeScriptTM 21st Strand cDNA Synthesis Kit
(TaKaRa, Dalian, China) and SYBR Green FS Universal SYBR Green Master (Roche Applied
Science, Indiana, USA) were used. PCR was carried out on the CFX96TM Real-Time PCR
Detection System (Bio-Rad, California, USA). The thermal cycling program consists of an
initial denaturation step at 95°C for 10 min, then 40 cycles at 95°C for 15 s, 55°C for 30 s, and
72°C for 30 s. Target gene abundance in each sample was normalized according to the U6
expression (for miRNAs) or TUBULIN expression (for coding genes) levels using the formula
ΔCt = Ct (target gene)–Ct (U6) or Ct (TUBULIN). The experiment was performed with three
biological repeats, each with three technical repeats. The primers used for qRT-PCR are listed
in S4 Table.
Results and Discussion
Deep sequencing of four small RNA libraries from maize seed
In order to study the roles of miRNAs involved in seed development, four sRNA libraries from
four time spans of immature seeds (4–6 DAP, 7–9 DAP, 12–14 DAP, and 18–23 DAP) of
maize inbred line Chang 7–2 were sequenced using Illumina 1G Sequencer. A total of
17,070,747; 17,303,264; 16,747,250; and 17,681,919 raw reads were obtained from the four
libraries, respectively (S1 Table). After removing the low quality reads and adaptor sequences,
the remaining clean reads from the four libraries were aligned to the maize genome. Sequences
that matched perfectly to the B73 genome (B73 RefGen_v3; Release 5b+ in June, 2013)
represented 66.29% to 78.38% of total reads, which indicated that the libraries were relatively intact.
Then, a total of 4,041,934; 4,174,092; 3,409,610; and 3,546,660 unique reads were obtained
from four libraries, respectively (S1 Table). The majority of the sRNAs were 20–24 nt long,
with the 24-nt sRNA being the most abundant, followed by the 22- and 21-nt classes (S1 Fig).
This result was consistent with recent reports of maize sRNAs [
] and similar to that of
Medicago truncatula [
], rice [
], peanut [
], and Arabidopsis [
], which suggest that the
majority of miRNAs are 24-nt in plants. Further analysis showed that approximately 0.01% of
unique reads matched to miRNAs, indicating that in maize grains, miRNAs account for a
proportion of ten thousandth in total RNAs. Analysis of nucleotide bias of miRNAs at each
position showed that the first nucleotide of miRNAs tended to be U (S2 Fig), which is typical of
most miRNAs. In addition, there was an average of 1.88%, 0.24%, 0.05%, 0.02%, and 2.29%
unique reads that matched other non-coding RNAs including rRNAs, tRNAs, snRNAs,
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snoRNAs, and siRNAs, respectively. Protein coding RNAs consisted of 22% of the reads, and
the remaining > 70% of the reads mapped to other sRNAs (Table 1).
Among the total unique sRNA reads, 12.18% was present in all four libraries. Libraries
made from seeds closer in age shared more sRNAs in common, while libraries with larger time
span differences shared relatively fewer sRNAs (S3 Fig). For example, the 4–6 DAP and 7–9
DAP libraries shared 15.30% of total sRNA reads, while the 4–6 DAP and 18–23 DAP libraries
shared only 12.18% (S3 Fig).
Conservation of miRNAs in maize
To contribute to our understanding of sRNA function and conservation, candidate miRNA
sequences were aligned to mature plant miRNAs and precursors. We found 111 miRNAs that
could be classified into 40 known miRNA gene families (S2 Table). Because miRNA precursors
are less conserved than other RNAs [
], and the minimal free energy index (MFEI) is an
important criterion for distinguishing miRNAs from other sRNAs, the strict criteria described
by Ding et al. [
] was used to predict the novel miRNAs. Then, a total of 196 unique miRNAs
(from 162 miRNA families) were identified as novel miRNAs according to sequence identity
(S3 Table). However, novel miRNAs were expressed at relatively low levels, with 6,752 Reads
per million (RPM) being the highest relative abundance and 10 RPM being the lowest
throughout the four libraries. Only 10% of the novel miRNAs had reads higher than 100 RPM.
Predicted target genes of miRNAs
We predicted the targets of novel maize miRNAs through computational methods. A total of
221 and 156 predicted targets were detected from 155 novel (from 125 miRNA families) and
108 conserved (from 40 miRNA families) miRNAs, respectively.
The predicted target genes of miRNAs with total reads over 100 RPM were related to
oxidoreductase activity, transcriptional regulation, transposon activity, stress response, and
development. On the contrary, target genes of miRNAs with total reads less than 100 RPM were
related to various biological processes (S2 and S3 Tables).
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Validation of target genes of miRNAs
To confirm the interaction between target genes and their cognate miRNAs in vivo, two
miRNAs, miR166 and miR164 with higher expression in the early development of maize kernel
were chosen. Given the miR164 target sites was located in the coding sequence (CDS) of No
apical meristem (NAM) gene, the overexpression vectors of NAM CDS as well as the precursor
of miR164 were constructed and subsequently coinoculated into N. benthamiana leaves.
Results showed that the relative expression levels of the NAM transcripts decreased
significantly when the precursor of miR164 was expressed (Fig 1A), which demonstrated that
miR164 can reduce the abundance of its predicted target gene, probably through mediating the
degradation of the NAM transcripts.
The target site of miR166 was located in the 3’-UTR of an uncharacterized gene (Unknown).
The interaction of miR-166 with this unknown gene was also investigated by the same method
as with miR164. Detected expression levels of the unknown gene decreased significantly when
the precursor of miR166 was expressed (Fig 1B), suggesting that miR166 can reduce the
expression level of this unknown gene through interaction with the 3’-UTR region.
Expression pattern of miRNAs showed that different miRNA families might play dominant roles at distinct developmental stages in maize seed
Maize grains take around 35 days to fully mature, and 10–15 DAP is the critical transition
stage of maize seed development. Before the 15th DAP, embryo development is focused on
formation of the tissues and organs, while storage of nutrients in the kernel begin after the 10th
]. From the 15th DAP onward, the accumulation of storage nutrients is accelerated
]. We profiled the miRNA abundance from four developmental time spans of maize
immature seeds (4–6 DAP, 7–9 DAP, 12–14 DAP, and 18–23 DAP). We chose 21 miRNAs with
significant expression variations across the four developmental time spans for further analysis.
The expression of six miRNAs were verified by Northern Blot and were consistent with the
sequencing results (Fig 2), while the others had weak or no hybridization signals most likely
due to low abundance as seen in the low sequencing reads. In addition, the expression pattern
of 14 miRNAs at four time points (6 DAP, 9 DAP, 14 DAP and 20 DAP) during maize seed
Fig 1. Coexpression of miRNA precursors and their target genes in a transient expression system in N. benthamiana cells. (A) Relative expression
levels of NAM gene coexpressed with miR164 precursor in N. benthamiana. (B) Relative expression levels of unknown gene coexpressed with miR166
precursor in N. benthamiana. Target genes were also coexpressed with an unrelated GFP construct as a control. Tobacco 18s rRNA was used as an internal
control for normalization.
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Fig 2. Northern blot analysis of selected maize miRNAs. Maize U6 RNA was used as an internal control.
DAP: days after pollination.
development were also verified by qRT-PCR. With the exception of miR166, whose expression
did not vary across the four stages, and miR169, miR172, miR393, and miR395, which all had
relatively more expression at the 6th DAP, the others were consistent with the sequencing data
(Fig 3). The RNA libraries prepared for sequenceing were generated from mixed samples of
seeds form different days during development, but here we used single DAP samples to detect
the expression of miRNAs, which might explain the discrepancies.
Since miRNAs with higher expression levels suggest their fixed regulatory roles during the
miRNA evolution, we chose conserved miRNA family members and miRNAs with total reads
over 100 RPM for further analysis, and then 109 miRNAs (44 families) were filtered. According
to the criteria described by Jin et al. [
], the expression pattern of miRNAs were categorized in
six groups (Table 2). Although the study in Zhangdan 958 revealed that a large number of
miRNAs accumulated more at 25 DAP [
], we found that only 16% of the miRNAs had more
accumulation 18–23 DAP, and the remaining 84% of miRNAs had higher accumulation before
the 14th DAP.
Group e, the miRNAs with the highest expression at 12–14 DAP, formed the largest group
with a percentage of 42%, but their total reads were relatively lower. This group includes 11
conserved and 7 novel miRNA families, such as the miR169, miR171, miR172, miR393,
miR395 and miR827 families. Target genes of miR169, miR171 and miR172 families are
transcription factors; and target genes of miR393, miR395 and miR827 families encode transporter
related proteins (S2 Table), which are involved in signal transductions. The expression pattern
of all miRNAs, with the exception of the miR827 family, and their target genes were negatively
correlated (Fig 3B). The accumulation of these miRNAs at 12–14 DAP indicate that they might
play roles in transcriptional regulation and signal transduction during the transition from
embryogenesis to nutrient storage of maize kernel.
We found that miR159, miR164, miR166, miR171, miR390, miR393, and miR529 families
all accumulated to high levels during the very early stage of development (4–6 DAP), especially
miR166. Kang et al., also found that miR166 was highly expressed in developing seeds [
they did not reveal the exact stage. Here, we found that miR166 had highest expression at the
very early stage of seed maturity in Chang 7–2. This differs from Zhengdan 958, the offspring
of Zheng 58 (maternal parent) and Chang 7–2 (paternal parent), from which miR166 had
higher accumulation after 25 DAP [
Target genes of miR159, miR166, miR171, and miR529 are transcription factors (S2 Table).
The expression profiles of miRNAs and their target genes at four time points of maize kernels
development were detected by qRT-PCR. Results show that miR159, miR166, miR171, and
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Fig 3. Relative expression levels of 14 miRNAs and their target genes at four time points during maize seed development. U6 and TUBULIN were
used as internal controls for miRNAs and target genes, respectively. DAP: days after pollination. Maize miRNAs are indicated by dark gray bars; target genes
are indicated by light gray bars.
miR529 had relatively higher expression before the 10th DAP, which corresponded to the
deepsequencing data, while their target genes had opposite expression trends, with more accumulation
after the 14th DAP (Fig 3A). miR166 was predicted to target basic-leucine zipper (bZIP) genes in
], which could regulate many processes like seed maturation, stress signaling, and
flowering timing [
]. In Arabidopsis, miR166/165 targets class III homeodomain leucine zipper
(HD-ZIP III) transcription factors, which determine the fate of the shoot apical meristem (SAM),
AGO10 acts as a decoy and sequesters miR166/165 from AGO1, thus preventing the silencing of
the HD-ZIP III genes and resulting in defective SAM [
]. Here we found that the target gene of
miR166 was an uncharacterized gene. The accumulation of miR166 in the early stage and the
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18–23 DAP RPM
a, miRNAs whose abundance increased linearly from 4 to 23 DAP
b, miRNAs whose abundance decreased linearly from 4 to 23 DAP
c, miRNAs with highest expression at 4–6 DAP
d, miRNAs with highest expression at 7–9 DAP
e, miRNAs with highest expression at 12–14 DAP
f, miRNAs with highest expression at 18–23 DAP
* denotes the miRNAs originates from the other strand of the miRNA:miRNA* duplex.
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corresponding down-regulated expression of its target gene seen in our results indicate that it
might play roles in transcriptional regulation in the embryogenesis of maize kernel.
Target genes of miR164 encode No apical meristem (NAM) proteins (S2 Table), The NAM
family genes encode transcription factors that play critical roles in boundary formation and
lateral organ separation, which is important for proper leaf and flower patterning [
function of miR164 in posttranscriptional regulation of NAM genes is conserved in many plants
]. Our results showed that miR164 has higher expression during early development of
maize seed while NAM expression is low, and the NAM gene has higher expression during the
latter stages (Fig 3A). The early stage accumulation of miR164 indicates that it might play roles
in the embryogenesis of maize kernel through silencing NAM genes.
Conserved miRNAs that accumulated more in the late developmental stage of maize seed
include miR156, miR167, miR398, and miR528 families. Expression of miR156 increased
linearly and was the highest at 18–23 DAP, which was consistent with the results seen in Zhengdan
], as well as in rice [
], wheat [
] and barley [
]. The expression pattern of the
miR167 family varied; some variants had highest expression level at 12–14 DAP, while others
increased linearly and had highest accumulation at 18–23 DAP. Variants that originated from
different regions on the same chromosome had differential expression patterns, similar to the
results seen in Zhengdan 958 [
]. Further analysis showed that the target gene of miR167
encodes a protein of monocopper oxidase (MCO) protein (S2 Table). This was different from
studies which predicated the target genes encoded auxin response factors (ARF) [
45, 99, 100
The discrepancy may be attributed to different criteria used for target prediction; we had used
more strict criteria that eliminates mismatches, bulges, or gaps between miRNAs and their
target genes. Nucleotides 1–21 of miR167 are fully complementary to the cDNA of MCO, but
nucleotides 3–20 of miR167 are only nearly complementary to the cDNA of ARF with one
mismatch. In the roots and developing ears of maize, miR167 exhibited a reverse expression
pattern to ARF [
]. Here we found that the expression pattern of miR167c was consistent
with the target gene MCO during maize seed development (Fig 3C). The commonly known
role of miRNAs include is regulating gene expression by repressing translation or directing
sequence-specific degradation of complementary mRNAs. But some miRNAs were found to
induce gene expression through complementarity to the promoter sequence of target genes
. Further analysis showed that miR167 has no sequence complementarity to the promoter
of MCO genes. Whether MCO gene is a bona fide target of miR167, and if so, by which
mechanism miR167 regulates MCO remains to be eluciated. Liu et al. found that from 15–25 DAP,
the majority (60%) of differentially expressed genes were related to metabolism, and many of
them were up-regulated [
]. Our results show that miR167 has higher accumulation during
the stage of nutrient storage, indicating that miR167 might be involved in the metabolism
regulation of seed maturity by regulating the expression of the MCO gene.
Another miRNA family which showed highest accumulation in the late stage of maize kernel
development was miR528, with highest expression at 18–23 DAP, which was consistent with the
results of its filial line Zhengdan 958 [
]. Recent studies showed that miR528 is significantly
repressed during low nitrate conditions in maize roots and shoots [
], while in Triticum.
dicoccoides, miR528 was down-regulated in leaves during drought stress [
], pointing to the role of
miR528 in stress response. The candidate target gene of of miR528 encodes antifreeze protein
(AFP), and the expressions of miR528 and AFP gene both increased in latter stages during maize
seed development (Fig 3C). Further analysis revealed that miR528 has no sequence
complementarity to the promoter region of AFP genes, which indicates that the expression of AFP gene
might be influenced by other factors in addition to miR528. The accumulation of miR528 in the
late development of maize kernel suggests that it might participate in the control of stress
responses during the process of nutrient storage by regulating the expression of AFP gene.
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Fig 4. A model of putative roles of miRNAs and their target genes involved in maize grain
In conclusion, conserved miRNA families that accumulate to higher levels during the early
stage of maize seed development such as miR159, miR164, and miR166 might play roles by
participating in transcriptional regulation and morphogenesis. Conserved miRNA families
with higher expression at the transitional stage such as miR169, miR171, and miR393 might
play roles in transcription regulation and signal transduction. Finally, the miRNA families with
higher expression levels in the latter stage of nutrient storage such as miR167 and miR528
might participate in metabolism and stress response (Fig 4).
We studied the expression profile of miRNAs during maize seed development using sRNA
deep sequencing, Northern blot and qRT-PCR analysis. We identified 111 conserved miRNAs
(from 40 miRNA families) and 196 novel miRNAs (from 162 miRNA families) in the
immature grains of maize. 44% of the miRNAs had higher accumulation before the 10th DAP, 42%
had highest expression at 12–14 DAP, and only 14% miRNAs had higher abundance at 18–23
DAP. A total of 377 target genes were predicted from 165 miRNA families, the interaction
between miR164, miR166 and their target genes were confirmed in vivo. miR159, miR164,
miR166, miR171, miR390, miR399, and miR529 families might play roles in the embryogenesis
of maize grain by participating in transcriptional regulation and morphogenesis, while miR167
and miR528 families might play roles in the process of nutrient storage by participating in the
metabolism process and stress response. Our study is the first to reveal an intact dynamic
expression profile of miRNAs during maize seed development.
S1 Fig. Length distribution of small RNAs from four libraries.
S2 Fig. Nucleotide bias at each position in miRNAs among the four small RNA libraries. A,
B, C, and D represented the libraries made from seeds cellected 4–6 DAP, 7–9 DAP, 12–14
DAP and 18–23 DAP, respectively.
S3 Fig. Common and specific unique reads among the four small RNA libraries. 5d: 4–6
DAP, 7d: 7–9 DAP, 12d: 12–14 DAP, 18d: 18–23 DAP.
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S1 Table. Summary of high-throughput small RNA sequencing.
S2 Table. Information and target genes of conserved miRNAs in the developing seeds of
S3 Table. Information and target genes of novel miRNAs in the developing seeds of maize.
S4 Table. Primer sets used in quantitative real-time PCR of miRNAs and target genes.
We thank Dr. Jihua Tang for providing the immature grains of Zea mays inbred line Chang
7–2. We also thank Dr. Guifeng Wei for assistance with the bioinformatics analysis.
Conceived and designed the experiments: RYL YCK. Performed the experiments: DDL ZCL
LFW MJG ZJJ HLQ JWY MC. Analyzed the data: LG DDL. Wrote the paper: DDL LGY YCK.
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2013; 25(9):3212–27. Epub 2013/09/24. doi: 10.1105/tpc.113.115592 PMID: 24058158; PubMed
Central PMCID: PMC3809528.
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