Dual transcriptome analysis reveals insights into the response to Rice black-streaked dwarf virus in maize
Journal of Experimental Botany
Dual transcriptome analysis reveals insights into the response to Rice black-streaked dwarf virus in maize
Yu Zhou 1 2
Zhennan Xu 1
Canxing Duan 2
Yanping Chen 0
Qingchang Meng 0
Jirong Wu 0
Zhuanfang Hao 2
Zhenhua Wang 1
Mingshun Li 2
Hongjun Yong 2
Degui Zhang 2
Shihuang Zhang 2
Jianfeng Weng 2
Xinhai Li 2
Björn Usadel, RWTH Aachen University
0 Jiangsu Academy of Agricultural Sciences , Zhongling Street, Xuanwu District, Nanjing, Jiangsu Province 210014 , China
1 College of Agronomy, Northeast Agricultural University , Mucai Street, XiangFang District, Harbin, Heilongjiang Province 150030 , China
2 Institute of Crop Science, Chinese Academy of Agricultural Sciences , Zhongguancun South Street, Haidian District, Beijing 100081 , China
Maize rough dwarf disease (MRDD) is a viral infection that results in heavy yield losses in maize worldwide, particularly in the summer maize-growing regions of China. MRDD is caused by the Rice black-streaked dwarf virus (RBSDV). In the present study, analyses of microRNAs (miRNAs), the degradome, and transcriptome sequences were used to elucidate the RBSDV-responsive pathway(s) in maize. Genomic analysis indicated that the expression of three non-conserved and 28 conserved miRNAs, representing 17 known miRNA families and 14 novel miRNAs, were significantly altered in response to RBSDV when maize was inoculated at the V3 (third leaf) stage. A total of 99 target transcripts from 48 genes of 10 known miRNAs were found to be responsive to RBSDV infection. The annotations of these target genes include a SQUAMOSA promoter binding (SPB) protein, a P450 reductase, an oxidoreductase, and a ubiquitin-related gene, among others. Characterization of the entire transcriptome suggested that a total of 28 and 1085 differentially expressed genes (DEGs) were detected at 1.5 and 3.0 d, respectively, after artificial inoculation with RBSDV. The expression patterns of cell wall- and chloroplast-related genes, and disease resistance- and stress-related genes changed significantly in response to RBSDV infection. The negatively regulated genes GRMZM2G069316 and GRMZM2G031169, which are the target genes for miR169i-p5 and miR8155, were identified as a nucleolin and a NAD(P)-binding Rossmann-fold superfamily protein in maize, respectively. The gene ontology term GO:0003824, including GRMZM2G031169 and other 51 DEGs, was designated as responsive to RBSDV.
Degradome; maize; miRNA; Rice black-streaked dwarf virus; transcriptome; virus-response
Maize rough dwarf disease (MRDD) is a viral disease and 2012
(Meng et al., 2008; Su et al., 2008; Zhang, 2010;
of maize that occurs worldwide, but can be particularly Tao et al., 2013a; Lu et al., 2014; )
. Symptoms of MRDD
severe in the maize-growing regions of China (Meng typically include dwarfed plant height, malformed tassels
et al., 2008; Su et al., 2008; Zhang, 2010). Yield losses of with no pollen, small ears or failure of heading, and green
30–100% due to widespread severe infections occurred in leaves that appear rough due to waxy enations
(Tao et al.,
the Yellow and Huai River valleys in China between 2008 2013a,b)
Abbreviations: MRDD, maize rough dwarf disease; RBSDV, Rice black-streaked dwarf virus; SBPH, small brown planthopper; RSV, Rice stripe virus; qRT-PCR,
quantitative real-time PCR; DAI, days after inoculation; DEGs, differentially expressed genes; CSL, CESA-like.
In China, MRDD is thought to be caused by Rice
blackstreaked dwarf virus (RBSDV), which is transmitted in a
persistent manner by the small brown planthopper (SBPH,
(Zhang et al., 2001)
. RBSDV belongs
to the genus Fijivirus in the family Reoviridae, and is
composed of 10 genomic double-stranded RNA (dsRNA)
segments (S1–S10), which encode 13 proteins
Lovisolo, 1977; Wang et al., 2003)
. The pathogenic pathway
involving the functions of the virus proteins and interaction
proteins has been partially determined in rice and maize. For
example, P5-2 (encoded by the second open reading frame,
ORF, of S5) is a non-structural protein that can be
specifically targeted to chloroplasts
(Liu et al., 2015)
. P7-2 (encoded
by the second ORF of S7) might be a viral F-box protein that
is referred to the ubiquitination pathway during the
interaction with plant SKP1 (a core subunit of SCF ubiquitin ligase)
(Wang et al., 2013)
Several microRNAs (miRNAs) that are related to disease
symptoms are known to be affected by viral infection in plants.
In previous studies, the expression of miRNAs 156, 160, 164,
166, 169, and 171 were found to be altered in a manner
correlated with the symptoms of Tobacco mosaic virus (TMV)
disease in Nicotiana tabacum (N.t.)
(Bazzini et al., 2007)
In addition, P1/HC-Pro, which is the Turnip mosaic virus
(TuMV)-encoded RNA-silencing suppressor, interfered with
the activity of miR171 (also known as miRNA39) by
suppressing RNA silencing during the infection of Arabidopsis
with TuMV (Kasschau et al., 2003). ARGONAUTE1 (AGO1)
mRNA levels are reduced when endogenous miR168
expression is induced by viruses infecting plants (Varallyay et al.,
2010). In subsequent work, when the RBSDV-responsive
miRNAs and the transcriptome were characterized in rice
leaves and roots from healthy rice plants or those infected
with RBSDV, the expression of 14 miRNAs in leaves and 16
miRNAs in roots changed significantly. A total of 104
target transcripts were responsive to RBSDV infection 1 month
post-infection, when RBSDV-inoculated rice began to show
symptoms of rice black-streaked dwarf disease (RBSDD)
(Sun et al., 2014)
During the response to Rice stripe virus (RSV), the
expression of genes for peroxidase biosynthesis, leucine-rich repeat
(LRR) receptor-like protein kinase, a pathogenesis-related
protein, a glycine-rich cell wall structural protein, xyloglucan
hydrolase, and cellulose synthase-related genes were affected
(Zheng et al., 2013)
. The expression profile of plants
with MRDD demonstrates that the expression of various
disease resistance-related genes, cell wall synthesis genes,
and development-related genes are dramatically altered at
the stage when white streaks appear on the topmost newly
expanded leaf (Jia et al., 2012). Maize can be infected by
RBSDV at any growth stage, but infections at the seedling
stage can be especially serious. In spite of this, a combined
analysis of the miRNA-degradome and the transcriptome
has not previously been reported for responses to RBSDV
infection during early growth stages of maize.
In order to investigate the miRNA-regulated
network response to RBSDV during early stages of
infection, deep sequencing of miRNAs, the degradome, and the
transcriptome were performed to determine which genes are
the targets of specific miRNAs, and to elucidate the
molecular pathway of RBSDV-infection in maize plants. Elucidation
of the molecular response to RBSDV infection was achieved
by analysis of the expression patterns of genes that are the
targets of miRNAs and analysis of the transcriptome at the
maize V3 (third leaf) stage.
Materials and methods
Plant materials and inoculation with RBSDV
Seeds of B73, a highly susceptible maize inbred line, were sown
in pots in a field in the natural environment of Nanjing, Jiangsu
Province, China. Two weeks later, each seedling at the third leaf
(V3) stage was exposed for 3 d in inoculation chambers to 100 small
brown planthoppers (SBPH, Laodelphax striatellus) that were 1%
viruliferous for RBSDV. The SBPH were removed from leaves on
the third day. At the same time, other B73 maize seedlings at the
V3 stage were exposed to virus-free SBPH as controls. Viruliferous
SBPH for inoculation were collected from rice fields in Nanjing,
Jiangsu Province, China. The virus-free SBPH were propagated for
many generations by feeding them on plants that were not infected
with RBSDV or RSV. Untreated maize plants were grown under the
same conditions as control plants. There were three technical
replicates for each of the three treatments: viruliferous SBPH, virus-free
SBPH, and untreated. Leaves were collected at 0 d (control, B0),
1.5 d (viruliferous, BP1.5; virus-free, BN1.5), and 3 d (viruliferous,
BP3; virus-free, BN3) after inoculation. Leaves for qRT-PCR
verification in three pathways were collected at V3a (1.5 d), V3b (3 d),
V6 (six-leaf stage), V9 (nine-leaf stage) and V12 (12-leaf stage) after
inoculation with viruliferous or virus-free SBPH. There were three
biological replicates for each of the sequencing samples B0, BN1.5,
BP1.5, BN3, and BP3 in the transcriptome sequencing, and the
correlation (R2) between the three biological replicates was calculated.
qRT-PCR labeling of a TaqMan® probe specific for RBSDV-S2
(Supplementary Table S1 at JXB online) was used to confirm
successful infection at 1.5, 3, 6, and 20 d after inoculation (DAI). Three
technical replicates were performed for detection of viral infection.
When all the seedlings had reached the V4 (fourth leaf) stage, they
were transplanted to the field and grown inside insect-proof netting.
By 1 month after transplanting, all the plants had reached the VT
(tasseling) stage, and the rates of infection were determined (=
number of plants with MRDD symptoms/number of plants inoculated).
Leaves with or without MRDD symptoms were then collected to
investigate the characteristics of the virus particles and
cytological variation among plants by transmission electron microscopy
(H-7500, HITACHI, Japan). Images were recorded using a Gatan
832 CCD camera (Gatan Inc., Pleasanton, CA, USA).
RNA extraction, library construction and sequencing
For every RNA-seq library, five plants were combined per sample.
Total RNA was extracted using TRIzol® Reagent (Invitrogen, CA,
USA) following the manufacturer’s procedure. Total RNA quantity
and purity were analyzed using a Bioanalyzer 2100 and RNA 6000
Nano LabChip Kit (Agilent, CA, USA) with RIN number >7.0.
Approximately 1 μg of total RNA was used to prepare a small RNA
library according to the TruSeq Small RNA Sample Prep Kit
protocol (Illumina, San Diego, USA). Single-end sequencing (36 bp)
was then performed on an Illumina HiSeq2500 at the facilities of
LC-BIO (Hangzhou, China), following the manufacturer’s
Approximately 20 μg of total RNA were used to prepare the
degradome library. First, poly (A)+ RNA was used as input RNA
and annealed with biotinylated random primers. These biotin-tagged
RNA fragments were then captured on streptavidin. Those RNAs
containing 5´-monophosphates were then ligated with a 5´ adaptor.
First-strand cDNA was then synthesized and the PCR product was
amplified. Libraries were sequenced using the 5´ adapter only,
resulting in the sequencing of the first 36 nucleotides of the inserts that
represented the 5´ ends of the original RNAs. We then performed
single-end sequencing (36 bp) on an Illumina HiSeq2500 at the
facilities of LC-BIO (Hangzhou, China) following the manufacturer’s
Approximately 15 μg of total RNA from leaves that had been
inoculated with either viruliferous or RBSDV-free SBPH were used
to prepare the transcriptome library. Poly-A containing RNA was
isolated from total RNA using Oligo (dT) magnetic beads. The
mRNAs were broken into fragments in fragmentation buffer.
Firststrand cDNA was then synthesized using random hexamers with the
mRNA template. The second-strand was synthesized in a reaction
mixture including buffer, dNTPs, Rnase H, and DNA polymerase
I. Fragments were purified using the Qiaquick® kit and eluted with
EB buffer (10 mM Tris·Cl, pH 8.5), and then termini were repaired.
The fragments were size-selected using agarose gel electrophoresis,
and then amplified by PCR. Sequencing of the constructed library
was then performed. The raw data have been uploaded into the
NCBI database SRA (PRJNA299369). The SRR numbers for
transcriptome sequencings were from SRR2758148 to SRR2758177.
Two small RNA libraries, one degradome library, and fifteen
RNA-Seq libraries were constructed from maize infected with either
viruliferous or virus-free SBPH. Fifteen RNA-Seq libraries were
constructed from the three biological replicates of the leaf tissue
samples B0, BN1.5, BP1.5, BN3, and BP3. Two small RNA
libraries were constructed from the mixed RNAs obtained from the three
technical replicates at 3 DAI with viruliferous or virus-free SBPH.
The degradome library was also constructed from mixed RNAs
obtained from the three technical replicates sampled at 3 DAI with
viruliferous or virus-free SBPH. The SRR numbers for the miRNA
and degradome sequencings were SRR2763387, SRR2763388, and
Sequence data analysis
Adapters and low-quality reads were filtered to obtain raw sequence
reads. Unique sequences 18–26 nucleotides in length were mapped to
specific species’ (such as Medicago truncatula or Vitis vinifera)
precursors in miRBase 20.0 using blast searches to identify known
miRNAs and novel 3p- and 5p-derived miRNAs. The unique sequences
that mapped to a hairpin arm of a specific species of mature miRNA
were identified as known miRNAs. The unique sequences mapping
to the other arm of a known specific species precursor hairpin
opposite the annotated mature miRNA-containing arm were considered
to be novel 5p- or 3p-derived miRNA candidates. The remaining
sequences were mapped to other selected species precursors (with
the exclusion of specific species) in miRBase 20.0 by blast, and the
mapped pre-miRNAs were used as further blast queries against
the specific species genomes to determine their genomic locations.
Thus, miRNAs in the above two categories were defined as known
For digital sequencing data, the adaptors, empty tags (no tag
sequence between the adaptors), low-quality tags (tags containing
one or more unknown nucleotides ‘N’), and tags with a copy number
equal to one were removed from the raw data to obtain 50-bp clean
tags. All clean tags were mapped to the assembled transcriptome
data generated by RNA-Seq. The number of tags corresponding to
each gene was calculated and normalized to the RPKM (the
number of transcripts per million clean tags per kilobase) to analyze the
expression of DEGs. The significance threshold was set at 0.05 to
identify genes expressed differentially at individual time points.
De novo transcriptome was assembled from transcriptome
sequence data. More than 4G of data were assembled using Trinity
(Bankar et al., 2015)
. Sequence homologies for the assembled
Trinity contigs were identified by local blastall against sequences in
the NCBI non-redundant (nr) protein database and the Swiss-Prot
database (E-value <1e-10). Genes were thus tentatively identified
according to the best hits against known sequences. In the present
study, miRNAs and genes with log2FC (fold-change) greater than
one and P-value less than 0.01 were considered to have altered
Verification by qRT-PCR
The validity of miRNA sequences and RNA-Seq were
verified by quantitative real-time PCR (qRT-PCR). Two miRNAs
(miR169i-p5 and miR8155), two target genes (GRMZM2G069316
and GRMZM2G031169), and eight DEGs (up-regulated:
GRMZM2G031790, GRMZM2G113191, GRMZM2G070620,
and GRMZM2G029912; down-regulated: GRMZM2G120619,
GRMZM2G057281, GRMZM2G155216, and GRMZM2G101664)
with differential expression at 1.5 and 3 DAI were validated using
qRT-PCR. First-strand cDNAs of miRNAs and genes were
synthesized using a miRcute miRNA First-Strand cDNA Synthesis Kit
(KR201) or Fast Quant RT Kit (KR106) (TIANGEN, China). The
qRT-PCR reaction was performed using Bio-Rad iQ5 following
the instructions for the miRcute miRNA qRT-PCR Detection Kit
(SYBR Green) or SuperReal PreMix Plus (SYBR Green) (FP205).
Three biological replicates were sampled and three technical
replicates of all reactions were performed on each sample. The 5S rRNA
(Lang et al., 2011)
(Zuo et al., 2015)
genes were used
as internal controls for miRNA and transcription level quantitation.
The expression from growth stages V3 to V12 of miR8155 and
target gene GRMZM2G031169, and DEGs relating to the metabolic
pathways zma01100 and zma01110 in the Kyoto Encyclopedia of
Genes and Genomes (KEGG) database were also verified by
qRTPCR. All primers are listed in Supplementary Table S13.
Inoculation of maize with RBSDV
The inoculation status of plants with RBSDV was confirmed
by qRT-PCR using RBSDV-S2 probe primers at 1.5, 3, 6,
and 20 DAI. RBSDV could be detected in maize plants that
had been inoculated at the V3 stage with viruliferous SBPH,
but not in the plants exposed to virus-free SBPH. Virus
content increased gradually as the maize plants grew (1.5, 3, 6,
and 20 DAI) (Supplementary Fig. S1a, b). MRDD
symptoms such as stunting, dark-green leaves and sheaths that
appear rough due to waxy enations, or failure of heading at
1 month after transplanting were evident on maize plants that
had been infected with viruliferous SBPH (Supplement Fig.
S1c). There were no diseased plants in the non-inoculated
group and no virus-free plants in the SBPH-infected group
(Supplement Fig. S1c). RBSDV particles with a diameter of
70–80 nm were observed in the cytoplasm of diseased leaves
(Supplement Fig. S1d). In addition, crystallized virus
particles were detected in the cytoplasm of diseased leaves at the
VT growth stage (Supplement Fig. S1e).
Response of known miRNAs to RBSDV in maize
A total of 13 175 409 and 11 065 903 raw reads were generated
from libraries prepared from maize leaf tissue that had been
grown after inoculation with BN3 (virus-free) or BP3
(viruliferous) vectors, respectively, and 2 615 920 and 1 888 049
raw unique reads were generated by deep sequencing
miRNAs from BN3 and BP3, respectively. Among the unique
miRNAs, sequences 21 and 24 nt in length were
predominant, and 21-nt sequences were the most abundant in these
two libraries (Fig. 1a).
Unique sequences of 18–25 nucleotides in length were
mapped to species precursors in miRBase 20.0 (http://
microrna.sanger.ac.uk/) by blast to identify known
miRNAs and novel miRNA sequences derived from 3´ (3p in
miRNA names) and 5´ (5p in miRNA names) ends. In
the two small RNA libraries from plants cultivated with
viruliferous or virus-free SBPH, 525 miRNAs
representing 123 known miRNA families and 299 novel miRNAs
were identified. The known and novel miRNAs from the
viruliferous and virus-free libraries with at least two-fold
change in expression (Log2 FC≥1) and at least 10 reads
in a dataset are shown in Supplementary Table S2. Three
non-conserved and 28 conserved miRNAs representing 17
known miRNA families were identified (Supplementary
Table S3). These 31 known miRNAs were detected on
chromosomes 1–9, and on the chloroplast and
mitochondrial genomes. The lengths of these miRNA precursors
varied from 25 to 334 nt (Supplementary Table S3). Three
non-conserved miRNAs (miR160c, miR167d-5p-1, and
miR167d-5p-3) were expressed at least three-fold lower
in the viruliferous maize than in the virus-free maize.
Among the conserved miRNAs, members of eight
families were highly abundant, while members of five families
were expressed at low levels. The expression patterns of
miRNAs from the miR166, miR167, miR169, and miR399
families were not completely uniform. The miR166b-5p,
miR167b, miR167d-5p-1, miR167d-5p-3, miR167e-3p,
miR169i-p5, and miR399c-5p miRNAs were expressed at
low levels, while miR166c-5p, miR167d-3p, miR169l-5p,
and miR399a-3p were highly expressed (Supplementary
Novel miRNAs in response to infection with RBSDV
Compared with the group of known miRNAs identified in
the library prepared from virus-free plants, 299 novel miRNA
sequences were identified in the library prepared from
virusinfected plants. Among these, 156 novel miRNAs were derived
from the 3´ ends of the pre-miRNAs, and the rest were derived
from the 5´ ends. Only 14 novel miRNAs (named miRp1-14)
showed at least a two-fold change in expression and at least 10
reads per dataset (Supplementary Table S4). These 14 novel
miRNAs were mapped to all maize chromosomes, except for
chromosome 9. The lengths of these 14 novel unique miRNA
sequences were either 20, 21, or 24 nt, and the majority were
21 and 24 nt in length. The lengths of these 14 novel unique
miRNA precursors ranged from 59 to 420 nt (Supplementary
Table S4). Five novel miRNAs (miRp1, miRp4, miRp10,
miRp11, and miRp14) were highly expressed with norm and
raw values in two libraries all greater than 10, and nine novel
miRNAs (miRp2, miRp3, miRp5, miRp6, miRp7, miRp8,
miRp9, miRp12, and miRp13) were expressed at low
levels with norm and raw values in two libraries lower than 10
(Supplementary Table S4).
miRNA target genes
To identify the target genes of the known and novel
miRNAs identified here, prediction of miRNA targets and
sequencing of the degradome were performed. A total of
107 raw reads and 4.05 × 106 unique raw reads were
generated from the viruliferous library for analysis of the target
genes for miRNAs. The software CleaveLane 3.0 was used
to identify known and novel miRNAs in the data generated
for target genes
(Addo-Quaye et al., 2009)
. A total of 3945
transcripts (prediction and sequencing) from 2823 genes for
633 miRNAs were predicted to be microRNA target genes. Fig. 2. Differential expression of the known miRNAs and target genes in
A total of 688 transcripts from 502 genes for 37 miRNAs virus-inoculated or virus-free maize. FC, fold change. Black bars represent
were identified in the degradome library (Supplementary expression of miRNAs; grey bars represent expression of target genes.
protein, and an NAD(P)-binding Rossmann-fold
superfamily protein (Supplementary Table S5). Three other miRNAs
(miR156e, miR169i-p5, and miR396a-5p) were
down-regulated (Fig. 2). Only one target gene each was identified for
miR156e and miR396a-5p, namely a SQUAMOSA
promoter-binding (SPB) protein and a growth-regulating
factor, respectively (Supplementary Table S5). For miR169i-p5,
37 target genes were detected, including a 60S acidic
ribosomal protein family, an abscisic stress-ripening protein, a
serine/threonine-protein kinase Rio1, and a ubiquitin-related
protein (Supplementary Table S5).
A total of 32 transcripts from 29 target genes for seven novel
miRNAs were predicted (Supplementary Table S6). These
target genes were related to nucleic acid binding, transferase
activity, zinc ion binding, and oxidation–reduction functions,
among others. However, target genes for novel miRNAs were
not identified in the degradome library. The expression levels
of 16 predicted target genes for seven miRNAs were affected
by infection with RBSDV according to RNA-Seq results,
and their targets included a protein kinase superfamily
protein and phototropin (Fig. 3, Supplementary Table S6). The
expression of five of these target genes changed significantly
(P<0.05), and three of the target genes for two of the
miRNAs were negatively regulated. GRMZM2G092123, a target
gene for miRp14, is annotated as a tetratricopeptide repeat
(TPR)-like superfamily member and was down-regulated by
1.67-fold (P=3.44 × 10–4).
The RBSDV-responsive transcriptome in maize
The numbers of differentially expressed genes (DEGs)
identified by transcriptome sequencing are shown in Table 1. A total
of 28 and 1085 DEGs were detected in the BP1.5–BN1.5 and
BP3–BN3 libraries, respectively, of which four up-regulated
DEGs (3-ketoacyl-CoA synthase, a bifunctional
monodehydroascorbate reductase and carbonic anhydrasenectarin-3
BP: inoculated with viruliferous small brown plant hopper (SBPH); BN: inoculated with virus-free SBPH; B0: day zero control; Significant DEGs:
|log2FC| > 1; P<0.01
precursor, a cytochrome P450 protein, and WAX2) and four
down-regulated DEGs (three chlorophyll A-B binding
proteins and one zinc finger family protein) were detected in
both BP1.5–BN1.5 and BP3–BN3 (Fig. 4, Supplementary
Table S7). The up-regulated DEGs were related to functions
including iron ion binding and fatty acid biosynthesis. The
expression of GRMZM2G070620, which was annotated
as a cytochrome P450 protein, changed most significantly
with log2FC values of 6.0191 and 2.2686 in BP1.5–BN1.5
and BP3–BN3, respectively. Three of four down-regulated
DEGs were annotated as chlorophyll A–B binding protein,
and the other was annotated as a zinc finger family protein
(Supplementary Table S7).
Dwarfing is one of the typical symptoms of MRDD;
accordingly, the expression of genes related to cell wall
development, such as cellulose synthase and pectinesterase,
lignin biosynthesis, and those related to plant stature, such
as gibberellin and auxin biosynthetic enzymes, was affected
in virus-infected plants. In BP3–BN3, the expression of
DEGs for pectinesterase, protein kinase, a probable
mannan synthase, CSLA1 (GRMZM2G105631), and a chitinase
family protein precursor was increased. The expression of
cellulose synthases, including CSLF 6 (GRMZM2G122277,
GRMZM2G110145) and CESA 3 (GRMZM2G025231),
declined significantly (Supplementary Table S8). In
virus-infected plants, the expression of pectinesterase
(GRMZM2G019411) and a high-light inducible protein
(GRMZM2G019807) also decreased significantly (P<0.01)
with log2FC values relative to uninfected plants of –1.1461
and –1.0275, respectively. The expression of two
ligninrelated genes (GRMZM2G169033 and GRMZM2G320786)
also increased significantly (P<0.01) with log2FC values
relative to uninfected plants of 3.2525 and 2.2729,
respectively. In BP1.5–BN1.5, the expression of only one
glycosyl hydrolase gene (GRMZM2G060837) related to cell
wall function changed significantly (log2FC value −1.3368,
P=1.83 × 10−05). These results showed that the behavior of
cell walls and the expression of genes related to the
function of cell walls were both influenced by RBSDV infection.
The decrease in the expression of cellulose synthase might be
one reason for the dwarfing symptoms observed in infected
plants. The expression of five gibberellin-related genes and
12 auxin-related genes was also altered significantly in BP3–
BN3 (P<0.01) (Supplementary Table S8). The functions of
gibberellin-related genes with altered expression included a
gibberellin receptor GID1L2, gibberellin 2-beta-dioxygenase,
and gibberellin 20-oxidase 2. Auxin-related genes with altered
expression included the auxin-induced protein 5NG4, an
auxin efflux carrier component, an auxin-repressed protein,
homologs of the rice auxin-responsive Aux/IAA gene family
member OsIAA, and an auxin-responsive SAUR gene family
Typically, plant leaves suffering from MRDD are dark green
and appear rough due to waxy enations
(Tao et al., 2013a,b)
The leaf symptoms could be due to photosystem damage or
to changes in the chloroplast. In our study, among 27
chloroplast-related DEGs, eight were up-regulated, and 19 were
down-regulated (Supplementary Table S6), of which three
(GRMZM2G024150, GRMZM2G005433, and AC190623.3_
FG001) are related to the photosystem. Because photosynthesis
takes place in chloroplasts, these organelles contain chlorophyll,
carotenoids, and cytochromes. In BP3–BN3 and BP1.5–BN1.5,
14 photosystem-related genes showed significantly suppressed
expression. Among these, one gene (GRMZM2G057281)
was significantly suppressed in both BP3–BN3 and BP1.5–
BN1.5, but the other 13 of these genes were only detected in
BP3–BN3. The expression of genes related to the functions of
chlorophyll, carotenoids, and cytochromes showed significant
alterations in BP3–BN3 and BP1.5–BN1.5. The expression of
three chlorophyll A–B binding proteins (GRMZM2G120619,
GRMZM2G057281, and GRMZM2G155216) was suppressed
in BP3–BN3 and BP1.5–BN1.5, and that of other
chlorophyllrelated genes was only detected in BP3–BN3. Except for the
expression of chlorophyllase-2 (GRMZM2G170734) with a
fold increase of 4.8974, the expression of all of the
chlorophyllrelated and carotenoid-related genes decreased. However, the
expression of cytochrome-related genes was also significantly
affected. The above results indicated that chloroplasts and
photosynthesis were affected by RBSDV infection through the
down-regulation of genes for chlorophyll A–B binding protein
(Supplementary Table S9).
The expression of genes related to plant hormone
biosynthesis, disease defense, or plant stress responses also often change
significantlyunderbioticstresses.Inthepresentstudy,theexpression of three pathogenesis-related genes (GRMZM2G072612,
GRMZM2G028928, and GRMZM2G108537), which
correspond to pathogenesis Gene Ontology (GO) terms GO:0009405
and GO:0009406, increased in BP3–BN3 (Supplementary
Table S10). Several identified DEGs were related to disease
defense and stress resistance functions, including stress
resistance signal transduction, and transcriptional regulation. The
resistance-related genes detected in the significant DEG
dataset included seven glutathione S-transferase genes, nine
peroxidase genes, five heat shock protein genes, two ferredoxin-nitrite
reductase genes and five chitinase genes (Supplementary Table
S10). DEGs related to signal transduction, such as an LRR
disease-resistance protein and protein kinases including a
lectin protein kinase, a receptor kinase, a serine/threonine-protein
kinase, and a tyrosine protein kinase, were also detected. The
expression of pathogenesis-related transcription factors was
RING finger and CHY zinc finger
domain-containing protein 1
U-box domain containing protein
also altered, and these included basic helix-loop-helix,
ethylene-responsive (ERF114), GRAS family, MYB family, heat
stress, HBP-1b, and WRKY family genes.
Protein degradation pathways such as the ubiquitin
proteasome system participate in multiple biotic and abiotic stresses. Our
results corroborated the hypothesis that the ubiquitin
proteasome system might be part of the response to RBSDV infection.
Through transcriptome analysis, three ubiquitin
biosynthesisrelated genes (GRMZM2G046848, GRMZM2G144782, and
GRMZM2G303964) with significantly altered expression were
detected in BP3–BN3 (Table 2). The expression of two of these
genes (GRMZM2G046848 and GRMZM2G144782) increased,
with log2FC values of 1.3561 and 1.0710, respectively, while
that of GRMZM2G303964 declined, with a log2FC value of
−1.7203. Each of these genes correspond to ubiquitin GO terms
(GO:0000151, GO:0004842, and GO:0016567, respectively) or
to the ubiquitin pathway (zma04120) in the KEGG database.
This result suggests that ubiquitin-related genes respond to
RBSDV infection in maize (Table 2).
To confirm the RNA-Seq results for the RBSDV-responsive
genes at different time points, the expression patterns of
eight DEGs (GRMZM2G120619, GRMZM2G057281,
GRMZM2G155216, GRMZM2G101664, GRMZM2G
031790, GRMZM2G113191, GRMZM2G070620, and
GRMZM2G029912) were validated by qRT-PCR in RNA
samples from leaves harvested at both 1.5 and 3 DAI. As
the results shown in Fig. 5a indicate, GRMZM2G120619,
GRMZM2G057281, GRMZM2G155216, and GRMZM2G
101664 were down-regulated at both 1.5 and 3 DAI. The
expression of GRMZM2G031790, GRMZM2G113191,
GRMZM2G070620, and GRMZM2G029912 increased at
1.5 d and 3 DAI with RBSDV.
Negatively regulated miRNAs target genes
Analysis of these miRNA degradomes and
transcriptomes indicated that most genes with altered expression
were enriched in GO terms related to the nucleus,
regulation of transcription and DNA templates, and DNA
binding (Fig. 6a). Genes related to photosynthesis in KEGG
were also enriched (Fig. 6b). To detect negatively regulated
miRNAs and their target genes, combined analysis of the
expression of miRNAs, the degradome, and the
transcriptome was performed. A total of 30 negatively regulated
genes, which are targeted by six miRNAs (miR169i-p5,
miR169l-5p, miR319b-p3, miR319b-p3-1,
miR319bp3-Pt, and miR8155), were identified (Supplementary
Table S5). Among these 30 genes, the expression of
only five (GRMZM2G069316, GRMZM2G057576,
GRMZM2G120329, GRMZM2G142093, and
GRMZM2G031169) changed significantly (P<0.05).
Furthermore, the expression of two target genes
GRMZM2G069316 (targeted by miR169i-p5) and
GRMZM2G031169 (targeted by miR8155) changed more
than 1.5-fold (|log2FC| > 0.58; P<0.05) (Supplementary
Table S5). GRMZM2G069316 was related to only one GO
term (GO:0005488//binding) (Fig. 7a). Thirteen DEGs
were detected for GO:0005488, which included
annotations for HEAT repeat family proteins, a lectin-like
protein kinase, a mitochondrial carrier protein, and a U-box
domain-containing protein component of ubiquitin ligase
(Supplementary Table S11). GRMZM2G031169 was
related to three GO terms (GO:0003824//catalytic activity;
GO: 0044237//cellular metabolic process; and GO:0050662//
coenzyme binding) (Fig. 7b). Fifty-one DEGs that were
detected were related to GO:0003824, and were annotated
as a 3-ketoacyl-CoA synthase, an alpha-amylase
precursor, an AMP-binding domain-containing protein, a protein
phosphatase 2C, a reticuline oxidase-like protein
precursor, and UDP-glucuronate 4-epimerase (Supplementary
Table S12). The same four DEGs were detected in each of
GO:0003824, GO:0044237, and GO:0050662, which were
annotated as a dehydrogenase/reductase SDR family
member 12, a dehydrogenase, and UDP-glucuronate
4-epimerase, respectively (Supplementary Table S12).
for the maize response to RBSDV, qRT-PCR was used to
validate two miRNAs, miR169i-p5 and miR8155, and their two
target genes, GRMZM2G069316 and GRMZM2G031169,
respectively. As shown in Fig. 5b, the expression of
miR169ip5 decreased, but that of miR8155 increased. Expression of
GRMZM2G069316, which is the target gene for
miR169ip5, increased both at 1.5 and 3 DAI with RBSDV. The target
gene for miR8155 (GRMZM2G031169) was down-regulated
at both 1.5 and 3 DAI. These results were consistent with
the results of analysis of sequence data for miRNAs and the
Metabolic pathway analysis at five maize growth stages
Based on miRNA and DEGs, the expression of genes involved
in KEGG metabolic pathways zma01100 and biosynthesis of
secondary metabolites (zma01110) were investigated at the
V3, V6, V9, and V12 maize growth stages. miR8155 was
upregulated at V3, V6, and V12, but down-regulated at V9. As
the target gene of miR8155, GRMZM2G031169 was
correspondingly regulated at these growth stages.The gene
ontology term GO:0003824, which includes GRMZM2G031169
and 51 other DEGs, mainly related to the two pathways
zma01100 and zma01110. Six DEGs are concerned with
photosynthesis or chlorophyll, which also connects with
the zma00196 pathway. Most of the genes in the pathways
zma01100, zma01110, and zma00196
(photosynthesisantenna proteins) were down-regulated, whilst seven genes
(GRMZM2G429118, GRMZM2G057281, GRMZM2G
162529, GRMZM2G436986, GRMZM2G108514, GRMZ
M2G035213, and GRMZM2G103773) were up-regulated
at V9. The expression of most DEGs in these pathway
reached their lowest levels at stage V6 (Fig. 8). These
findings demonstrate that the response to infection with RBSDV
mainly involved multiple maize pathways, such as zma01100,
zma01110 and zma00196.
RBSDV-responsive miRNAs and target genes in maize
Many studies have reported that small RNAs play
regulatory roles in the expression of numerous genes in plants
during plant growth, development, and stress responses
(Jones-Rhoades et al., 2006; Liu et al., 2014a; Xu et al., 2014;
Yan et al., 2015)
. Some studies have been published on the role
of small RNAs in plant responses to infection with viruses
(Bazzini et al., 2007; Tagami et al., 2007; Singh et al., 2012;
Xiao et al., 2014; Xu et al., 2014)
, but only a few in the family
Reoviridae. A previous study used deep sequencing to
characterize the small RNA profiles of rice plants infected with Rice
dwarf virus (RDV) or RSV
(Du et al., 2011)
. Seven putative
novel miRNAs (pn-miRNAs) with previously
uncharacterized precursor sequences were identified in rice in response to
RSV infection (Guo et al., 2012). Microarray profiling of rice
miRNAs expressed in response to Southern rice black-streaked
dwarf virus (SRBSDV) identified 56 miRNAs that were
regulated in response to this disease in rice plants. Analyses of
target genes indicated that the expression of four miRNA
families (miR164, miR396, miR530, and miR1846) was
positively or negatively correlated with that of their respective
targets, genes that were associated with symptom development.
However, the expression of other miRNAs was not correlated
with the expression of other genes, which implies that other
circumstances can affect the interactions between miRNAs
and their target genes
(Xu et al., 2014)
. The miRNAs and
their target genes expressed in response to RBSDV were
characterized in rice leaves and roots at 1 month following
inoculation with the virus
(Sun et al., 2014)
. In that study,
deep sequencing revealed that the expression of 14 miRNAs
in leaves and 16 miRNAs in roots was altered significantly
during the response to RBSDV infection in rice
(Sun et al.,
. However, the roles of miRNAs and their target genes
in response to RBSDV inoculation in an early maize
developmental stage (V3) have not previously been reported. In
our study, combined analysis of the expression of miRNAs
and their target genes by transcriptome sequencing revealed
RBSDV-response pathways in maize. Three non-conserved
and 28 conserved miRNAs representing 17 known miRNA
families and 14 novel miRNAs were identified among small
RNA sequence data (Supplementary Table S2). The
expression dynamics of three miRNA families in response to
RBSDV at the maize V3 stage were revealed.
In the first group of miRNAs, seven known miRNA families
(miR1432, miR319, miR408, miR4366, miR8155, miR9773,
and miR9774) were up-regulated in the maize library BP3–
BN3. In rice infected with RBSDV at a later developmental
stage, the expression of the miR1432 family increased in the
leaves but decreased in the roots
(Sun et al., 2014)
the expression of the miR408 family was reduced in both
leaves and roots
(Sun et al., 2014)
. In addition, other miRNAs
that are differentially expressed at the maize V3 stage, such as
miR319, miR4366, miR8155, miR9773, and miR9774, were
not detected in the later leaf and root stages in rice. These
discrepancies may be species-specific responses in maize
and rice, or due to differences in sampling time points after
RBSDV infection. miR1432 is thought to be involved in pollen
development and male sterility
(Yan et al., 2015)
as well as in
drought shock stress (Kantar et al., 2011) in rice. The target
gene of miR319, the transcription factor TCP1, is related to
the S RNA (NSs) of the Groundnut bud necrosis virus (GBNV)
(Goswami et al., 2012)
. Leaf-curling symptoms in
plants infected with Tomato leaf curl virus (ToLCV) might also
be associated with miR319 (Naqvi et al., 2010). Other targets of
miR319 might also be involved in the thickening of cell walls in
the fibrous bast material during the elongation phase in ramie
(Boehmeria nivea; Wang et al., 2014)
, and in cell proliferation
(Schommer et al., 2014)
, stress-response regulation (Sunkar
and Zhu, 2004), and photomorphogenesis in Arabidopsis
et al., 2014)
. Previous studies have connected miR408 with
responses to plant pathogens and symbionts, such as infection
with Puccinia graminis f. sp. tritici in Triticum aestivum
et al., 2012)
, Cotton leaf curl Allahabad virus (CLCuAV) in
cotton (Khan, 2014), or Exserohilum turcicum in maize
et al., 2014)
, and symbiosis with beneficial diazotrophic
bacterial endophytes in maize (Thiebaut et al., 2014). For
RBSDVinfected maize, the seven up-regulated known miRNA families
might affect the expression of MRDD symptoms and the
development of maize cells in response to RBSDV infection.
In the second group of miRNAs, the expression of five
miRNA families (miR156, miR158, miR160, miR395, and
miR8677) was down-regulated in response to RBSDV
infection in maize. In rice infected with RBSDV at later stages,
the expression of miR156 increased in leaves and roots
et al., 2014)
. The regulation of miR156 expression is
apparently related to the improvement of plant architecture in
(Chen et al., 2015)
, Solanum tuberosum ssp. andigena
(Bhogale et al., 2014)
, and Lotus japonicus
(Wang et al., 2015)
control of flowering time in Arabidopsis and other plants
; and growth of individual organs and whole
plants in Arabidopsis (Chew et al., 2014). A previous study
demonstrated that miR158 might act in male sterility in
Brassica campestris ssp. chinensis
(Jiang et al., 2013)
also regulates gene expression and activity cascades during
the early stages of plant development (Nonogaki, 2010),
pathological development of stem canker disease in Populus
trichocarpa (Zhao et al., 2012), symbiotic nodule
development and auxin sensitivity in soybean
(Turner et al., 2013)
and the response to Soybean mosaic virus (SMV)
(Yin et al.,
. The predicted targets of miR395 might be involved in
morphological and metabolic adaptations in maize root cells
(Zhang et al., 2008) and in wheat response to infection with
Wheat streak mosaic virus (WSMV)
(Fahim et al., 2012)
results of the present study showed that down-regulation of
miR156, miR158, miR160, and miR395 upon RSBVD
infection could be related to plant architecture in maize.
In the third group of miRNAs, members within five known
miRNA families (miR166, miR167, miR169, miR396, and
miR399) increased or decreased at the same time. miR166,
miR167, miR169, and miR396 also responded to RBSDV
in rice leaves and roots
(Sun et al., 2014)
. Previous results
indicated that miR166 controls development of the shoot
apical meristem in Arabidopsis
(Zhu et al., 2011)
nodule in Medicago truncatula (Boualem et al., 2008), and cell
wall thickening in bast during the elongation phase in ramie
(Wang et al., 2014)
. Targets of miR167 include an auxin
response factor that leads to floral development defects and
female sterility in tomato
(Liu et al., 2014b)
, plant growth
retardation upon infection with Hibiscus chlorotic ringspot
(Gao et al., 2013)
, and decreased response to
RBSDV in rice (Sun et al., 2014). The NF-YA genes, which
are targets of miR169, have been closely associated with
stress-induced flowering, abiotic stress response in leaves or
(Calvino and Messing, 2013; Borowski et al., 2014;
Sorin et al., 2014; Luan et al., 2015)
and with root nodule
development (Reynoso et al., 2012). In our study, the
expression of miR169l-5p changed with a log2FC value of 1.3689,
which is consistent with results of a previous study in rice
(Sun et al., 2014)
. Its target gene, which was annotated as
nuclear factor Y, subunit A6, was negatively regulated. While
the expression of miR169i-p5 decreased with a log2FC value
of −1.2605, its major target genes, which were annotated as
nucleolin (suppressor of Mek), a serine/threonine-protein
kinase Rio1, a member of the 60S acidic ribosomal
protein family, and ubiquitin-related enzymes, were negatively
regulated. A few target genes were positively regulated, and
were annotated as an abscisic acid stress- and
ripeningrelated gene, a UDP-glycosyltransferase superfamily
protein, and an ATPase. miR396 is related to the regulation of
stress responses (Liu et al., 2008) and pistil development in
(Liang et al., 2014)
, and to arsenate and
arsenite stress responses in wild accessions of rice
(Sharma et al.,
. miR399 was isolated from the phloem of Brassica
(Buhtz et al., 2008)
, and is related to the expression of
Huanglongbing (HLB, or citrus greening) disease symptoms
(Zhao et al., 2013)
, and is also to the function of a
MYB transcription factor in signaling phosphorus deficiency
(Valdes-Lopez et al., 2008). Combined analyses indicated
that the regulation of the miRNA families miR166, miR167,
miR169, miR396, and miR399 might be involved in maize
tissues and stress responses. The differential expression patterns
observed within a single miRNA family need to be elucidated
in future studies.
Analysis of dwarfing symptoms associated with infection by RBSDV
Plant height is an important agronomic trait that is influenced
by biosynthetic and metabolic pathways related to cell walls
(Reiter et al., 1993; Kalluri et al., 2014)
, and it is negatively
affected by MRDD. The cytological characteristics of leaf
tissues from diseased B73 plants infected with RBSDV by
viruliferous SBPH and from healthy B73 plants were investigated
by electron microscopy. The cell walls of diseased B73 leaves
were changed by infection and appeared bulky compared
with those of healthy B73 leaves (Fig. 9a, b). Previous studies
have shown that members of the cellulose synthase (CESA)
superfamily including CESA active subunits and CESA-like
(CSL) proteins are important in cell wall biosynthesis at the
stage when white streaks or enations appear on the
uppermost newly expanded leaf
(Jia et al., 2012)
. Other studies
have indicated that the expression of several CESA genes and
some CSL genes significantly decrease in response to
infection with RSV, RDV, or RBSDV, all of which belong to the
(Shimizu et al., 2007; Satoh et al., 2010; Jia et al.,
. It has previously been showed that normal cell wall
biosynthesis and plant growth are closely related to CSL D4 (Li
et al., 2009). In the present study, the expression of CESA3
(GRMZM2G025231) and CSLF6 (GRMZM2G122277 and
GRMZM2G110145) genes were all decreased, consistent with
the behavior of their previously known homologs. The plant
cell wall is composed largely of cellulose, lignin, and pectin
(Kalluri et al., 2014)
. Our results showed that the expression
of two lignin-related genes, the laccase precursor proteins, and
most pectinesterase genes increased in response to RBSDV
infection in maize. Combining the results of the present study
with those of previous ones, the dwarf symptom of MRDD
could be due to changes in cell wall-related structure and
biosynthesis, possibly attributable to the decreased expression of
CESA and CSLF genes.
Analysis of the pathogen-response pathway as related to the ubiquitin pathway
A recent study illustrated that the ubiquitin-proteasome
system of papaya is modified upon the infection of plants
with the dsRNA Papaya meleira virus (PMeV)
(Abreu et al.,
. Previous results suggested that a core subunit of E3
ubiquitin ligase, Z. mays SKP1 (SKP1Maize), strongly
interacts with P7-2, a non-structural protein of RBSDV
et al., 2013)
. In the present study, the expression of
ubiquitin-related genes was altered significantly among miRNA
target genes and the transcriptome. Three negatively
regulated genes (GRMZM2G087312, GRMZM2G094595, and
GRMZM2G012690), which are targets of miR169i-p5,
are ubiquitin-related genes, and include NADH:
ubiquinone oxidoreductase, ubiquitin-conjugating enzyme, and
the ubiquitin-associated (UBA)/TS-N domain-containing
protein. Based on target prediction, three transcripts of
GRMZM2G027546 that are targets for miR8155 are
ubiquitin-conjugating enzyme 25. Three ubiquitin
biosynthesisrelated DEGs (GRMZM2G046848, GRMZM2G144782,
and GRMZM2G303964) were detected in response to
RBSDV infection. GRMZM2G303964 is also related to the
binding GO term (GO:0005488), which includes the
negatively regulated gene GRMZM069316 that is a target of
miR169i-p5. GO analysis revealed that these three DEGs
are related to the ubiquitin ligase complex (GO:0000151),
ubiquitin-protein ligase activity (GO:0004842), and protein
ubiquitination (GO:0016567). GRMZM2G144782
probably takes part in the ubiquitin-mediated proteolysis pathway
(zma04120 in KEGG). The results above suggest that
ubiquitin-related genes and genes involved in the ubiquitin
biosynthesis pathway might be influenced during maize infection
with RBSDV. Future studies will be needed to elucidate the
mechanism of interaction between the maize ubiquitin
pathway and RBSDV infection.
Analysis of the pathogen-response pathway in terms of chloroplast and photosynthetic functions
Previous research has indicated that chloroplasts can be
affected by infection of plants with viruses such as TMV
(Chiba and Tominaga, 1952; Reinero and Beachy, 1986;
Bhat et al., 2013)
, Cucumber mosaic virus (CMV)
et al., 2014)
, or RSV
(Xu and Zhou, 2012; Kong et al., 2014)
Recent research suggests that the non-structural protein
P5-2 can be specifically targeted to chloroplasts (Liu et al.,
2015). In the present study, the chloroplasts of healthy B73
plants developed normally, with normal ultrastructure and
clearly defined internal matrix, grana, thylakoids, and starch
grains (Fig. 8c). Internal and external chloroplast structures
changed or vanished upon infection with RBSDV (Fig. 8d).
Transcriptome analysis showed that the expression of several
chloroplast-related genes was altered, and that the expression
of photosynthesis- and photosynthetic pigment-related genes
including chlorophyll and carotenoids was down-regulated
in maize plants infected with RBSDV (Supplementary Table
S6). The decreased expression of these photosynthesis-related
genes seems to indicate that chloroplasts and photosynthesis
were affected during the early stages of RBSDV infection
in maize. When symptoms of RBSDV infection appear, the
chloroplast- or photosynthesis-related genes could not be
detected, although this could have been due to the sampling
The negatively regulated gene GRMZM2G031169
referred to three GO terms (GO:0003824, GO:0044237, and
GO:0050662). Fifty-one significant DEGs were detected
for GO:0003824, which is annotated as catalytic activity.
Among these, the expression levels of three alpha-amylase
precursors (GRMZM2G070172, GRMZM2G074781,
and GRMZM2G138468) were all increased relative to
control plants, with log2FC values of 3.3815, 1.9730, and
1.3342, respectively. However, the expression levels of
three chloroplast precursor genes (GRMZM2G046163,
GRMZM2G015892, and GRMZM2G097457) were lower
in RBSDV-infected leaves. Previous research results
indicated that alpha-amylase is the only enzyme that can degrade
starch granules in spinach chloroplasts (Steup et al., 1983).
In rice leaves, alpha-amylase isoform I-1 is involved in starch
degradation through the endoplasmic reticulum–Golgi
(Asatsuma et al., 2005)
. During biotic and abiotic stress,
an alpha-amylase (At4g25 000) was induced and secreted
in Arabidopsis leaves
(Doyle et al., 2007)
. In Plasmopara
viticola-infected grapevine leaves, increased alpha-amylase
activity was involved in the starch degradation pathway
(Gamm et al., 2011)
. In the present study, starch grains were
not apparent in the chloroplasts of diseased maize plants
compared with those of healthy control plants (Fig. 8c, d).
The disappearance of starch grains may be related to the
altered expression of alpha-amylase precursor genes. The
expression of several miRNAs and other genes detected in
the transcriptome related to catalytic activity, cellular
metabolic processes, and coenzyme binding responded to RBSDV
infection in maize. These genes encoded enzymes including
3-ketoacyl-CoA synthase, alpha-amylase precursor,
AMPbinding enzyme, dehydrogenase, phosphatase, reticuline
oxidase-like protein, UDP-glucuronate 4-epimerase, and others.
We propose here that the degradation of starch grains in the
chloroplast, decreased expression of photosynthesis-related
genes, and the deformation of chloroplasts are closely related
to infection of maize plants by RBSDV.
Seventeen DEGs related to three KEGG pathways
(zma01100, zma01110, and zma00196) showed
differential expression from growth stages V3 to V12. These DEGs
mainly take part in zma01100 and zma01110, which means
metabolic pathways and biosynthesis of secondary
metabolites. Metaboism of terpenoids and polyketides, metabolism
of cofactors and vitamins, energy metabolism,
carbohydrate metabolism, and nucleotide metaboism were directly
involved. Some DEGs in zma01100 and zma01110 also
participate in carbon fixation in photosynthetic organs and in
chlorophyll A–B binding proteins. These results were
consistent with analysis of miRNA-target genes and the
transcriptome. Pathways that related to photosynthetic organs and
chlorophyll A–B binding proteins showed significant
differential expression at five growth stages. The majority of DEGs
showed their lowest expression at stage V6 with higher
levels at V9. These results may suggest that V6 is the sensitive
growth stage of maize in relation to its response to infection
Supplementary data are available at JXB online.
Figure S1. Quantitative real-time RT-PCR (qRT-PCR),
plant disease status, and cytological identification of the
infection status of maize inoculated with RBSDV.
Table S1. Primers used for virus detection by qRT-PCR.
Table S2. Differentially expressed miRNAs and target genes.
Table S3. Three non-conserved and 28 conserved
miRNAs from virus-infected or virus-free leaves at growth
Table S4. Fourteen novel miRNAs from virus-infected or
virus-free leaves at growth stage V3.
Table S5. Differentially expressed target genes for known
Table S6. Differentially expressed target genes for novel
Table S7. Alterations in expression of genes at two time
points in maize infected with RBSDV.
Table S8. Alterations in expression of cell-related genes in
maize infected with RBSDV.
Table S9. Alterations in expression of chloroplast-related
genes in maize infected with RBSDV.
Table S10. Alterations in expression of chloroplast-related
genes in maize infected with RBSDV.
Table S11. GO terms for GRMZM2G069316.
Table S12. GO terms for GRMZM2G031169.
Table S13. qRT-PCR primers used in this study.
This work was supported by grants from the National Hi-Tech Research
Program and Development Program of China
International Cooperation Program of Ministry of Science and Technology
(2014DFG31690), and the Agricultural Science and Technology Innovation
Program at CAAS. Virus-free SBPHs were provided by Yi-Jun Zhou, Tong
Zhou, Ying Lan, Shuang-Gui Tie, and Xiao-Hua Han, whom we would like
to thank for their kind assistance. Also thanks to Jianhua Yuan and Jianrong
Shi for their kind help.
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