The effect of red light and far-red light conditions on secondary metabolism in Agarwood
Kuo et al. BMC Plant Biology
The effect of red light and far-red light conditions on secondary metabolism in Agarwood
Tony Chien-Yen Kuo 0 1 3
Chuan-Hung Chen 0 1 2
Shu-Hwa Chen 7
I-Hsuan Lu 7
Mei-Ju Chu 1
Li-Chun Huang 1
Chung-Yen Lin 5 6 7
Chien-Yu Chen 3 4
Hsiao-Feng Lo 8
Shih-Tong Jeng 2
Long-Fang O. Chen 1
0 Equal contributors
1 Institute of Plant and Microbial Biology, Academia Sinica , 128 Sec. 2, Academia Rd, 11529 Nankang, Taipei , Taiwan
2 Institute of Plant Biology, College of Life Science, National Taiwan University , Taipei 106 , Taiwan
3 Department of Bio-industrial Mechatronics Engineering, National Taiwan University , Taipei 106 , Taiwan
4 Center for Systems Biology, National Taiwan University , Taipei 106 , Taiwan
5 Institute of Fisheries Science, College of Life Science, National Taiwan University , Taipei 106 , Taiwan
6 Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes , Zhunan 350 , Taiwan
7 Institute of Information Science , Academia Sinica, Taipei 115 , Taiwan
8 Department of Horticulture and Landscape Architecture, National Taiwan University , Taipei 106 , Taiwan
Background: Agarwood, a heartwood derived from Aquilaria trees, is a valuable commodity that has seen prevalent use among many cultures. In particular, it is widely used in herbal medicine and many compounds in agarwood are known to exhibit medicinal properties. Although there exists much research into medicinal herbs and extraction of high value compounds, few have focused on increasing the quantity of target compounds through stimulation of its related pathways in this species. Results: In this study, we observed that cucurbitacin yield can be increased through the use of different light conditions to stimulate related pathways and conducted three types of high-throughput sequencing experiments in order to study the effect of light conditions on secondary metabolism in agarwood. We constructed genome-wide profiles of RNA expression, small RNA, and DNA methylation under red light and far-red light conditions. With these profiles, we identified a set of small RNA which potentially regulates gene expression via the RNA-directed DNA methylation pathway. Conclusions: We demonstrate that light conditions can be used to stimulate pathways related to secondary metabolism, increasing the yield of cucurbitacins. The genome-wide expression and methylation profiles from our study provide insight into the effect of light on gene expression for secondary metabolism in agarwood and provide compelling new candidates towards the study of functional secondary metabolic components.
Agarwood; Aquilaria agallocha; Genome; Secondary metabolism; Red light; Cucurbitacin
Agarwood is resinous heartwood derived from Aquilaria
and Gyrinops trees. Due to the high economic value of
these trees and the extensive deforestation, agarwood
producing tree species have become endangered. The
use of agarwood is prevalent in many cultures for religious
ceremonies, perfumes, and especially in Chinese herbal
medicine, where plant materials are commonly utilized [1,
2]. Agarwood is one of the most used plant materials in
Chinese medicine, second only to ginseng. The value of
agarwood lies not only in its aromatic compounds , but
also in its non-volatile compounds, which potentially have
beneficial properties with regards to human medicine [4, 5].
In our previous study, we presented a draft genome and a
putative pathway for cucurbitacins E and I, compounds with
known medicinal value, in Aquilaria agallocha , one of the
largest producers of agarwood. Briefly, gene expression changes
for in vitro samples treated with methyl jasmonate (MJ) were
shown to be consistent with known responses of A. agallocha
to biotic stress and a set of homologous genes related to
cucurbitacin biosynthesis in Arabidopsis thaliana was identified.
However, MJ treatment is perhaps not the most efficient
protocol. Although there exists much research into Chinese
medicinal herbs and extraction of high value compounds, few have
focused on increasing the quantity of target compounds
through stimulation of its related pathways in this species.
In this study, we demonstrate that the quantity of
cucurbitacins can be controlled by utilizing different
types of light. Red light (R) and far-red light (FR) are
components of the solar spectrum that strongly affect
plant tissues. Many studies have reported an interaction
between plant defenses and R/FR responses [7, 8]. Under
low R/FR conditions, there is a dramatic decrease not
only in the number of root nodules but also in the
expression of jasmonic acid (JA) response genes. In a study
on phytochrome B (phyB) mutants, JA-related gene
expression levels have also been observed to be
downregulated  and are known to participate in secondary
metabolic pathways .
In order to better understand the effect of light
conditions on cucurbitacin secondary metabolic
pathways in A. agallocha, we performed
highthroughput sequencing experiments under two
different light conditions: red light, a factor activating
phyB, and far-red light, a factor inhibiting phyB .
Three types of sequencing experiments were
performed: RNA sequencing (RNA-seq) to study gene
expression, whole-genome bisulfite sequencing to
study DNA methylation, and small RNA (sRNA)
sequencing to determine sRNAs that play a role in
methylation. As epigenetic modifications may also
play a role in the regulation of gene expression,
studies on DNA methylation are becoming
To higher organisms, DNA methylation plays an
important and widespread role in epigenetic modification,
mediated by DNA methyltransferases (DMTs). DNA
methylation in the genome is known to provide
protection from transposons and/or RNA viruses, where they
play a role in regulating splicing. DNA methylation is
also associated with major developmental
reprogramming . Small RNAs are also an essential factor in
plants where they play a role in regulating the activation
of functional genes and transposons .
The results of our analysis show that R/FR conditions
have a large effect on gene expression levels in
agarwood. RNA-seq data revealed an array of gene clusters
with distinctive expression patterns, where individual
gene clusters responded primarily to red light or far-red
light. Differentially methylated regions (DMRs)
discovered from whole-genome bisulfite sequencing data
showed that there is also a large difference in
methylation levels between R/FR conditions. We observed that
sRNAs may potentially play a role in influencing the
methylation levels of genes important to secondary
metabolism and subsequently play a role in gene
These genome wide profiles provide insight into the
regulatory interaction between red light and far-red light
conditions in A. agallocha as well as identify compelling
new candidates for secondary metabolic functional
components. The data used in this study is freely available at
our provided webserver (http://molas.iis.sinica.edu.tw/
agarwood) and at NCBI (Bioproject ID: PRJNA240626).
Results and discussion
Red light conditions increase cucurbitacin E and I content
In our previous study, we showed that agarwood
contained high cucurbitacin content and that MJ treatment
increased content levels . Here, we instead used red
light conditions to stimulate cucurbitacin biosynthesis
(Fig. 1). From LC-ESI-MS quantification, it was seen that
cucurbitacin content increased as red light exposure
increased, up to 356 μg/g of cucurbitacin I at day 2.
Cucurbitacin I content decreased as far-red light
exposure increased, down to 96 μg/g at day 2. Similarly for
cucurbitacin E, content levels increased up to 972 μg/g
under red light conditions at day 1 and decreased down
to 567 μg/g under far-red light conditions at day 5.
Under red light conditions, at peak levels, cucurbitacin
content was significantly increased compared to normal
light conditions with p-values of 1.09E-5 and 4.57E-6 for
cucurbitacin I and E respectively in a two-sample t-test.
Similarly for far-red light conditions, at the lowest levels,
cucurbitacin content was significantly decreased
compared to normal light conditions with p-values of
3.44E2 and 1.32E-4 for cucurbitacin I and E respectively.
Different types of light affect various biological
pathways in plants. There are five classes of phytochromes
which typically absorb red light and far-red light .
Previous studies on phyA and phyB photosensory
functions show that red light activated phyB interacts
with transcription factors to induce a
phytochromedependent signaling cascade [7, 8] and that vascular
plant one-zinc-finger (VOZ) transcription factors
interact with phyB . VOZs are active transcription factors
that promote SA and JA-mediated defense responses
under biotic stress [14, 15]. Far-red light is known to
inhibit phyB and plays an antagonistic role in most
pathways [11, 14].
Previous studies have demonstrated that target
compounds can be increased through stimulating
biosynthetic pathways [6, 16] and that light can be used as
stimuli for increasing compound yield . With the
increasing commonality of plant factories, the use of light
as stimuli instead of chemical treatment may be
preferable due to a simpler protocol.
Red light and far-red light gene expression patterns in
In order to study the effects of different light on gene
expression in agarwood, we performed high-throughput
RNA sequencing under red light and far-red light
conditions. The time-course RNA-seq data (Table 1) was
obtained from samples under red light and far-red light
conditions at 1, 2, and 5 days, as well as normal
conditions (white light control). Two biological replicates
Fig. 1 Endogenous cucurbitacin content of in vitro agarwood. Content was measured after red and far-red light treatment over the course of
5 days. Data is represented as mean ± standard deviation (n = 5). At peak levels under red light conditions, cucurbitacin content was significantly
increased compared to normal light conditions (paired t-test p-values 1.09E-5 and 4.57E-6 for cucurbitacin I and E respectively). At the lowest
levels under far-red light conditions, cucurbitacin content was significantly decreased compared to normal light conditions (paired t-test p-values
3.44E-2 and 1.32E-4 for cucurbitacin I and E respectively)
We utilized the RNA-seq data and the previously
constructed A. agallocha genome  for gene expression
quantification, resulting in an average correlation
coefficient of 0.9404 for gene expression levels between
biological replicates. Genes were clustered into 16 clusters
based on their expression patterns, requiring a two-fold
change in expression and a p-value cut-off of 0.001 for
differential expression (Fig. 2). In total, 8882 genes were
determined to be differentially expressed and clustered into
distinct expression patterns (Additional file 1: Table S1).
Gene ontology (GO) classification was performed to
identify each cluster’s most significant biological process
Clusters 3 and 11 were observed to exhibit a pattern
of up-regulation under red light conditions and
repression under far-red light conditions, consistent with the
observed changes in cucurbitacin content levels. The
GO classifications show that 253 out of 495 genes, in
clusters 3 and 11 combined, are classified as belonging
to metabolic processes (Additional file 2: Figure S1).
Furthermore, these clusters contain 3 genes classified as
belonging to terpene biosynthesis, the main class of
Table 1 RNA-seq libraries under different light conditions
compounds related to the medicinal properties of
agarwood [18–20]. Terpenoid content is induced under
biotic stress as an immune response to resist various
pathogens [6, 21] and its derivatives have been shown to
exhibit anti-microorganism, anti-tumour, and other
pharmacological effects that are beneficial towards
human medicine [4, 5]. In addition to terpene biosynthesis,
clusters 3 and 11 contained 26 genes related to defense
response. Previous studies have shown that far-red light
down-regulates the expression of defense response genes
by reducing a plant’s sensitivity to jasmonate (or methyl
jasmonate) in Arabidopsis [7, 8]. From the RNA-seq
data, it was seen that some defense response genes were
up-regulated under red light conditions and
downregulated under far-red light conditions. These results
are consistent with our expectations and suggest that
controlled light conditions can be used in place of plant
hormones to induce defense response genes in
Red light and far-red light DNA methylation patterns in
In order to study the effect of different light on
methylation patterns in agarwood, we performed whole-genome
bisulfite sequencing with two biological replicates for
red light day 2, far-red light day 2, and normal samples
(Additional file 2: Table S2). The methylation levels for
each sample were used to discover differentially
methylated regions (DMR) between different light conditions.
A characterization of DMRs (Fig. 3a) shows that DMR
proportions in transposons and intergenic regions were
not significantly changed by R or FR conditions. In genic
regions, it was seen that there was a slight increase
(~6.4 %) in DMR proportions at promoter regions under
FR conditions. The number of DMRs for each light
Fig. 2 Cluster analysis of gene expression patterns in agarwood. Sixteen clusters were identified by k-means clustering. The samples are
represented on the x-axis, from left to right: FR day 5, FR day 2, FR day 1, normal, R day 1, R day 2, R day 5. The centered log2 fold-change is
represented on the y-axis
condition (Fig. 3b) indicates that there is a large change
in methylation levels between red light and far-red light
We focused on hypo-DMRs under red light conditions,
using the consensus hypo-DMRs between R/normal and
R/FR data, resulting in 621 regions for analysis. The
average methylation levels in red light hypo-DMRs (Fig. 4a)
show that CHH methylation (where H represents A, T, or
C) exhibit the most significant differences under red light
conditions. This remains the trend for average weighted
methylation levels  in genic regions (Fig. 4b), where
the most significant differences in methylation levels were
observed in promoter regions for CHH methylation. CHG
methylation levels were also observed to be affected by
red light while CG methylation levels were relatively
unchanged. These results suggest that red light may regulate
gene expression in agarwood by changing CHH and CHG
methylation, primarily in promoter regions.
In higher plants, Domains Rearranged Methylase 2
(DRM2) catalyzes de novo DNA methylation in all
cytosine contexts including CG, CHG, and CHH , via
the RNA-directed DNA methylation pathway (RdDM)
[24–26]. Cytosine methylation and demethylation are
both closely linked with gene regulation where high
methylation patterns typically accompany low gene
expression [27, 28]. In RdDM, Argonaute 4 (AGO4) has
been recognized to interact with sRNAs and participate
in DNA methylation [28–30].
sRNAome of red light and far-red light conditions in
In order to identify sRNAs that play a role in changes to
methylation under different light conditions, we
performed sRNA sequencing with two biological replicates
for red light day 2, far-red light day 2, and normal
samples (Table S2). Overall, approximately 6 million distinct
Table 2 Gene ontology analysis on 16 clusters of gene expression patterns
negative regulation of nucleotide metabolic process
cell redox homeostasis
trehalose biosynthetic process
response to water stimulus
detection of visible light
proteolysis involved in cellular protein catabolic process
sRNAs were able to be mapped perfectly and uniquely to
the genome. A characterization of mapped sRNAs
(Additional file 2: Figure S2) revealed that the majority (56.28 %)
of sRNAs were mapped to genic regions, within which, a
large majority (61.11 %) were mapped to promoter regions.
As well, we characterized the mapped sRNAs in terms of
their length (Table 3) and observed that 71.93 % of the
sRNAs were 24-nt long overall, 73.37 % in promoter
regions. These results support the idea that under different
light conditions, sRNA may play a role in DNA methylation
via AGO4 and the RdDM pathway in agarwood.
Small RNAs are classified into two major categories:
microRNA (miRNA) and short interfering RNA (siRNA)
. Small RNAs, which are cut from double-stranded
RNA (dsRNA) by Dicer-like enzymes, participate in gene
silencing as miRNA [32–34]. The focus of this study,
siRNAs, are processed from the overlapping regions of
natural sense-antisense transcript pairs or the near-perfect
double-stranded RNAs (dsRNAs) synthesized by
RNAdependent RNA polymerases (RDRs) [35–37]. Based on
their origins, plant siRNAs include four major classes:
heterochromatic siRNAs (hc-siRNAs), trans-acting siRNAs
(ta-siRNAs), natural antisense transcript-derived siRNAs
(nat-siRNAs), and long siRNAs (lsiRNAs) . siRNAs
bind to specific Argonaute proteins to form a
RNAinduced silencing complex (RISC) guiding RISCs to DNA
Fig. 3 Characterization of differentially methylated regions for light conditions red light, far-red light, and normal. a Composition of DMRs in the
A. agallocha genome. TE represents transposable elements, IG represents intergenic regions, Gene represents the gene body, and Promoter
represents gene promoter regions. b Number of DMRs that are overlapping or unique to red light and far-red light conditions
Fig. 4 Methylation levels for hypo-DMRs under red light conditions. a Box plots displaying the distribution of average CG, CHG, and CHH methylation
levels for hypo-DMRs under red light conditions. b Average methylation levels in gene bodies and flanking 2 kb regions. Each gene was aligned from start
to end and divided into 20 equal bins. Upstream and downstream flanking regions were also each divided into 20 equal bins. Weighted methylation levels
were calculated for each of the 60 bins across all corresponding regions
or RNA targets based on sequence complementarity
and trigger gene silencing transcriptionally or
posttranscriptionally . Different AGOs have different
preferences. AGO1 has a strong bias towards 5’
terminal uridine, AGO2 prefers 5’ terminal adenosine, and
AGO4 prefers 5’ terminal adenosine, guanine, or
uridine . Different length small RNAs play different
roles and are cut by different Dicer-like enzymes (DCL)
[34, 36, 39]. Among them, the 24-nt long miRNAs
(lmiRNAs) and 24-nt siRNAs are processed by DCL3
. These 24-nt small RNAs interact with AGO4 and
Regulation of secondary metabolic gene expression by
Although DNA methylation in promoter regions and
intergenic transposable elements generally inhibit gene
expression , the role of DNA methylation in A.
agallocha is still unclear. To further our understanding of
DNA methylation in A. agallocha, we identified sRNAs
that inhibit gene expression through the RdDM pathway
Table 3 Characterization of sRNAs by sequence length
selected from the set of metabolic processes genes
containing hypo-methylated regions (Additional file 2: Figure S3).
As mentioned previously, different AGOs have
different preferences. Here, we focused on sRNA sequences
that suited AGO4 preferences and mapped to
hypoDMRs. We identified 61 genes in agarwood related to
secondary metabolism that fit our criteria. Three
candidate genes were selected for further analysis (Fig. 5), a
sterol methytransferase (g16251), a hydroxysteroid
dehydrogenase (g23648), and a cytochrome P450 (g29032).
The selected genes show that sRNAs were mapped to
red light hypo-DMRs with a corresponding increase in
mRNA expression under red light conditions. The
expression levels were also verified using qRT-PCR
(Additional file 2: Figure S4).
In the three candidate genes, we detected three
specific sRNAs that mapped perfectly to promoter regions
under far-red light conditions. It was seen that these
sRNAs had a positive relationship with DNA
methylation levels and a negative relationship with gene
expression levels. In contrast, for both the sRNA sequencing
and qRT-PCR validation, these sRNAs were not able to
be detected under red light conditions. This suggests
that the effects of red light and far-red light on
secondary metabolism gene expression in agarwood are
antagonistic to each other and that these sRNAs potentially
play a role in gene expression regulation through the
RdDM pathway in cucurbitacin biosynthesis.
Sterols (steroid alcohols) belong to steroids and are
ubiquitous in eukaryotic organisms, playing pivotal roles
in membrane structure and as precursors of vitamins
and steroid hormones . Sterol methyltransferases are
known to catalyze a single methyl addition, an important
step in phytosterol synthesis , and important to
biosynthesis of secondary metabolites such as cucurbitacin.
Hydroxysteroid dehydrogenases belong to alcohol
oxidoreductases, which catalyzes the dehydrogenation of
hydroxysteroid in steroidgenesis by cofactor NADP(H) or
NAD and may affect the activity of compounds .
Cytochrome P450s (CYP450s) are also ubiquitous in
many organisms. In plants, one or more CYP450s
participate in compound modification and affect compound
activity in secondary metabolism . As well, some
CYP450s play an important role in steroidgenesis [46, 47].
Although these three candidate genes belong to rather
large gene families, the gene expression, sRNA, and
methylation patterns under red light and far-red light
conditions indicate that these genes are potentially
important for cucurbitacin metabolism in agarwood.
In this study, we performed three types of sequencing
experiments in order to study the effect of light
conditions on cucurbitacin biosynthesis and secondary
metabolism in agarwood. This resulted in a number of new
insights regarding the global regulation of genes by red
light and far-red light. From the RNA sequencing
results, gene expression patterns were clustered into
distinct clusters, many of which can be characterized as
responding primarily to light conditions. In particular,
two gene expression clusters clearly exhibited gene
expression patterns in response to red light and far-red
light. Significantly, the two clusters included genes
related to terpene biosynthesis and defense response. In
addition to gene expression, small RNA and DNA
methylation were observed to be factors affected by
different light conditions which in turn affect cucurbitacin
metabolism in agarwood. We identified a set of small
RNA which potentially regulates gene expression
through the RdDM pathway.
The results from this study provide genome-wide
profiles of RNA expression, small RNA, and DNA
methylation with regards to light conditions. These profiles
provide insight into the effect of light on gene
expression for cucurbitacin biosynthesis in agarwood as well as
provide compelling new candidates for functional
secondary metabolic components, highlighting new
questions to be addressed in future studies.
We also demonstrate that light conditions can be used
in lieu of methyl jasmonate treatment to stimulate
pathways related to secondary metabolism, increasing the
yield of cucurbitacins. This has important implications
for the increasing use of plant factories for the synthesis
of high value compounds.
Fig. 5 Light conditions regulate gene expression by the RdDM pathway. The RNA expression, DNA methylation, and sRNA expression is shown
for three candidate genes: g16251 (sterol methytransferase), g23648 (hydroxysteroid dehydrogenase), and g29032 (cytochrome P450). Signals in
red represent red light conditions while signals in blue represent far-red light conditions
Plant materials for DNA and RNA extraction
A plant regeneration system from shoot tips into in vitro
plants was created using a tissue culture process similar to
the processes described by He et al. . LED light sources
(Daina Electronics) were used to provide different light
conditions (Table S3). Normal (white light ~55 μmol m−2 s−1)
in vitro plant materials were grown under long-day
conditions (16 h of light, 8 h of darkness) at 25 °C. Red light
samples (~15 μmol m−2 s−1, 680 nm) and far-red light samples
(~15 μmol m−2 s−1, 730 nm) were continuously exposed to
their respective light conditions at 25 °C and the materials
used for sequencing were collected after 1, 2, and 5 days.
DNA was extracted from 1 g of in vitro materials
using the Plant Genomic DNA MiniKit (Maestrogen)
following the manufacturer’s instructions. RNA was
extracted from 1 g of in vitro materials using RNeasy Plant
MiniKit following the protocol prescribed by the
manufacturer. Normal light samples were collected from
material grown under long-day conditions in white light.
The DNA and RNA samples were sent to BGI for
poly(A) RNA sequencing, whole-genome bisulfite
sequencing, and small RNA sequencing.
In vitro materials were ground with liquid nitrogen and
mixed with 1 mL of methanol. Supernatant was
collected by centrifugation (12000 rpm, 1 min). The
LCESI-MS system consisted of an ultra-performance liquid
chromatography system (Ultimate 3000 RSLC, Dionex)
and an electrospray ionization source of quadrupole
time-of-flight mass spectrometer (maXis HUR-QToF
system, Bruker Daltonics). The autosampler was set at
4 °C. Separation was performed with reversed-phase
liquid chromatography on a BEH C8 column (2.1 ×
100 mm, Walters). The elution started from 99 % mobile
phase A (0.1 % formic acid in ultrapure water) and 1 %
mobile phase B (0.1 % formic acid in ACN), held at 1 %
B for 1.5 min, raised to 60 % B in 6 min, further raised
to 90 % in 0.5 min, and then lowered to 1 % B in
0.5 min. The column was equilibrated by pumping 1 %
B for 4 min. The flow rate was set to 0.4 mL/min with
an injection volume of 5 μL. LC-ESI-MS chromatogram
were acquired under the following conditions: capillary
voltage of 4500 V in positive ion mode, dry temperature
of 190 °C, dry gas flow maintained at 8 L/min, nebulizer
gas at 1.4 bar, and acquisition range of m/z 100–1000.
Five samples for each condition were independently
measured for cucurbitacin content levels.
RNA sequencing analysis
The RNA-seq data for all samples (Table 1) were
trimmed for low quality bases at the 3’ terminal and
then individually aligned to the set of annotated A.
agallocha transcripts using BWA . For each dataset,
expression quantification was performed using eXpress
. R/FR pair-wise differential gene expression analysis
was performed using edgeR  incorporating all
replicates. Genes which exhibit at least a two-fold change in
expression with a p-value threshold of 0.001 between
any red light and far-red light sample were retained for
clustering analysis. Clustering analysis was performed on
the expression profiles of differentially expressed genes
using k-means clustering. Gene ontology classifications
for each cluster was performed using BinGO .
Whole-genome bisulfite sequencing analysis
The whole-genome bisulfite sequencing data for red
light day 2, far-red light day 2, and normal were
trimmed for low quality bases at the 3’ terminal.
MOABS  was utilized to perform alignment to the
A. agallocha genome, methylated cytosine calling,
discovery of differentially methylated cytosines (DMCs),
and discovery of differentially methylated regions
(DMRs). Differentially methylated cytosines were
discovered using a Fisher Exact Test, with a p-value threshold
of 0.05, a minimum depth of 3, and a minimum of 33 %
nominal difference in methylation ratios between
conditions. Differentially methylated regions were discovered
using a Fisher Exact Test, with a p-value threshold of
0.05, a minimum of 3 DMCs in a region, and a
maximum distance of 300 bp between DMCs.
sRNA sequencing analysis
The sRNA sequencing reads for red light day 2, far-red
light day 2, and normal were aligned to the A. agallocha
genome using BWA . Only sequences with perfect
mappings (no mismatches, no gaps) and uniquely
mapped (to one genome location only) were retained for
Validation of RNA expression on three candidate genes
was performed using qRT–PCR analysis. The RNA
samples for each light condition were extracted from 1 g of
in vitro A. agallocha shoots using RNeasy Plant MiniKit
following the protocol prescribed by the manufacturer.
Primers pairs were designed for each transcript (Table S4)
with the ABI Prism 7500 sequence detection system
(Applied Biosystems). Each primer pair was used to amplify
the respective cDNA fragments using a cycling profile
consisting of 58 °C for 2 min, 95 °C for 10 min, and 40
cycles of 95 °C for 15 s and 60 °C for 1 min. The relative
gene expression was determined by the comparative CT
method, 2−ΔCT (ΔCT = CT, gene of interest – CT, control
gene), using AcHistone as the internal control . Four
independent biological repeats were performed for each
assay where the final expression value is the mean
expression of the repeats.
Validation of sRNA used the same plant materials as
described above. An endogenous sRNA (CGGTGGAAG
AAATAATAGGGCCTG) was chosen as internal control
due to its expression levels being stable under different
light conditions (mean TPM of 237.00 ± 39.44) as well as
uniquely mapping to an intergenic region and thus will
not affect genes. For detecting sRNAs of g16251,
g23648, and g29032, miScript Primer Assays (Qiagen)
#MSC0074731, #MSC0074729, and #MSC0074727,
respectively, as well as the miScript Universal primer were
used. Five independent biological repeats were
performed for each assay where the final expression value is
the mean expression of the repeats.
Availability of supporting data
The datasets supporting the results of this article are available
in the NCBI repository, BioProject ID: PRJNA240626, http://
annotations, KEGG, and GO classifications for Aquilaria
agallocha are available at our webserver,
Additional file 2: Table S2. (a) Whole-genome bisulfite sequencing
DNA libraries and (b) sRNA sequencing libraries. Table S3. Spectral data
of lamps used for different light conditions in this study. Table S4. Gene
specific primers for real-time PCR analysis of gene expression. Figure S1. Gene
Ontology classifications of the set of transcripts in cluster 3 and cluster 11.
Relative gene proportions were calculated separately for Biological Process
and Molecular Function. Figure S2. The composition of sRNAs that mapped
to the A. agallocha genome. Only sRNAs which mapped perfectly and
uniquely to one genome location were retained for analysis. Figure S3. Gene
Ontology classifications of hyper and hypo differentially methylated regions.
Relative gene proportions were calculated separately for Biological Process
and Molecular Function. The set of metabolic process genes containing
hypo-methylated regions were curated for secondary metabolic function and
sRNA which mapped to hypo-DMR regions. Figure S4. qRT-PCR validation of
mRNA expression and sRNA expression. Expression quantification from
sequencing data as FPKM and TPM of the mRNA and sRNA expression are
also shown, respectively.
AGO4: Argonaute 4; CYP450s: Cytochrome P450s; DCL: Dicer-like enzyme;
DMRs: Differentially methylated regions; DMTs: DNA methyltransferases;
DRM2: Domains rearranged Methylase 2; dsRNA: Double-stranded RNA;
DMCs: Differentially methylated cytosines; FR: Far-red light;
hcsiRNAs: Heterochromatic siRNAs; GO: Gene ontology; lsiRNAs: Long siRNAs;
lmiRNAs: Long miRNAs; JA: Jasmonic acid; phyB: Phytochrome B;
natsiRNAs: Natural antisense transcript-derived siRNAs; MJ: Methyl jasmonate;
miRNA: MicroRNA; R: Red light; RNA-seq: RNA sequencing; RdDM:
RNAdirected DNA methylation pathway; RDRs: RNA-dependent RNA polymerases;
RISC: RNA-induced silencing complex; sRNA: Small RNA; siRNA: Short
interfering RNA; ta-siRNAs: Trans-acting siRNAs.
The initiation and financial responsibility of this study were from LFOC and
HFL. Experiments were designed by CHC, CYC, and LFOC. Biological
experiments were performed by TCYK, CHC, TYC, MJC, MHY. Analysis
performed by TCYK, CHC, SHC, IHL, LCH, CYC. The in vitro plant
manipulation, sampling and quality were controlled by MJC and LCH.
Supervision performed by LCH, STJ, CYC, HFL, LFOC. Manuscript was
prepared by TCYK and CHC with input from the other coauthors. All authors
read and approved the final manuscript.
The authors would like to thank Academia Sinica and the Ministry of Science
and Technology, Republic of China, Taiwan, for the financial support under
the grants: NSC 102-2313-B-001-001-MY3, 101-2313-B-001-002 and grants
103-2811-B-001 -083 and 102-2811-B-001 -088 for postdoctor fellowship to
TCYK. TCX-D800 Metablomics Core, Technology Commons, College of Life
Science, and National Taiwan University for their help with LC-ESI-MS
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