R E S E A R C H A R T I C L E Open Access
High flavonoid accompanied with high
starch accumulation triggered by nutrient
starvation in bioenergy crop duckweed
, Yang Fang
, Meng-Jun Huang
, Yao Xiao
, Yang Liu
, Xin-Rong Ma
and Hai Zhao
Background: As the fastest growing plant, duckweed can thrive on anthropogenic wastewater. The purple-backed
duckweed, Landoltia punctata, is rich in starch and flavonoids. However, the molecular biological basis of high flavonoid
and low lignin content remains largely unknown, as does the best method to combine nutrients removed from sewage
and the utilization value improvement of duckweed biomass.
Results: A combined omics study was performed to investigate the biosynthesis of flavonoid and the metabolic flux
changes in L. punctata grown in different culture medium. Phenylalanine metabolism related transcripts were identified
and carefully analyzed. Expression quantification results showed that most of the flavonoid biosynthetic transcripts were
relatively highly expressed, while most lignin-related transcripts were poorly expressed or failed to be detected by iTRAQ
based proteomic analyses. This explains why duckweed has a much lower lignin percentage and higher flavonoid
content than most other plants. Growing in distilled water, expression of most flavonoid-related transcripts were
increased, while most were decreased in uniconazole treated L. punctata (1/6 × Hoagland + 800 mg•L
When L. punctata was cultivated in full nutrient medium (1/6 × Hoagland), more than half of these transcripts were
increased, however others were suppressed. Metabolome results showed that a total of 20 flavonoid compounds were
separated by HPLC in L. punctata grown in uniconazole and full nutrient medium. The quantities of all 20 compounds
were decreased by uniconazole, while 11 were increased and 6 decreased when grown in full nutrient medium. Nutrient
starvation resulted in an obvious purple accumulation on the underside of each frond.
Conclusions: The high flavonoid and low lignin content of L. punctata appears to be predominantly caused by
the flavonoid-directed metabolic flux. Nutrient starvation is the best option to obtain high starch and flavonoid
accumulation simultaneously in a short time for biofuels fermentation and natural products isolation.
Keywords: Duckweed, Flavonoids, Starch, Combined omics, Nutrient starvation, Uniconazole
Flavonoids, also known as vitamin P, constitute a vast
class of secondary metabolites widely distributed in plants,
which encompasses more than 10,000 structures . They
have a low molecular weight and a general structure of
three rings, including two phenyl rings (A and B) and a
heterocyclic ring (C). With different substituent groups,
flavonoids can be divided into seven subgroups, includ-
ing chalcones, flavones, flavonols, flavandiols, anthocya-
nins, condensed tannins and aurones . Some
specialized forms of flavonoids can be synthesized by
some plant species, such as the isoflavonoids  and 3-
deoxyanthocyanins [4, 5]. Different flavonoids usually
play various roles in plants by regulating several develop-
mental processes [6–10]. Furthermore, these secondary
metabolites are well characterized as defense compounds
and signaling molecules that can withstand a wide array of
environmental stresses in plants and diseases in humans
* Correspondence: firstname.lastname@example.org;email@example.com
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu,
Sichuan 610041, China
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Tao et al. BMC Genomics (2017) 18:166
[11, 12], due to their capacity to absorb ultraviolet (UV)
radiation, and inhibiting the generation of reactive oxygen
species (ROS) [13–15]. Through their ability to inhibit
DNA gyrase, energy metabolism and cytoplasmic mem-
brane function, flavonoids possess antifungal, antiviral and
antibacterial activity [16, 17].
Duckweed (Lemnacecae family) is the smallest and
simplest flowering aquatic plant in the world, and its
growth highly adaptable across a broad range of climates
. It has a long yearly production period with an al-
most exponential growth rate, producing biomass faster
than most other plants. It can thrive on eutrophic waste-
water, through its ability to remove nutrients from sew-
age  and large amounts of CO
from the atmosphere
[20–22]. In warm seasons, duckweed can remove up to
85% of total Kjehldahl nitrogen (TKN) and 78% of total
phosphorous (TP) from sewage . The value of duck-
weed as a test species for the registration of agrochemi-
cals has been discussed worldwide . A previous
study indicated that this plant possesses negligible lignin
content . Depending on the duckweed species and
the growing conditions, the starch content of duckweed
ranges from 3% to 75% [25–27]. Furthermore, it has
been found that the purple-backed duckweed has high
flavonoid content in crude plant form [28, 29], while
only flavonoid-rich fractions of the most prevalent flavon-
oid sources, tartary buckwheat or ginkgo, can be used to
extract these kinds of flavonoids [30–32]. Together with a
much higher biomass production, duckweed should be
a more promising flavonoid resource plant than tartary
buckwheat and gingko. These characteristics make
purple-backed duckweed a potential sustainable source
for bioenergy production [33, 34], animal feed  and
even human food . A company from Israel has found
that duckweed can address the challenges of consumer
health concerns, rising health care costs and food security
issues by exploring the nutritional value, traditional con-
sumption in Southeast Asia, and commercialization possi-
bilities of duckweed . However, a method to combine
nutrients remove from sewage and the utilization value im-
provement of duckweed biomass remains as yet unknown.
In a previous study, it was found that the total flavonoid
content of L. punctata increased from 4.51% to 5.56% fol-
lowing nutrient starvation for 168 h , accompanied by
high starch accumulation for bioethanol fermentation .
Spraying with 800 mg · L
uniconazole is an alternative
method to accumulate high levels of starch [26, 27], but
whether it underwent the same physiological and molecu-
lar alteration remains unknown. In this study, the changes
of flavonoids in full nutrient, starvation and uniconazole
treated L. punctata groups were investigated and com-
pared by a combined omics study. This provided molecular
support for the simultaneous accumulation of high starch
and high flavonoid levels in this bio-resource plant.
Comprehensive transcriptome construction for L. punctata
In order to construct a comprehensive transcriptome for
L. punctata, Illumina HiSeq 2000 paired-end (PE) reads
of nutrient starvation (distilled water, NS)  and unico-
nazole (1/6 × Hoagland + 800 mg•L
[26, 27] responsive transcriptomes, and also the full nutri-
ent (1/6 × Hoagland, FN) transcriptome, were pooled to-
gether and de novo assembled using Trinity (v2012-06-08)
. All PE reads were deposited in Sequence Read
Archive database (SRA) under accession number of
PRJNA185389. A total of 543,912,936 PE 90 bp reads
were obtained from the three RNA-Seq groups, corre-
sponding to 48.95 Gbp in total (Table 1). Furthermore,
155,903 contigs with lengths ≥200 bp were assembled,
corresponding to a transcriptome size of 170.34 Mb.
The average length, N50 length and max length was
1093 bp, 2190 bp and 17,234 bp, respectively. Among
these contigs, 51,873 were longer than 1000 bp and
26,931 were longer than 2000 bp. The results from scan-
ning of the Open Reading Frames (ORFs) of all contigs
showed that there were 67,061 ORFs with lengths ≥600 bp
(from ATG to stop codon), and 37,797 ORFs with
lengths ≥900 bp.
All PE reads were used separately for short-read align-
ment for each sample through the perl script provided with
the Trinity package (v2012-06-08) . The number of
aligned reads for each contig was counted and used for ex-
pression profiling. To normalize the bias introduced by the
sequencing library size and mRNA composition, edgeR
(the Empirical analysis of Digital Gene Expression in R)
 in the Trinity package (v2012-06-08)  was used to
make an effective library size for each sample and
normalize the number of aligned reads per transcript to
generate a FPKM (Fragments Per Kilobase of tran-
scripts per Million mapped fragments) value using the
RESM-based algorithm. It was found that the number
of expressed transcripts ranged from 36,950 to 60,854,
with only 20,776 transcripts expressed in all samples
(Table 1). Furthermore, the results showed that full nu-
trient conditions stimulated more transcript expression
compared to the other two experimental groups.
A BlastX sequence similarity search against the non-
redundant protein database (NR) of NCBI [http://
www.ncbi.nlm.nih.gov/] was conducted by a locally-
installed blast program to investigate functional annota-
tion of each contig. BlastX results were then uploaded
to the Blast2GO platform [39, 40] for annotation. A total
of 98,106 (62.9%) contigs (transcripts) had significant
BlastX hits. Of the 26,931 contigs ≥2000 bp in length,
26,273 were annotated, corresponding to an annota-
tion rate of 97.6%. For the 51,873 contigs ≥1000 bp,
the annotation rate was 93.0% (annotated 48,266). For
contigs ≥900 bp and ≥600 bp, this rate was 91.7%
Tao et al. BMC Genomics (2017) 18:166 Page 2 of 14
(50,762 of 55,328) and 85.3% (59,595 of 69,878),
Biosynthetic network of phenylalanine metabolism
To construct the biosynthetic network related to phenyl-
alanine metabolism, enzyme codes were extracted and
Kyoto Encyclopedia of Genes and Genomes (KEGG)
pathways retrieved from the KEGG web server [http://
www.genome.jp/kegg/]. Transcripts were detected that
corresponded to almost all of the enzymes involved in
flavonoid and lignin biosynthesis, except for flavone
synthase, aureusidin synthase, flavanone 7-O-beta-
glucosyltransferase and flavanone 7-O-glucoside 2''-
O-beta-L-rhamnosyltransferase (Fig. 1, Additional file 1:
Table S1, Additional file 2: Table S2). Phenylalanine ammo-
nialyase (EC: 220.127.116.11, PAL), cinnamate 4-hydroxylase (EC:
18.104.22.168, C4H) and 4-hydroxycinnamoyl-CoA ligase (EC:
22.214.171.124, 4CL) are the universal factors involved in flavonoid
and lignin biosynthesis . Transcripts encoding these en-
100 FPKM. Cinnamoyl-CoA reductase (EC: 126.96.36.199, CCR)
and hydroxycinnamoyl transferase (EC: 188.8.131.52, HCT)
catalyze the initial reactionintheligninbiosynthesis
branch. Almost all transcripts related to CCR and HCT
had expression levels lower than 20 FPKM. Conversely,
chalcone synthase (EC: 184.108.40.206, CHS) and chalcone isom-
erase (EC: 220.127.116.11, CHI), the enzymes that catalyze the first
two reactions of flavonoid biosynthesis branch, were more
highly expressed (Fig. 1). This possibly explains why duck-
weed has a much lower lignin percentage than most other
plants [24, 34, 42, 43]. As p-coumaroyl CoA is the product
of a 4CL or C4H catalyzed reaction, it can be converted
into isoliquiritigenin or naringenin chalcone, then catalyzed
by chalcone isomerase (EC: 18.104.22.168, CHI) to feed this prod-
uct into the isoflavonoid biosynthesis pathway. Expression
data showed that CHS and CHI were both highly expressed
at over 100 FPKM, which may indicate that a large amount
of p-coumaroyl CoA was directed into the isoflavonoid
biosynthesis pathway. Meanwhile, the expression of fla-
vanone 3-hydroxylase (EC: 22.214.171.124, F3H), dihydroflavo-
nol 4-reductase (EC: 126.96.36.199, DFR) and anthocyanidin
synthase (EC: 188.8.131.52, ANS), which direct the meta-
bolic flux into the anthocyanin biosynthesis branch, were
all higher than 100 FPKM. However, flavone synthase (EC:
184.108.40.206, FNS) was unable to be detected in this study.
Of course, this may be because there was no expression of
RNA-Seq based flavonoid biosynthetic analyses of
nutrient starvation or uniconazole treated L. punctata
Expression patterns of genes involved in specific pathways
can affect the metabolic flux. All transcripts described
above were quantified by RNA-Seq analyses (Fig. 2,
Additional file 1: Table S1, Additional file 2: Table S2).
Culturing duckweed in distilled water, the highest expressed
PAL, comp39767_c0_seq1, showed no obvious change
(132.07, 140.13 and 113.28 FPKM). The other highly
expressed PAL, comp39767_c0_seq2, was increased in
NS-2 (29.62 FPKM) and NS-24 (39.36 FPKM) when
compared with that in NS-0 (17.70 FPKM). Expression
level of comp46865_c0_seq1, a C4H encoding transcripts,
was increased from 78.22 FPKM to 152.93 FPKM in 24 h.
The expression level of comp46833_c0_seq1, a 4CL en-
coding transcript, was increased 2.22 times in NS-24
(294.61 FPKM) compared with that in NS-0 (132.43
FPKM). Spraying with 800 mg · L
in a slight initial increase in the expression of the two
highly expressed PAL, comp39767_c0_seq1 and comp39767_
c0_seq2, followed by a slight decrease after 72 h. The highest
expressed C4H, comp46865_c0_seq1, was increased in
UT-72 (197.19 FPKM) and UT-240 (189.65 FPKM)
when compared with that in UT-0 (102.44 FPKM), UT-2
(105.64 FPKM) and UT-5 (108.16 FPKM). Moreover, two
other poorly expressed C4H, comp45597_c0_seq1 and
Table 1 RNA-Seq statistics for different duckweed samples
Sample name Clean read Clean bases (bp) Q20(%) GC(%) Expressed transcripts
NS-0 41,337,098 3,720,338,820 97.02 56.90 38,056
NS-2 38,628,052 3,476,524,680 97.00 57.20 36,950
NS-24 38,789,556 3,491,060,040 97.03 57.12 38,627
UT-0 48,315,010 4,348,350,900 98.55 55.18 42,319
UT-2 48,390,098 4,355,108,820 98.57 55.26 42,693
UT-5 48,623,932 4,376,153,880 98.60 55.10 45,081
UT-72 48,282,456 4,345,421,040 98.56 55.30 45,789
UT-240 48,248,454 4,342,360,860 98.55 55.50 43,254
FN-2 45,491,706 4,094,253,540 97.89 55.31 43,497
FN-5 45,962,348 4,136,611,320 97.94 54.92 45,028
FN-72 45,954,756 4,135,928,040 97.96 55.12 50,300
FN-240 45,889,470 4,130,052,300 97.94 54.92 65,854
Tao et al. BMC Genomics (2017) 18:166 Page 3 of 14
comp45597_c1_seq2, were increased during the first
240 h in the uniconazole treated group. However, the
results also showed that the highest expressed 4CL en-
coding transcripts (comp46833_c0_seq1, comp46135_
c0_seq2) were obviously suppressed by uniconazole. In
addition, several other 4CL were also suppressed, in-
cluding comp44243_c0_seq10, comp44243_c0_seq9,
comp35216_c0_seq1 and comp35216_c1_seq1. 4-
coumaroyl-CoA produced by 4CL can be catalyzed by
HCT to produce 4-coumaroylshikimate or catalyzed by
CHS to be converted into naringenin chalcone, which
directs the substrate into lignin biosynthesis or flavonoid
biosynthesis. Enzymes involved in the flavonoid metabol-
ism branch were carefully analyzed. It was found that a
CHS encoding transcript (comp46654_c0_seq1) was in-
creased by starvation treatment from the original 401.10
FPKM to 500.20 FPKM at 2 h and 519.48 FPKM at
24 h. Similarly, comp46654_c0_seq1 showed a comparable
upward tendency in the uniconazole treated group.
However, its expression level was much lower than in
NS-0, NS-2 and NS-24. Furthermore, expression level
ofseveralCHI,FLS,F3H,F3’H, ANS, ANR, LAR, IFR
and GT4 encoding transcripts were increased by nutrient
starvation. Conversely, the highest expressed DFR tran-
script (comp36170_c1_seq2) was suppressed (176.81,
118.47 and 36.75 FPKM in NS-0, NS-2 and NS-24),
while several other lowly expressed DFR transcripts were
increased (comp19960_c0_seq2, comp44884_c0_seq1,
comp44884_c0_seq2 and comp44884_c0_seq3). In the
uniconazole treated group, the highly expressed FLS,
comp48210_c0_seq1, was increased in the first 5 h, but
suppressed thereafter by uniconazole. Meanwhile,
three F3’H encoding transcripts (comp43561_c0_seq1,
comp43561_c0_seq3, comp43561_c0_seq4) were also
suppressed by this plant growth regulator. Upon culti-
vation of L. punctata in full nutrient (1/6Hoagland)
Fig. 1 Phenylalanine metabolism networks in L. punctata. The abbreviations correspond to enzymes involved in phenylalanine metabolic networks.
Different colors represent different expression levels. PAL: phenylalanine ammonialyase, EC: 220.127.116.11. C4H: cinnamate 4-hydroxylase, EC: 18.104.22.168. 4CL:
4-coumarate-CoA ligase, EC: 22.214.171.124. HCT: hydroxycinnamoyl transferase, EC: 126.96.36.199. C3H: 4-coumarate 3-hydroxylase, EC: 188.8.131.52.
CCoAOMT: caffeoyl-CoA O-methyl transferase, EC: 184.108.40.206. COMT: caffeic acid o-methyl transferase, EC: 220.127.116.11. F5H: ferulate 5-hydroxylase,
EC:1.14.-.-. CCR: cinnamoyl-CoA reductase, EC: 18.104.22.168; CAD: cinnamyl-alcohol dehydrogenase, EC: 22.214.171.124; LACC: laccase, EC: 1.10. 3.2. CHS:
chalcone synthase, EC: 126.96.36.199. CHI: chalcone isomerase, EC: 188.8.131.52. F3H: flavanone 3-hydroxylase, EC: 184.108.40.206. FLS: flavonol synthase EC:220.127.116.11.
DFR: dihydroflavonol 4-reductase, EC: 18.104.22.168. F3’H: flavonoid 3'-hydroxylase, EC: 22.214.171.124. F3’5’H: EC: 126.96.36.199. FNS: flavone synthase, EC:188.8.131.52.
ANS: anthocyanidin synthase, EC: 184.108.40.206. ANR: anthocyanidin reductase, EC:220.127.116.11. LAR: leucoanthocyanidin reductase, EC:18.104.22.168. AS1: aureusidin
synthase, EC:22.214.171.124. The bold arrows show the main metabolic flux
Tao et al. BMC Genomics (2017) 18:166 Page 4 of 14
solution, the number of increased transcripts was larger
than that of the suppressed transcripts. For example,
comp39767_c0_seq4, comp39767_c0_seq6, comp46865_
c0_seq1, comp44243_c0_seq10, comp44483_c0_seq2,
comp35216_c0_seq1, comp35216_c1_seq1, comp35307_
c1_seq1, comp46833_c0_seq1, comp18376_c0_seq1,
comp41458_c0_seq1, comp46286_c0_seq1, comp46286_
c0_seq2, comp19956_c0_seq1, comp43561_c0_seq6,
comp46246_c0_seq1 were increased in full nutrient condi-
tions. These results suggest that these three different treat-
ments may trigger different molecular responses.
iTRAQ based flavonoids biosynthetic analyses of L.
punctata treated with nutrient starvation or uniconazole
RNA-Seq study provides a global expression pattern to
reveal mRNA composition, but it cannot reveal infor-
mation about the proteome. As the newest developed
quantitative technology, iTRAQ is widely used for
proteome characterization. In this study, iTRAQ data
of previous studies  was re-analyzed using the tran-
scriptome described above as a reference database. The
abundance of the most detected flavonoid related pro-
teins, including the PAL, C4H, 4CL, CHS, CHI, F3H
Fig. 2 Expression changes of transcripts related to flavonoid biosynthesis based on RNA-Seq. A heatmap was drawn by HemI toolkit using log2FC
values . Most abbreviations correspond to the enzymes listed in Fig. 1. Transcripts with extremely low expression levels are not shown in this figure
Tao et al. BMC Genomics (2017) 18:166 Page 5 of 14
and ANS (Fig. 3, Additional file 3: Table S3), was de-
tected to be improved in L. punctata when grown in
distilled water. CHS (comp46654_c0_seq1), the first
pivotal catalyzer for the flavonoid biosynthetic branch,
was increased 6.92 times at 2 h, and 4.37, 8.71 and
15.28 times at 5, 24 and 72 h, respectively, when com-
pared with that of 0 h. Conversely, the first key enzyme
of the other branch of the phenylalanine metabolic net-
works, the lignin biosynthetic branch, failed to be detected
in starvation treated samples. Although 25 laccase tran-
scripts were assembled by our de novo RNA-Seq study,
none of the proteins corresponding to these transcripts
were detected by iTRAQ. F3H, DFR and ANS are the en-
zymes directing metabolic flux into the anthocyanin bio-
synthesis branch. In starvation treated L. punctata,the
expression of F3H (comp47195_c0_seq1) was increased
by 1.14, 1.04, 1.42 and 3.73 times at 2, 5, 24 and 72 h, re-
spectively, when compared with that of 0 h, whereas DFR
(comp44884_c0_seq2) was increased by 0.83, 0.83, 0.97
and 1.32, and 1.33, 1.00, 1.39 and 3.13 for ANS
(comp18732_c0_seq1), respectively. These results may in-
dicate that the metabolic flux was regulated by nutrient
starvation to direct more substrates toward the anthocya-
nin biosynthesis branch. Spraying with uniconazole re-
sulted in the levels of most flavonoid related proteins
being decreased. Three universal factors of phenylalanine
metabolism, PAL (comp39767_c0_seq1), C4H (comp46865_
c0_seq1) and 4CL (comp35307_c0_seq1), were suppressed
immediately (at 2 h) by uniconazole. Although the ex-
pression of C4H was increased thereafter, the 4CL was
suppressed in all of the four UT samples. The other
4CL, comp46135_c0_seq2, was also suppressed at 72 h
Fig. 3 Expression changes of proteins involved in flavonoid biosynthesis based on iTRAQ. A heatmap was drawn by HemI toolkit according to
log2FC values . Most abbreviations correspond to the enzymes listed in Fig. 1
Tao et al. BMC Genomics (2017) 18:166 Page 6 of 14
and 240 h. Furthermore, CHI (comp41458_c0_seq1),
IFR (comp46286_c0_seq1, comp46286_c0_seq2), COMT
(comp44590_c0_seq3, comp44487_c0_seq1), 3GT
(comp19783_c0_seq1, comp40167_c0_seq4), UF3GT
(comp45471_c0_seq2), and 5AT (anthocyanin 5-aromatic
acyltransferase, comp45766_c0_seq1) showed a downward
trend by the application of uniconazole.
Expression of lignin biosynthesis related genes
Lignin provides mechanical support for plant growth,
but is not necessary in duckweed, which floats on water
surfaces. It has been found that most of the lignin biosyn-
thesis related genes in L. punctata had lower expression
than that seen in the flavonoid biosynthesis pathway, and
the last key gene involved in lignin biosynthesis was only
poorly expressed . These results were supported by an
iTRAQ study of the same test samples . When treated
with 800 mg · L
uniconazole, the first enzyme of the lig-
nin biosynthetic branch, HCT, had limited expression
(Additional file 1: Table S1, Additional file 2: Table S2).
The highest expression level recorded, for HCT, was 14.64
FPKM in UT-5. For the other enzymes in this pathway,
only three transcripts had expression levels ≥100
FPKM, including comp46970_c0_seq1 (CCoAOMT),
comp44590_c0_seq3 (COMT) and comp36380_c1_seq1
(F5H). 25 laccase (LACC, EC: 126.96.36.199) encoding tran-
scripts were assembled and all had lower expression
levels than 10.00 FPKM (Additional file 1: Table S1,
Additional file 2: Table S2). The highest expressed tran-
script exhibited an expression abundance of 2.97, 5.10,
6.76, 4.95 and 2.75 FPKM in five samples, while expres-
sion levels of the other transcripts were all lower than
1.5 FPKM. iTRAQ proteomics profiling results also
strongly supported this view. When treated with nutri-
ent starvation, almost all key enzymes involved in lignin
biosynthesis were not detected . When exposed to
uniconazole and full nutrient medium, most of these
assembled transcripts were not detected either.
Expression of flavone, flavonol, isoflavonoid and
anthocyanin biosynthesis involved genes
The results described above suggest that the metabolic flux
may be primarily directed to the isoflavonoid or anthocya-
nin biosynthesis branches in L. punctata (Fig. 1). To verify
this, enzyme encoding genes involved in flavone, flavonol,
isoflavonoid and anthocyanin biosynthesis were carefully
analyzed. It was found that almost all genes involved in iso-
flavonoid biosynthesis, or the flavone and flavonol biosyn-
thesis pathway were not detected in the transcriptome.
Despite most anthocyanin biosynthesis related genes failing
to be identified, most detected transcripts were increased
by nutrient starvation and uniconazole (Additional file 1:
Table S1, Additional file 2: Table S2). Five UDP-glucose
flavonoid 3-O-glucosyltransferase (EC: 188.8.131.52, UF3GT)
encoding sequences, including comp44420_c0_seq1,
comp44420_c0_seq2, comp44420_c0_seq3, comp38450_
c0_seq2 and comp47570_c0_seq1, were identified. Four
of them (comp44420_c0_seq2, comp44420_c0_seq3,
comp38450_c0_seq2 and comp47570_c0_seq1) were in-
creased by nutrient starvation, while being slightly in-
creased by uniconazole treatment and suppressed by
full nutrient treatment. Moreover, expression levels of
two anthocyanidin 3-o-glucosyltransferase (GT1, EC:
184.108.40.206, comp46472_c0_seq3, comp46472_c0_seq14)
genes were also increased by the first two treatments
described above, but decreased by full nutrient treatment.
Whereas 5AT (comp19598_c1_seq1) was only increased
by uniconazole, anthocyanin 3-o-beta-glucosyltransferase
(3GT, 220.127.116.11, comp33618_c0_seq1) was increased by
starvation. These observations support the hypothesis that
the metabolic flux was mainly directed into the anthocya-
nin biosynthesis branch and not the others.
Flavonoid content of uniconazole and full nutrient
treated L. punctata
In a previous study, it was found that the total flavonoid
content of L. punctata increased from 4.51% to 5.56%
during nutrient starvation for 168 h, of which seven of
the 17 components showed an obvious increase .
Growing L. punctata under natural conditions, the same
number of flavonoid compounds was separated by spec-
troscopic, chemical and biochemical methods, and four
of these were identified as new flavonoids in duckweed
. However, whether these 17 flavonoid compounds
are the same as those observed in the starvation or uni-
conazole treated L. punctata has not been verified. In
this study, flavonoids were extracted and characterized
from uniconazole treated L. punctata following the
protocol described in the study of Wang, et al. . The
results showed that a total of 20 compounds were sepa-
rated, including the additional compounds 1, 9, 14, 15,
16, 17, 18, 19 and 20 that did not separate in the previ-
ous study (Fig. 4). In contrast to the starvation treated L.
punctata, all of the 20 compounds were decreased by
uniconazole treatment. In addition, several compounds
(compound 1, 3, 4, 5, 6, 7, 8, 9, 13, 14 and 17) were in-
creased and several were decreased (compound 11, 12,
15, 18, 19 and 20) by full nutrient treatment. The total
flavonoid content of entire plants changed from 2.83%
to 0.94% and 3.37% in uniconazole and full nutrient
treated L. punctata, respectively. Furthermore, it was
found that purple coloration accumulated on the frond
underside in starved L. punctata, whereas no obvious
changes were observed in the full nutrient group, and
only slight changes seen for uniconazole treatment
group (Fig. 5). These results suggest that anthocyanin
accumulation may be one of the main factors of flavon-
oid increase caused by nutrient starvation.
Tao et al. BMC Genomics (2017) 18:166 Page 7 of 14
Fig. 4 Flavonoid profiles of uniconazole or full nutrient treated L. punctata.aflavonoids of uniconazole treated L. punctata, 0342014-5-11, 0242014-5-11
and 0322014-5-11 corresponded to UT-0, UT-72 and UT-240, respectively. bflavonoids of full nutrient treated L. punctata, 0252014-5-10 and 0332014-5-11
corresponded to FN-72 and FN-240, respectively
Tao et al. BMC Genomics (2017) 18:166 Page 8 of 14
Special phenylalanine metabolic flux resulted in high
flavonoid and low lignin content
Duckweeds are the fastest growing and smallest flower-
ing plants. A number of studies have shown the poten-
tial for duckweeds to be developed as feedstock, for
biofuel production and as a natural purifier for swine
wastewater treatment [21, 25, 44–49], due to its high fer-
mentable starch level (40-70% of dry weight), negligible
lignin content and capacity to thrive on anthropogenic
wastewater [24, 25, 33, 42, 50–52]. More recently, its
high flavonoid content (>4% of dry weight) in crude
plant form [28, 29], has been found. As flavonoids play a
crucial role in plant defense against pathogens [16, 53],
they can be used to partially explain why duckweeds are
rarely infected by pathogens. With near-exponential
growth rates, duckweed can achieve a biomass of 13 to
38 metric tons/hectare/year dry weight , resulting in
more than 520 kg/hectare/year flavonoid production.
However, the molecular mechanism responsible for high
flavonoid content remains largely uninvestigated. Newly-
developed, high-throughput DNA sequencing technol-
ogy provides an opportunity for genome-wide global
transcriptome studies and metabolic pathway analyses.
In this study, phenylalanine metabolism involved genes
were carefully analyzed based on the RNA-Seq data of
starvation, uniconazole and full nutrient treated L.
punctata. Except flavone synthase, aureusidin synthase,
flavanone 7-O-beta-glucosyltransferase, and flavanone
7-O-glucoside 2''-O-beta-L-rhamnosyltransferase, all of
the other key enzymes involved in phenylalanine
metabolism were successfully detected from the transcrip-
tome (Fig. 1, Additional file 2: Table S2). p-coumaroyl
CoA is the common substrate for the biosynthesis of fla-
vonoid and lignin. The expression levels of CHS, HCT
and CCR provided cues that p-coumaroyl CoA may be
predominantly directed into the flavonoid branch and
rarely into the lignin branch, resulting in the high flavon-
oid and low lignin content in L. punctata (Fig. 1). It is well
known that lignin primarily provides mechanical support
for plants to stand upright and enables xylems to with-
stand the negative pressure generated during water trans-
port. Consequently, lignin is useless for L. punctata as
these plants usually grow on the water’s surface with no
need for mechanical support. To effectively avoid the ac-
cumulation of a helpless product, the metabolic flux is
therefore mainly directed into the flavonoid branch. With
this characteristic, L. punctata can be developed as a
promising resource plant for biofuels fermentation and
The following iTRAQ based proteomics analyses sup-
ported these results. The majority of lignin synthesis in-
volved transcripts identified by RNA-Seq were not
detected in the iTRAQ study. Although possibly due to
technology bias, these lignin related enzymes were present
in levels lower than the detection limit of this technology,
as most enzymes involved in the other branch were suc-
cessfully quantified using the same samples. Moreover, the
global expression pattern of the phenylalanine metabolism
pathway revealed that the metabolic flux was directed to
the following anthocyanin biosynthesis branch with prior-
ity, but not the isoflavonoid biosynthesis or flavone and
Fig. 5 Color change of frond underside under different growth conditions. L. punctata 0202 monoclonal was cultivated in 1/6 × Hoagland (FN),
1/6 × Hoagland and sprayed with 800 mg•L
uniconazole (Aoke Biotech Corp, Japan) solution on the surface (UT), or distilled water for 12 days (NS)
Tao et al. BMC Genomics (2017) 18:166 Page 9 of 14
flavonol biosynthesis branches (Fig. 1). Since L. punctata
also known as purple-backed duckweed due to the
reddish-purple tint on the underside of its fronds as a re-
sult of anthocyanin production, the metabolic flux can be
explained by its morphological characteristics. Further-
more, almost all of the enzymes involved in isoflavonoid
biosynthesis or the flavone and flavonol biosynthesis path-
way, failed to be de novo assembled using RNA-Seq reads,
probably because of extremely low levels of expression.
This study combined omics data to investigate flavonoid
biosynthesis in L. punctata for the first time. The expres-
sion profiling not only gives a valuable insight into the
molecular biological basis of the high flavonoid content in
L. punctata, but also supports the morphological charac-
teristics of this plant species by the analyses of metabolic
Nutrient starvation is the optimized method to accumulate
high starch and flavonoid content simultaneously in this
When growing L. punctata in distilled water, almost all
“essential mineral nutrients”were deficient resulting in
extreme nutrient starvation. To cope with this abiotic
stress, L. punctata immediately increased expression of
some transporters with the aim of increasing nutrient
acquisition , but without success due to the absence
of nutrients. The global physiological and metabolic sta-
tus was altered and starch biosynthesis was enhanced,
resulting in a high starch accumulation of 45% (dry
weight) in 168 h . These effects may be explained as
a stress escape or stress avoidance response to complete
the life cycle in advance by storing most carbon nutrients
and energy in starch (Fig. 6) . As a class of important
defense compounds, over-accumulation of flavonoids in
plants can enhance stress tolerances by inhibiting the gen-
eration of ROS in plants [13–15, 56–61]. Manipulating
flavonoid biosynthetic gene expression is an effective
method to alter the accumulation of flavonoids in Arabi-
dopsis and other plants [62–65]. In nutrient starvation
treated L. punctata, transcriptome analyses showed that
most flavonoid involved transcripts were increased (Fig. 2,
Additional file 2: Table S2), which was confirmed by
iTRAQ based proteome results (Fig. 3, Additional file 3:
Table S3). Metabolomic studies revealed a flavonoid accu-
mulation from the original 4.51 to 5.56% (dry weight) after
168 h, with seven of the 17 detected flavonoid compounds
having increased significantly , possibly due to the al-
tered expression of flavonoid biosynthetic genes. Further-
more, purple color accumulation on the frond undersides
correlated with the levels of flavonoids (Fig. 5). Overall,
these integrated results from transcriptome, proteome,
metabolome and morphology reveal a flavonoid based
stress response in distilled water.
Uniconazole, a plant growth retardant, has been exten-
sively applied in plants to increase tolerance and im-
prove quality by regulating endogenous hormone levels
[66–69]. Culturing duckweed in 1/6 × Hoagland medium
uniconazole is an optimized
method to accumulate high starch content for bioethanol
fermentation and biomass accumulation [26, 27]. The con-
tent of starch was increased from 3.16% to 48.01% in 240 h
. Different from that in distilled water treated L. punc-
tata, the biomass of uniconazole treated L. punctata was
almost equal to the control (1/6 × Hoagland) (Fig. 6), indi-
cating that 1/6 × Hoagland and 800 mg · L
did not create stress conditions and consequently did not
trigger extra demand for flavonoids. As expected, flavonoid
content was decreased from 2.83% to 0.94% at 168 h. Simi-
larly, expression profiling results showed that more than
half of the flavonoid involved genes were suppressed by
this growth retardant. In our previous study, it was found
Fig. 6 Growth status of L. punctata under different culture conditions.
L. punctata 0202 monoclonal was cultivated in 1/6 × Hoagland, 1/6 ×
Hoagland spraying with 800 mg•L
uniconazole (Aoke Biotech Corp,
Japan) solution on the surface, or distilled water for 12 days
Tao et al. BMC Genomics (2017) 18:166 Page 10 of 14
that uniconazole increased the content of abscisic acid
(ABA) and cytokinins (CK), and suppressed the synthesis
of gibberellin (GA) [26, 27]. As ABA, CK and GA usually
crosstalk with salicylic acid (SA), jasmonic acid (JA), other
endogenous hormones and small molecule regulators, al-
terations ion the levels of these regulators should affect the
regulatory network in L. punctata.Previousstudieshadre-
vealed that different endogenous hormones usually play
different roles in flavonoid biosynthesis. For example, su-
crose can induce anthocyanin biosynthesis, but its effect is
repressed by the addition of GA, whereas JA and ABA
have a synergic effect with sucrose . Accordingly, the
decreased level of flavonoid may be a result of interference
to the whole hormonal regulatory network in uniconazole
treated L. punctata. However, whether the flavonoid de-
crease is primarily caused by the change of ABA, GA, CK,
or uniconazole directly affecting the expression of some
flavonoid related key genes, still requires further investiga-
tion in the future.
Full nutrient (1/6 × Hoagland) is an optimized culture
medium, which usually cannot provide abiotic stress. So
that the physiological status of L. punctata would not be
altered in this study, starch and flavonoid content were
kept at normal levels. Although the growth status of the
nutrient starvation group was obviously suppressed
(Fig. 6), the total starch weight was increased by 42
times in 7 days . Comparatively, the biomass of uni-
conazole treated L. punctata was almost equal to the
control (1/6 × Hoagland), with starch weight increasing
by 46 times in 7 days . Therefore, although starva-
tion limits the accumulation of biomass, it can still have
the same effect on starch accumulation, which is caused
by a much lower dry matter rate in uniconazole treated
L. punctata. Since the flavonoid content was increased
by nutrient starvation, it can be surmised that nutrient
starvation is the optimized method for obtaining high
starch and high flavonoid content simultaneously in L.
punctata, while uniconazole treatment can only produce
high starch content.
Although some sampling time points of the RNA-Seq,
iTRAQ and metabolome studies were inconsistent, the
combined omics data reflect the changing trends of
mRNAs, proteins and flavonoid compounds, as these high
throughput technologies can characterize global gene ex-
pression patterns and metabolic status. In addition, a few
discordant results appeared in the expression results in
this study. As most enzymes were encoded by more than
one transcript, the non-matching results may have been
due to functional redundancy and spatio-temporal expres-
sion specificity of enzyme encoding transcripts.
Transcriptome and iTRAQ based expression profiling
revealed that high flavonoid and low lignin content of L.
punctata resulted primarily from phenylalanine meta-
bolic flux directed towards the flavonoid biosynthetic
pathway. Together with the metabolome assays, it was
found that full nutrient medium generated high biomass
with low starch and stable flavonoid content, unicona-
zole only induced starch accumulation accompanied by
a decreased flavonoid content, while nutrient starvation
triggered the accumulation of starch and flavonoids sim-
ultaneously. L. punctata has the potential to be devel-
oped as a resource plant for biofuel fermentation and
Plant materials and treatments
Monoclonal L. punctata 0202 was cultivated in 1/6 ×
Hoagland nutrient solution (total N = 58.3 mg/L, P =
25.8 mg/L) for 14 days under a 16/8 h day/night cycle,
with a light intensity of 130 μmol/m
/s, and a
temperature of 25 °C/15 °C during the day/night. For
the nutrient starvation group (NS), fresh fronds were
transferred into distilled water for further cultivation
over a period of two weeks. For the uniconazole treated
group (UT), fronds were subsequently cultivated in 1/
6 × Hoagland solution and sprayed on the surface with
800 mg · L
uniconazole (Aoke Biotech Corp, Japan)
solution. The other groups were cultivated in 1/6 ×
Hoagland solution (FN). Different time points following
the transfer of fronds into different media were selected
for flavonoid analyses. For each time point, more than
3 g fresh fronds were collected from three culture flasks
for each sample, corresponding to a total of >800
RNA extraction and RNA-Sequencing analyses
For each frond sample, more than 1 g fronds was
ground into powder in liquid nitrogen. Total RNA was
extracted using OMEGA™Plant DNA/RNA kit (OMEGA,
USA), following the manufacturer’s instructions, and gen-
omic DNA was removed by DNase I (Fermentas, USA).
More than 20 μg total RNA was then submitted to Beijing
Genomics Institute (BGI)-Shenzhen, Shenzhen, China
[http://www.genomics.cn] for quality control. The purity,
concentration and RNA integrity number (RIN) were
measured by an Agilent 2100 Bioanalyzer or SMA3000.
Qualified total RNAs were used for the following
mRNA purification and 200 bp fragmented cDNA library
construction, identical to that described in our previous
The validated fragmented cDNA library was submitted
to the Illumina Hiseq 2000 platform at BGI for tran-
scriptome sequencing. The 90 bp paired-end (PE) read
sequence and base-calling quality values were obtained
following the manufacturer’s instructions. The raw PE
reads were qualified by removing the reads with adapter
Tao et al. BMC Genomics (2017) 18:166 Page 11 of 14
sequence or excessive unknown bases. The clean reads
from the different samples were then pooled together
and de novo assembled using Trinity (v2012-06-08) with
the default parameters . Length distribution was
assessed by common perl scripts to generate the N50
number, average length, max length and contig number
during different length intervals.
To profile the genome-wide expression patterns, all reads
were aligned back to the assembly using perl scripts in the
Trinity package (v2012-06-08)  for each RNA-Seq sam-
ple separately. The aligned read number was calculated
and presented as digital expression levels for each contig.
These values were then normalized for each RNA-Seq
sample by RESM-based algorithm using perl scripts in the
Trinity package (v2012-06-08)  to get FPKM values.
A BlastX sequence similarity search against the non-
redundant protein database (NR) of NCBI [http://
www.ncbi.nlm.nih.gov/] was conducted by a locally installed
blast program (ncbi-blast-2.2.28+, ftp://ftp.ncbi.nlm.nih.gov/
blast/executables/blast+/) to investigate functional annota-
tion for each contig. BlastX results were uploaded into
the Blast2GO platform [39, 40] for Kyoto Encyclopedia
of Genes and Genomes (KEGG) and Gene Ontology
Protein extraction and iTRAQ based proteomic analyses
For each frozen sample, total protein extraction, qualifi-
cation and digestion were performed as the method de-
scribed in our previous study . The digested peptides
were labeled following the manufacturer’s protocol with
iTRAQ® Reagent 8-plex Kit (AB SCIEX, USA) and sub-
sequently used for LC-MS/MS analyses using an AB
SCIEX TripleTOF™5600 mass spectrometer (AB SCIEX,
USA), coupled with an LC-20AB HPLC Pump system
(Shimadzu, Kyoto, Japan).
MS/MS data acquisition was performed with Analyst®QS2.0
software (AB SCIEX, USA), and processed by searching
against the database generated from the annotated tran-
scriptome using the Paragon™Algorithm and the Mascot
search engine (Matrix Science, London, UK; version
2.3.02). The relative abundance was analyzed by the report
ion peak areas as previously described . For protein
quantitation, it was required that a protein contains at
least two unique peptides.
Flavonoid content and classification
Flavonoid extraction and isolation were performed follow-
ing the methods described in our previous study . The
flavonoid content of each frond sample was measured by
spectrophotometry with a spectrophotometer (Varioskan
Flash, Thermo Corp, USA) and HPLC (Thermo spectra
system AS3000, Thermo Corp, USA)-UV (Thermo
UV6000 Detector, USA) following the methods [72, 73].
HPLC/MS analyses of flavonoids were performed on
an Agilent series 1100 HPLC instrument (Agilent,
Waldbronn, Germany) coupled with a quadrupole time-
of-flight (Q-TOF) mass spectrometry (micrOTOF-Q II;
Bruker, Bremen, Germany) mainly in positive-ion mode.
The ESI source conditions were set following the method
of Yang . The mass data were processed by Bruker
Compass DataAnalysis 4.0 software.
Additional file 1: Table S1. Sequence annotation and expression
profiling. (XLSX 20158 kb)
Additional file 2: Table S2. Transcript levels of flavonoid metabolism
related contigs. (XLSX 58 kb)
Additional file 3: Table S3. Quantities of flavonoid metabolism related
proteins. (XLSX 11 kb)
ABA: Abscisic acid; CKs: Cytokinins; DW: Dry weight; EC: Enzyme codes;
FN: Full nutrient; FPKM: Fragments Per Kilobase of transcripts per Million
mapped fragments; GA: Gibberellins; iTRAQ: Isobaric tags for relative and
absolute quantitation; JA: Jasmonic acid; log2FC: log2 fold-change;
NGS: Next-generation sequencing; NR: Non-redundant protein database;
NS: Nutrient starvation; PE: Paired-end; RNA-Seq: RNA-sequencing;
SA: Salicylic acid; UT: Uniconazole treated
This work was supported by the National Natural Science Foundation of China
(No. 31400218), the National Key Technology R&D Program of China (No.
2015BAD15B01) and the Projects of International Cooperation of Ministry
of Science and Technology of China (No. 2014DFA30680).
Availability of data and materials
The transcriptome datasets supporting the conclusions of this article are
available in the [NCBI’s Sequence Read Archive database (SRA) database]
repository under the accession number of PRJNA185389 [unique persistent
identifier and hyperlink to dataset(s) in http://www.ncbi.nlm.nih.gov/
XT conceived the study, carried out the data analysis, drafted and revised the
manuscript. YF drafted and revised the manuscript. YX carried out the data
analysis and revised the manuscript. MJH carried out the biochemical assays
and HPLC experiment, drafted and revised the manuscript. YL carried out the
biochemical assays and revised the manuscript. XRM conceived the study
and revised the manuscript. HZ conceived the study and revised the manuscript.
All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu,
Sichuan 610041, China.
University of Chinese Academy of Sciences, Beijing
Key Laboratory of Environmental and Applied Microbiology,
Chinese Academy of Sciences, Chengdu 610041, China.
College of Life
Science & Forestry, Chongqing University of Art & Science, Yongchuan,
Chongqing 402160, China.
Tao et al. BMC Genomics (2017) 18:166 Page 12 of 14
Received: 8 June 2016 Accepted: 7 February 2017
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