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Transcriptome Analysis and Metabolic Profiling of Green and Red Mizuna (Brassica rapa L. var. japonica)

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Mizuna (Brassica rapa L. var. japonica), a member of the family Brassicaceae, is rich in various health-beneficial phytochemicals, such as glucosinolates, phenolics, and anthocyanins. However, few studies have been conducted on genes associated with metabolic traits in mizuna. Thus, this study provides a better insight into the metabolic differences between green and red mizuna via the integration of transcriptome and metabolome analyses. A mizuna RNAseq analysis dataset showed 257 differentially expressed unigenes (DEGs) with a false discovery rate (FDR) of <0.05. These DEGs included the biosynthesis genes of secondary metabolites, such as anthocyanins, glucosinolates, and phenolics. Particularly, the expression of aliphatic glucosinolate biosynthetic genes was higher in the green cultivar. In contrast, the expression of most genes related to indolic glucosinolates, phenylpropanoids, and flavonoids was higher in the red cultivar. Furthermore, the metabolic analysis showed that 14 glucosinolates, 12 anthocyanins, five phenolics, and two organic acids were detected in both cultivars. The anthocyanin levels were higher in red than in green mizuna, while the glucosinolate levels were higher in green than in red mizuna. Consistent with the results of phytochemical analyses, the transcriptome data revealed that the expression levels of the phenylpropanoid and flavonoid biosynthesis genes were significantly higher in red mizuna, while those of the glucosinolate biosynthetic genes were significantly upregulated in green mizuna. A total of 43 metabolites, such as amino acids, carbohydrates, tricarboxylic acid (TCA) cycle intermediates, organic acids, and amines, was identified and quantified in both cultivars using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS). Among the identified metabolites, sucrose was positively correlated with anthocyanins, as previously reported.
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Article
Transcriptome Analysis and Metabolic Profiling of
Green and Red Mizuna (Brassica rapa L. var. japonica)
Chang Ha Park 1, , Sun Ju Bong 1, Chan Ju Lim 2, Jae Kwang Kim 3, * and Sang Un Park 1, *
1Department of Crop Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu,
Daejeon 34134, Korea; parkch804@gmail.com (C.H.P.); asop_258@naver.com (S.J.B.)
2Asia Seed Co., Ltd., 109-35, 518 Beon-gil, Gyeongchungdae-ro, Janghowon-eup, Icheon-si,
Gyeonggi-do 17414, Korea; cabbage@asiaseed.co.kr
3Division of Life Sciences and Bio-Resource and Environmental Center, Incheon National University,
Incheon 22012, Korea
*Correspondence: kjkpj@inu.ac.kr (J.K.K.); supark@cnu.ac.kr (S.U.P.); Tel.: +82-32-835-8241 (J.K.K.);
+82-42-821-5730 (S.U.P.); Fax: +82-32-835-0763 (J.K.K.); +82-42-822-2631 (S.U.P.)
Current address: Max-Planck-Institute of Molecular Plant Physiology, Am Müehlenberg 1,
14476 Potsdam-Golm, Germany.
Received: 3 July 2020; Accepted: 5 August 2020; Published: 8 August 2020
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Abstract:
Mizuna (Brassica rapa L. var. japonica), a member of the family Brassicaceae, is rich
in various health-beneficial phytochemicals, such as glucosinolates, phenolics, and anthocyanins.
However, few studies have been conducted on genes associated with metabolic traits in mizuna.
Thus, this study provides a better insight into the metabolic dierences between green and red
mizuna via the integration of transcriptome and metabolome analyses. A mizuna RNAseq analysis
dataset showed 257 dierentially expressed unigenes (DEGs) with a false discovery rate (FDR) of
<0.05. These DEGs included the biosynthesis genes of secondary metabolites, such as anthocyanins,
glucosinolates, and phenolics. Particularly, the expression of aliphatic glucosinolate biosynthetic
genes was higher in the green cultivar. In contrast, the expression of most genes related to indolic
glucosinolates, phenylpropanoids, and flavonoids was higher in the red cultivar. Furthermore,
the metabolic analysis showed that 14 glucosinolates, 12 anthocyanins, five phenolics, and two
organic acids were detected in both cultivars. The anthocyanin levels were higher in red than in
green mizuna, while the glucosinolate levels were higher in green than in red mizuna. Consistent
with the results of phytochemical analyses, the transcriptome data revealed that the expression
levels of the phenylpropanoid and flavonoid biosynthesis genes were significantly higher in red
mizuna, while those of the glucosinolate biosynthetic genes were significantly upregulated in green
mizuna. A total of 43 metabolites, such as amino acids, carbohydrates, tricarboxylic acid (TCA) cycle
intermediates, organic acids, and amines, was identified and quantified in both cultivars using gas
chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS). Among the identified
metabolites, sucrose was positively correlated with anthocyanins, as previously reported.
Keywords: mizuna; transcriptome; metabolome; glucosinolates; anthocyanins; phenolics
1. Introduction
Plant species of the family Brassicaceae, previously called Cruciferae, have long been considered
health-boosting vegetables and are commonly cultivated worldwide because they provide high amounts
of dietary minerals, amino acids, carbohydrates, fatty acids, dietary fibers, vitamins(tocopherol, ascorbate,
and folate), and bioactive molecules, including glucosinolates, phenylpropanoids, anthocyanins,
and carotenoids. Furthermore, they have been commercially important as a main element of the
daily human diet as well as a source of vegetable oil for the food and biodiesel industry [15].
Foods 2020,9, 1079; doi:10.3390/foods9081079 www.mdpi.com/journal/foods
Foods 2020,9, 1079 2 of 13
Glucosinolates, found mainly in Brassicaceae plants, are a variable and diverse group of natural
products, representing a wide range of more than 200 naturally occurring secondary metabolites [
6
] and
share a general structure composed of a D-thioglucose moiety, a sulfonated oxime group, and a flexible
side-chain derived from phenylalanine (Phe), methionine (Met), tryptophan (Trp), and branched-chain
amino acids [
5
]. Subsequently, an endogenous enzyme, namely myrosinase, hydrolyzes glucosinolates
to a variety of biologically active compounds, including vinyl oxazolidinethiones, nitriles, epithionitriles,
isothiocyanates, thiocyanates, and indoles [
5
]. These compounds are involved in plant defense [
5
] and
exhibit a wide range of pharmaceutical and biological activities associated with the reduced risk of
breast, liver, lung, stomach, pancreas, colon, rectum, prostate, and colorectal cancers [1,4,5,7,8].
Phenylpropanoids, including lignin, flavonoids, coumarins, and a variety of small phenolic
molecules, are natural products with biological properties that contribute to plant protection
against environmental, physical, and biological stresses, such as a microbial, insect, and herbivore
attacks, plant-plant interactions, excessive exposure to visible (light) and ultraviolet radiation (UV),
drought, and low and high temperatures [
9
,
10
]. Moreover, consuming Brassicaceae family plants
is potentially beneficial to human health because they contain a variety of phenylpropanoids,
which have anti-allergic, anticancer, anti-estrogenic, antioxidant, vascular and cytotoxic antitumor,
and antimicrobial properties [1,4,11,12].
Anthocyanins, belonging to the flavonoid group, are plant pigments mainly responsible for
color development in dierent plant organs, and their basic structures consist of an anthocyanidin
(also called aglycon) attached to sugar moieties. Additionally, when linked to organic acids, they are
known as acylated anthocyanins [
13
]. Among the six major anthocyanidins (cyanidin, delphinidin,
malvidin, pelargonidin, peonidin, and petunidin) present in Brassicaceae vegetables, cyanidin is the
most ubiquitous [
11
]. Anthocyanins are involved in many plant physiological processes such as
photo-protection [
13
] and defense against environmental and biological stresses [
14
]. In addition,
they play a role in color development in flower petals, fruit peels, and seed coats, thereby facilitating
pollination and seed dispersal [15,16].
Mizuna (B. rapa L. var. japonica), commonly cultivated in Japan, is a leafy vegetable characterized
by dense leaf rosettes, pinnatisect-type leaves, and long and thin petioles [
17
]. This plant has been
used as a salad vegetable and has been shown to have human health-beneficial properties, such as
antioxidant [
18
,
19
] and anti-inflammatory eects [
19
]. Though mizuna is an important crop, there has
been no research on a comprehensive description of the metabolic dierence between the green and
red mizuna through transcriptome analysis based on next-generation sequencing (NGS) and mass
spectrometry-based metabolic profiling. Great progress in NGS technology enables an approach
to whole-transcriptome sequencing rather than whole-genome sequencing, such that an RNA-seq
technique provides functional information from the transcripts of the genome and is regarded as a
cost-eective approach [
20
]. Among the well-known NGS technologies, Illumina Solexa GA, one of
the “short-read” (36–72 bp) sequencing technologies, has been successfully used to perform the
whole-transcriptome analysis of the Brassicaceae species, such as Brassica. rapa [
21
], B. oleracea L. var.
capitata [
22
], B. juncea L. [
23
], and B. oleracea L. var. italic [
24
]. Furthermore, metabolic profiling is
commonly defined as the identification and quantification of low-molecular-weight metabolites and
intermediates produced in many biosynthetic and catabolic pathways in living organisms [25].
In this study, green and red mizuna cultivars were used as plant materials (Figure 1). We analyzed
the transcriptome and metabolome of these two cultivars using the Illumina Solexa platform,
GC-TOFMS, liquid chromatography electrospray ionization tandem mass spectrometric (LC-ESI-MS),
and high-performance liquid chromatography (HPLC) and comprehensively described the relationship
between all identified metabolites. To our knowledge, this is the first study to provide information on
metabolic dierences between green and red mizuna through transcriptome and metabolome analyses.
Foods 2020,9, 1079 3 of 13
Foods 2020, 9, x FOR PEER REVIEW 3 of 13
provide information on metabolic differences between green and red mizuna through transcriptome
and metabolome analyses.
Figure 1. Phenotypes of the green and red cultivars of mizuna.
2. Materials and Methods
2.1. Plant Material
Asia Seed Co., Ltd. (Seoul, Korea) provided plant samples of green and red cultivars of mizuna
(B. rapa L. var. japonica) cultivated at an experimental field of the Asia Seed R&D Center (Icheon,
Gyeonggi-do, Korea). Mizuna plants (Figure 1) were harvested after four months, treated with liquid
nitrogen (196 °C), and then stored at 80 °C. Both samples were ground into fine powders for RNA
extraction and HPLC analysis.
2.2. RNA Extraction and Illumina Sequencing
RNA extraction and Illumina sequencing were performed according to our previously reported
method (Jeon et al., [26]). Total RNA was extracted using the Plant Total RNA Mini Kit. The extracted
RNA was quantitated using a Nanodrop, and its integrity was measured through denaturing 1%
agarose gel electrophoresis. Subsequently, mRNA was separated and purified using Sera-Mag
Magnetic Oligo (dT) beads, and cDNA was synthesized for Illumina sequencing using the
Illumina/Solexa HiSeq2000 platform. RNA-sequencing analysis was performed to comprehensively
compare the characteristics of red and green mizuna transcriptomes. In total, 81,330,120 and
46,286,878 reads were obtained for green and red mizuna, making up 6.18 Gb (giga-bases) and 3.52
Gb, respectively, with an average length of 76 nucleotides per read. After filtering, 61,035,862 and
36,350,466 clean reads were obtained for the green and red mizuna samples, respectively, with Q30
values of 89.69% and 92.31%, respectively, (Table S1). The Bowtie2 software and the DESeq library
were used to estimate the expression abundance.
2.3. Assembly and Functional Annotation
After quality trimming of the raw RNA-sequencing reads, 81,330,120 and 46,286,878 high-
quality clean reads of green and red cultivars of mizuna, respectively, were prepared for
transcriptome assembly. The Trinity de novo assembly program
(https://github.com/trinityrnaseq/trinityrnaseq/wiki) was used to combine the overlapping reads into
contigs without gaps. Furthermore, the filtered reads were aligned back to the de novo assembled
Figure 1. Phenotypes of the green and red cultivars of mizuna.
2. Materials and Methods
2.1. Plant Material
Asia Seed Co., Ltd. (Seoul, Korea) provided plant samples of green and red cultivars of mizuna
(B. rapa L. var. japonica) cultivated at an experimental field of the Asia Seed R&D Center (Icheon,
Gyeonggi-do, Korea). Mizuna plants (Figure 1) were harvested after four months, treated with liquid
nitrogen (
196
C), and then stored at
80
C. Both samples were ground into fine powders for RNA
extraction and HPLC analysis.
2.2. RNA Extraction and Illumina Sequencing
RNA extraction and Illumina sequencing were performed according to our previously reported
method (Jeon et al. [
26
]). Total RNA was extracted using the Plant Total RNA Mini Kit. The extracted
RNA was quantitated using a Nanodrop, and its integrity was measured through denaturing 1%
agarose gel electrophoresis. Subsequently, mRNA was separated and purified using Sera-Mag Magnetic
Oligo (dT) beads, and cDNA was synthesized for Illumina sequencing using the Illumina/Solexa
HiSeq2000 platform. RNA-sequencing analysis was performed to comprehensively compare the
characteristics of red and green mizuna transcriptomes. In total, 81,330,120 and 46,286,878 reads
were obtained for green and red mizuna, making up 6.18 Gb (giga-bases) and 3.52 Gb, respectively,
with an average length of 76 nucleotides per read. After filtering, 61,035,862 and 36,350,466 clean reads
were obtained for the green and red mizuna samples, respectively, with Q30 values of 89.69% and
92.31%, respectively, (Table S1). The Bowtie2 software and the DESeq library were used to estimate the
expression abundance.
2.3. Assembly and Functional Annotation
After quality trimming of the raw RNA-sequencing reads, 81,330,120 and 46,286,878 high-quality
clean reads of green and red cultivars of mizuna, respectively, were prepared for transcriptome assembly.
The Trinity de novo assembly program (https://github.com/trinityrnaseq/trinityrnaseq/wiki) was used to
combine the overlapping reads into contigs without gaps. Furthermore, the filtered reads were aligned
back to the de novo assembled transcriptome sequences to validate the assembly and then mapped
into the B. rapa reference genome from the Brassica database (BRAD) (http://brassicadb.org/brad) using
TopHat2 (http://tophat.cbcb.umd.edu) Martin [
27
] and bowtie2 (http://bowtie-bio.sourceforge.net)
Foods 2020,9, 1079 4 of 13
(Kim et al. [28]). After normalizing expression levels by using the DESeq package in R, the transcript
expression levels were calculated using the Fragments Per Kilobase of transcript per Million mapped
reads (FPKM), and a false discovery rate (FDR) was applied to determine the significance cutoof 0.05
via DESeq. Gene ontology (GO) was performed for the dierentially expressed unigenes (DEGs) with
an FDR <0.05 in both cultivars. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Plant
Transcription Factor (PlantTFDB) databases were used for the further analysis of genome networks.
The statistical significance of DEGs was determined using the threshold setting (log2-fold changes of
≤−1 or 1 and an adjusted p-value of 0.05).
2.4. HPLC Analysis of Desulfo-Glucosinolates
Desulfoglucosinolates were extracted and analyzed as per previously reported procedures by
Park et al. [
29
]. Briefly, 100 mg dried green and red mizuna cultivars were extracted with 1.5 mL
of 70
C boiling aquatic methanol 70% (v/v) for 5 min and then centrifuged at 11,000
×
gat 4
C for
15 min. The supernatants were transferred into fresh tubes. The remaining pellets were re-extracted
twice more in the same manner. The final collected supernatants were loaded onto a mini-column
filled with DEAE-Sephadex A-25, followed by desulfation using 75
µ
L of an aryl sulfatase solution for
12 h. The resulting desulfoglucosinolate extract was further eluted with 0.5 mL of HPLC-grade water.
An Agilent Technologies 1200 Series HPLC System (Palo Alto, CA, USA) equipped with an Inertsil
®
ODS-3 column (150
×
3.0 mm i.d., particle size 3
µ
m; GL Sciences, Tokyo, Japan) and an Inertsil
®
ODS-2
guard column (10
×
2.0 mm i.d., particle size 5
µ
m) was used to separate glucosinolate components.
The HPLC conditions were set as follows: detection wavelength, 227 nm; oven temperature, 40
C;
flow rate, 0.2 mL min
1
; injection volume, 20
µ
L. The gradient program used was as follows: solvent A,
HPLC-grade water; solvent B, HPLC-grade acetonitrile; 0–18 min, 7–24% B; 18–32 min, 24% B; 32.01 min,
rapid drop to 7% B; and 32.01–40 min, 7% B (total 40 min). Quantification of desulfoglucosinolates
was performed as previously described by Park et al. [
29
]. Each compound was quantified using
sinigrin (internal standard) and the response factor of individual desulfoglucosinolates relative to the
internal standard.
2.5. HPLC Analysis of the Phenolic Compounds
Phenolics were extracted as per the previously reported method by Park et al. [
30
]. Briefly, 1 mL of
aqueous methanol (80% v/v) was added to a fresh tube containing fine powders (100 mg) of dried green
and red mizuna cultivars and vortexed thoroughly for 20 s. The extract was sonicated at temperatures
below 25
C for 60 min and centrifuged at 11, 000
×
gfor 15 min. Then, the supernatants were collected
into fresh tubes. The remaining sludge was used to re-extract phenolics two more times in the same
manner. The collected supernatants were dried using a vacuum concentrator and then dissolved in
0.5 mL of methanol. An NS-4000 HPLC system (Futecs, Daejeon, Korea) with a UV
Vis detector and a
C
18
column (250
×
4.6 mm, 5
µ
m; RStech, Daejeon, Korea) was used to isolate gallic acid, chlorogenic
acid, caeic acid, catechin, epi-catechin, vanillin, and benzoic acid. The gradient program was used
according to our previously reported method [
31
]. The mobile phase consisted of solvent A, ultrapure
water containing 0.2% acetic acid, solvent B, and methanol at a flow rate of 1 mL/min. The HPLC
running time was 98 min, the oven temperature was 30
C, and the detection wavelength was 280 nm.
Peak identification was performed by comparison with the retention times of the standard chemicals
and spike test, and quantification was carried out according to each calibration curve of eight phenolic
and organic compounds (Table S2). The standards used for analysis of the phenolic compounds are
gallic acid (
99%), vanillin (99%), catechin hydrate (
98%), (
)-catechin (
98%), benzoic acid (
99.5%),
caeic acid (98%), chlorogenic acid (95%), 4-hydroxybenzoic acid (99%) and were purchased from
Sigma-Aldrich Co., Ltd. (St. Louis, MO, USA).
Foods 2020,9, 1079 5 of 13
2.6. HPLC and LC-ESI-MS/MS Analysis of Anthocyanins
Anthocyanins were extracted as per our previously reported method (Park et al. [
31
]).
Anthocyanins were extracted from 100 mg fine powders (100 mg) of dried green and red mizuna
cultivars, with 2 mL water/formic acid (95:5 v/v), followed by gentle sonication for 20 min.
After centrifugation at 11,000
×
gfor 15 min, the extract was syringe-filtered into an LC vial. Dierent
anthocyanins were separated using an Agilent 1200 series HPLC linked to a 4000 Q-Trap LC-ESI-MS/MS
system with a Synergi 4
µ
m POLAR-RP 80A column (250
×
4.6 mm i.d., particle size 4
µ
m) combined
with a Security Guard Cartridges Kit AQ C18 column. The operating conditions and gradient program
were used as in our previously reported method (Park et al. [
31
]). Dierent anthocyanin quantifications
were performed using a standard calibration curve depicted from the commercial anthocyanin
(Cyanidin-3-O-glucoside (C3G)). C3G was used as an external standard and each anthocyanin was
expressed as milligram per C3G gram dry weight (mg/C3G g dry weight).
2.7. GC-TOFMS Analysis of Polar Metabolites
Hydrophilic were extracted as per our previously reported method (Park et al. [
29
]). Fine powders
(50 mg) of green and red mizuna were extracted with 1 mL of a chloroform-water-methanol mixture
(1:1:2.5 v/v/v) to which 60
µ
L of ribitol (0.2 g/L) was added as an internal standard. The extract was
shaken at 37
C and 1200
×
gfor 30 min and then centrifuged at 12,000
×
gfor 15 min. After the
supernatants were evaporated in a SpeedVac vacuum concentrator for 3 h, the extract was derivatized
by adding 80
µ
L of methoxy-amine hydrochloride/pyridine (20 g L
1
) and shaken at 37
C and 1200
×
g
for 2 h. Thereafter, 80
µ
L of N-methyl-N-(trimethylsilyl)trifluoroacetamide was added and the resulting
mixture was heated at 37
C for 30 min. After centrifugation, the final extract was transferred to a 2 mL
glass vial with a micro insert. The analysis equipment and operation conditions of GC-TOFMS were
as described in our previous study (Park et al. [
29
]). The quantification of the polar metabolite was
performed using selected ions, and the Chroma-TOF software was used to locate the peaks. The peak
identification of the GC-TOF/MS data was performed by comparing their retention times and mass
spectrum with standard compounds, in-house library, and MS library (Nist database). ChromaTOF
software was used to identify the hydrophilic compounds in mizuna cultivars. The results were filtered
with retention time, signal-to-noise ratio (>5:1), and mass spectral matching (based on a match >700) by
using reference compounds and the use of an in-house library. As a result, a total of 43 metabolites were
identified (i.e., Metabolomics Standards Initiative (MSI) level 1) Viant et al. [
32
]. The corresponding
retention times and their fragment patterns were agreed with our previous data (Park et al. [29]).
2.8. Statistical Analysis of Metabolites
A Student’s t-test was performed using the Statistical Analysis System (SAS, system 9.4, 2013;
SAS Institute, Inc., Cary, NC, USA). A volcano plot and a hierarchical cluster analysis (HCA) were
carried out, and Pearson correlations for 76 metabolites identified in these analyses were determined
using MetaboAnalyst 4.0 (http://www.metaboanalyst.ca/) with auto-scaling.
3. Results and Discussion
3.1. Functional Annotation and Classification of the Green and Red Mizuna Transcriptomes
The cDNA libraries of the green and red mizuna were mapped to the B. rapa reference genome
with coverages of 75.5% and 75.4%, respectively, (Table S3). Among the 257 DEGs with an FDR
<0.05, 94 were expressed at higher levels and 163 were expressed at relatively lower levels in the
red cultivar than in the green cultivar (Figure 2). A GO analysis of the DEGs was carried out using
DAVID (http://david.abcc.ncifcrf.gov/tools.jsp). The DEGs were assigned to the GO terms of biological
process (BP) and molecular function (MF) categories as shown in Table 1. In the BP category, the DEGs
were assigned to cell death (10 DEGs), apoptosis (eight DEGs), toxin catabolic process (four DEGs),
toxin metabolic process (four DEGs), sucrose metabolic process (three DEGs), defense response
Foods 2020,9, 1079 6 of 13
(19 DEGs), innate immune response (eight DEGs), response to temperature stimulus (nine DEGs),
secondary metabolic process (10 DEGs), response to bacterium (seven DEGs), multidrug transport
(four DEGs), oxidation reduction (19 DEGs), drug transport (four DEGs), response to drug (four DEGs),
and response to reactive oxygen species (five DEGs). In the MF category, the DEGs were assigned
to heme binding (11 DEGs), tetrapyrrole binding (11 DEGs), oxygen binding (eight DEGs), iron ion
binding (15 DEGs), glutathione transferase activity (four DEGs), electron carrier activity (14 DEGs),
and drug transporter activity (four DEGs). This result was consistent with the previous results of
Park et al. [33].
Foods 2020, 9, x FOR PEER REVIEW 6 of 13
response (19 DEGs), innate immune response (eight DEGs), response to temperature stimulus (nine
DEGs), secondary metabolic process (10 DEGs), response to bacterium (seven DEGs), multidrug
transport (four DEGs), oxidation reduction (19 DEGs), drug transport (four DEGs), response to drug
(four DEGs), and response to reactive oxygen species (five DEGs). In the MF category, the DEGs were
assigned to heme binding (11 DEGs), tetrapyrrole binding (11 DEGs), oxygen binding (eight DEGs),
iron ion binding (15 DEGs), glutathione transferase activity (four DEGs), electron carrier activity (14
DEGs), and drug transporter activity (four DEGs). This result was consistent with the previous results
of Park et al. [33].
Figure 2. Gene expression levels of green and red mizuna. The differentially expressed genes are
shown in red and green, and genes without expression changes are shown in black (false discovery
rate (FDR) < 0.05).
Table 1. Gene ontology terms (p-value and fold enrichment) that were significant in the enrichment
analysis in the gene list from the red vs. green mizuna cultivar comparison.
Category Term Count p-value Fold Enrichmen
t
Biological process
GO:0008219~cell death 10 0.00092 4
GO:0006915~apoptosis 8 0.0016 4.7
GO:0009407~toxin catabolic process 4 0.0104 8.8
GO:0009404~toxin metabolic process 4 0.0104 8.8
GO:0005985~sucrose metabolic process 3 0.0119 17.8
GO:0006952~defense response 19 0.0125 1.9
GO:0045087~innate immune response 8 0.0192 2.9
GO:0009266~response to temperature stimulus 9 0.024 2.6
GO:0019748~secondary metabolic process 10 0.0242 2.4
GO:0009617~response to bacterium 7 0.0339 2.9
GO:0006855~multidrug transport 4 0.0379 5.4
GO:0055114~oxidation reduction 19 0.0434 1.6
GO:0015893~drug transport 4 0.0445 5
GO:0042493~response to drug 4 0.0459 5
GO:0000302~response to reactive oxygen species 5 0.0497 3.6
GO:0020037~heme binding 11 0.00382 3.0
GO:0046906~tetrapyrrole binding 11 0.00653 2.8
GO:0019825~oxygen binding 8 0.00818 3.5
Molecular function
GO:0005506~iron ion binding 15 0.01239 2.1
GO:0004364~glutathione transferase activity 4 0.01243 8.2
GO:0009055~electron carrier activity 14 0.01295 2.1
GO:0015238~drug transporter activity 4 0.04875 4.9
3.2. Identification of Secondary Metabolite Biosynthetic Genes from the Green and Red Mizuna
Transcriptomes
Transcriptome analysis of mizuna cultivars revealed the identification of genes involved in the
biosynthesis of secondary metabolites, including glucosinolates, phenolics, and anthocyanins. Based
Figure 2.
Gene expression levels of green and red mizuna. The dierentially expressed genes are
shown in red and green, and genes without expression changes are shown in black (false discovery rate
(FDR) <0.05).
3.2. Identification of Secondary Metabolite Biosynthetic Genes from the Green and Red Mizuna Transcriptomes
Transcriptome analysis of mizuna cultivars revealed the identification of genes involved in
the biosynthesis of secondary metabolites, including glucosinolates, phenolics, and anthocyanins.
Based on the Arabidopsis Information Resource (TAIR) website and the basic local alignment search
tool (BLAST) program, 12 genes encoding enzymes involved in the glucosinolate biosynthesis
pathway and 10 genes encoding enzymes involved in the phenylpropanoid and flavonoid biosynthesis
pathways were identified in the transcriptome data of mizuna (Tables S4 and S5). Among these
12 identified genes, the expression of the gene encoding the transcription factor MYB28, which
regulates aliphatic glucosinolate biosynthesis, was significantly higher in green mizuna than in
red mizuna. In addition, the expression of the structural genes (branched-chain aminotransferase
4 (BCAT4); methylthioalkylmalate synthase 1 (MAM1); cytochrome p450, family 79, subfamily F,
polypeptide 1 (CYP79F1); cytochrome P450, family 83, subfamily A, polypeptide 1 (CYP83A1); tyrosine
transaminase family protein (SUR1), 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily
protein (AOP3), sulfotransferase 17 (ST5c), and desulfoglucosinolate sulfotransferase 18 (ST5b)),
involved in aliphatic glucosinolate biosynthesis were significantly higher in green mizuna. In addition,
the expression of the bile acid transporter 5 (BAT5) gene, required for aliphatic glucosinolate biosynthesis,
was upregulated in green mizuna. In contrast, the expression of the transcription factor MYB34,
which regulates indolic glucosinolate biosynthesis, was significantly upregulated in red mizuna
(Table S4). Furthermore, the key genes involved in flavonoid biosynthesis (dihydroflavonol 4-reductase
(DFR), leucoanthocyanidin dioxygenase (ANS), UDP-glucose: flavonoid 3-O-glucosyltransferase
(UF3GT), anthocyanin 5-O-glucosyltransferase (5GT), and transparent testa 19 (TT19)) as well as several
phenylpropanoid biosynthetic genes (cinnamate-4-hydroxylase (C4H) and hydroxycinnamoyl-CoA
shikimate/quinate hydroxycinnamoyl transferase (HCT)) were expressed at higher levels in red mizuna
than in green mizuna. In contrast, the 4-coumarate:CoA ligase 5 (4CL5) and caeate O-methyltransferase
Foods 2020,9, 1079 7 of 13
1 (COMT1) genes, which are involved in the phenylpropanoid pathway, were expressed at higher
levels in green mizuna than in red mizuna (Table S5).
Table 1.
Gene ontology terms (p-value and fold enrichment) that were significant in the enrichment
analysis in the gene list from the red vs. green mizuna cultivar comparison.
Category Term Count p-Value Fold Enrichment
Biological process
GO:0008219~cell death 10 0.00092 4
GO:0006915~apoptosis 8 0.0016 4.7
GO:0009407~toxin catabolic process 4 0.0104 8.8
GO:0009404~toxin metabolic process 4 0.0104 8.8
GO:0005985~sucrose metabolic process 3 0.0119 17.8
GO:0006952~defense response 19 0.0125 1.9
GO:0045087~innate immune response 8 0.0192 2.9
GO:0009266~response to temperature stimulus 9 0.024 2.6
GO:0019748~secondary metabolic process 10 0.0242 2.4
GO:0009617~response to bacterium 7 0.0339 2.9
GO:0006855~multidrug transport 4 0.0379 5.4
GO:0055114~oxidation reduction 19 0.0434 1.6
GO:0015893~drug transport 4 0.0445 5
GO:0042493~response to drug 4 0.0459 5
GO:0000302~response to reactive oxygen species
5 0.0497 3.6
GO:0020037~heme binding 11 0.00382 3.0
GO:0046906~tetrapyrrole binding 11 0.00653 2.8
GO:0019825~oxygen binding 8 0.00818 3.5
Molecular function
GO:0005506~iron ion binding 15 0.01239 2.1
GO:0004364~glutathione transferase activity 4 0.01243 8.2
GO:0009055~electron carrier activity 14 0.01295 2.1
GO:0015238~drug transporter activity 4 0.04875 4.9
3.3. Quantification of Glucosinolates in Green and Red Mizuna
Fourteen glucosinolates were detected in green mizuna, whereas only nine glucosinolates were
found in red mizuna (Table 2). The level of total glucosinolates was significantly higher in green mizuna
than in red mizuna. Specifically, glucoraphanin, glucoalyssin, and gluconapoleiferin were detected only
in green mizuna, and progoitrin and 4-hydroxyglucobrassicin levels were significantly higher in green
than in red mizuna. In contrast, gluconasturtiin was detected only in red mizuna and glucobrassicin,
4-methoxyglucobrassicin, and neoglucobrassicin were significantly higher in red than in green mizuna.
In particular, the highest accumulation patterns of most aliphatic glucosinolates (glucoiberin, progoitrin,
glucoraphanin, glucoalyssin, gluconapoleiferin, and gluconapin) were observed in the green cultivar,
whereas the red cultivar showed higher production patterns of indolic glucosinolates, represented
mainly by glucobrassicin, 4-methoxyglucobrassicin, and neoglucobrassicin. These results were
consistent with the results of the DEG analysis, revealing that the expression of the regulatory gene
MYB28 and structural genes (BCAT4,MAM1,CYP79F1,CYP83A1,SUR1,AOP3,ST5c, and ST5b)
responsible for aliphatic glucosinolate biosynthesis was higher in the green than in red mizuna,
but revealed that the expression of a regulatory gene MYB34 involved in indolic glucosinolate
biosynthesis was significantly higher in red than in green mizuna. Furthermore, these findings were
supported by previous studies reporting that BoaMYB28 overexpressing lines of Chinese kale showed
increased transcript levels of the aliphatic glucosinolate biosynthesis genes and increased levels of
Foods 2020,9, 1079 8 of 13
aliphatic glucosinolates. In contrast, the transcript levels and aliphatic glucosinolate levels decreased in
the BoaMYB28 RNAi transgenic lines of Chinese kale [
34
]. Similarly, Frerigmann and Gigolashvilli [
35
]
reported that MYB34 is the main transcription factor regulating indolic glucosinolate biosynthesis.
Table 2. Glucosinolate content in green and red kale (µmol/g dry weight).
Class Name Green Mizuna Red Mizuna
Glucoiberin 0.14 ±0.03 10.07 ±0.00
Progoitrin 0.31 ±0.05 *,2 0.16 ±0.04
Glucoraphanin 0.14 ±0.04 N.D. 3
Glucoalyssin 0.32 ±0.08 N.D.
Aliphatic glucosinolate Gluconapoleiferin 0.22 ±0.05 N.D.
Gluconapin 6.45 ±1.09 4.67 ±1.63
Glucobrassicanapin 0.40 ±0.07 2.37 ±0.84
Glucoerucin 3.45 ±0.59 N.D.
Glucoberteroin 2.71 ±0.47 N.D.
Phenethyl glucosinolate Gluconasturtiin N.D. 0.16 ±0.04
Indolic glucosinolate
4-Hydroxyglucobrassicin
0.26 ±0.11 * 0.05 ±0.02
Glucobrassicin 0.84 ±0.09 1.43 ±0.03 ***
4-Methoxyglucobrassicin
0.48 ±0.05 0.70 ±0.03 **
Neoglucobrassicin 0.08 ±0.01 0.28 ±0.05 **
Total 15.81 ±2.51 * 9.88 ±2.66
1
The values represent the means
±
standard deviation of three biological replicates.
2
Asterisks indicate significant
dierences as determined by the Student’s t-test (* p<0.05; ** p<0.01, *** p<0.001). 3N.D., Not detected.
3.4. Quantification of Phenolic and Organic Compounds in Green and Red Mizuna
Five phenolic and two organic compounds related to the biosynthesis of phenolic compounds
were detected in both green and red mizuna cultivars using HPLC (Table 3), whereas a total of
12 anthocyanins were identified only in red mizuna (Table 4). For the individual compounds, the levels
of caeic acid, (
)-epicatechin, and vanillin were higher in green mizuna, whereas those of gallic
acid and catechin were higher in red mizuna. Furthermore, cyanidins were the major anthocyanins
ubiquitous in red mizuna, and the red color might be derived from the identified cyanidin derivatives
in the red cultivar [
36
]. These HPLC results were in accordance with the results of the analysis of
DEGs which revealed that the expression of structural genes (C4H,DFR,ANS,UF3GT,5GT, and TT19)
responsible for the phenylpropanoid and flavonoid biosynthesis was significantly higher in red mizuna.
Similarly, Jeon et al. [
26
] reported that higher levels of cyanidin derivatives were present in red kale
than in green kale, which is consistent with the higher expression of anthocyanin biosynthetic genes in
red kale via metabolome and transcriptome analysis.
Table 3. Phenolic and organic compounds in green and red mizuna (µm/g dry weight).
Class Name Green Mizuna Red Mizuna
Phenolic acid
Gallic acid 1.48 ±0.18 4.71 ±0.25 *** 1
Chlorogenic acid 176.51 ±2.88 184.86 ±5.56
Caeic acid 120.09 ±6.03 *** 64.82 ±1.47
Flavonoid Catechin 154.16 ±0.90 234.07 ±6.15 **
()-Epicatechin 1351.16 ±21.66 *** 847.38 ±42.12
Organic compound
Vanillin 64.71 ±3.82 *** 5.09 ±1.28
Benzoic acid 195.20 ±22.33 220.89 ±14.38
Total 2063.30 ±23.08 *** 1561.82 ±66.89
1
The values represent the means
±
standard deviation of three biological replicates. Asterisks indicate significant
dierences as determined by the Student’s t-test (** p<0.01, *** p<0.001).
Foods 2020,9, 1079 9 of 13
Table 4. Anthocyanin content in green and red kale. (µmol/g dry weight).
Class Name Green Mizuna Red Mizuna
Flavonoids
Cyanidin 3-diglucoside-5-glucoside N.D. 10.02 ±0.00 2
Cyanidin 3-(sinapoyl)diglucoside-5-glucoside N.D. 0.16 ±0.01
Cyanidin 3-(caeoyl)(p-coumaroyl)diglucoside-5-glucoside N.D. 0.03 ±0.00
Cyanidin 3-(glycopyranosyl-sinapoyl)diglucoside-5-glucoside
N.D. 0.13 ±0.01
Cyanidin 3-(p-coumaroyl)(sinapoyl)triglucoside-5-glucoside N.D. 0.02 ±0.00
Cyanidin 3-(sinapoyl)glucoside-5-glucoside N.D. 0.20 ±0.02
Cyanidin 3-(p-coumaroyl)diglucoside-5-glucoside N.D. 0.11 ±0.01
Cyanidin 3-(sinapoyl)diglucoside-5-glucoside N.D. 0.25 ±0.02
Cyanidin 3-(p-coumaroyl)(sinapoyl)diglucoside-5-glucoside N.D. 0.04 ±0.01
Cyanidin 3-(feruloyl)(sinapoyl)diglucoside-5-glucoside N.D. 0.35 ±0.02
Cyanidin 3-(sinapoyl)(sinapoyl)diglucoside-5-glucoside N.D. 0.76 ±0.04
Cyanidin 3-(feruloyl)(sinapoyl)diglucoside-5-glucoside N.D. 0.15 ±0.01
Total 2.49 ±0.18
1N.D., Not detected. 2The values represent the means ±standard deviation of three biological replicates.
3.5. Quantification of Phenolic and Organic Compounds in Green and Red Mizuna
A total of 43 hydrophilic (two phenolic acids, three photorespiration intermediates, four TCA
cycle intermediates, five organic acids, 18 amino acids, and 11 sugars) were identified and quantified
in both cultivars using GC-TOFMS (Table S6). A comparison of amino acid levels between the
green and red mizuna cultivars indicated that the levels of valine, serine, leucine, isoleucine, proline,
glycine, threonine,
β
-alanine, aspartic acid, methionine, pyroglutamic acid, asparagine, glutamine,
phenylalanine, tryptophan, and glutamic acid were significantly higher in green mizuna, whereas
4-aminobutyric acid levels were only higher in red mizuna. In particular, the glutamine content was
consistent with the transcript levels of glutamine synthetase 1;4 (Table S7). Among the identified
sugars, xylose, fructose, glucose, mannose, and glycerol levels were significantly higher in green
mizuna. However, the levels of sucrose, maltose, trehalose, ranose, and inositol were higher in red
mizuna (Figure S1). Sucrose synthesis involves a two-step process catalyzed by two dierent enzymes,
sucrose-6-phosphate synthase (SPS) and sucrose-6-phosphate phosphatase (SPP), in plants. In the first
step of the sucrose biosynthetic pathway catalyzed by the SPS, sucrose-6-phosphate is synthesized
from uracil-diphosphate glucose (UDP-glucose) and fructose-6-phosphate through the SPS activity.
Next, SPP rapidly dephosphorylates sucrose-6-phosphate to sucrose and inorganic phosphate [
37
].
The produced sucrose can be further degraded to fructose and UDP-glucose by the activity of sucrose
synthase [
38
]. In this study, the sucrose level was consistent with the analysis of DEGs indicating the
higher expression of sucrose-phosphate synthase family protein (SPS4F) and sucrose-phosphatase 1
(SPP1) and lower expression of sucrose synthase 3 (SUS3) in red mizuna.
To obtain an insight into the correlation among the 73 metabolites identified in green and red
mizuna cultivars, an HCA was performed on the datasets using Pearson’s correlation results (Figure 3).
Glutamine, glutamic acid, aspartic acid, and asparagine comprise the metabolic network involved in
nitrogen metabolism into amino acids. In this study, glutamic acid was highly positively correlated
with glutamine (r=0.99958, p<0.0001), aspartic acid (r=0.98871, p<0.0005), and asparagine
(r=0.99881, p<0.0001). Strong correlations were observed between glutamic acid and the amino acids
of the glutamate family, including pyroglutamic acid (r=0.99872, p<0.0001) and proline (r=0.96723,
p<0.005), as well as between aspartic acid and the amino acids of the aspartate family, including
asparagine (r=0.98857, p<0.005), threonine (r=0.97286, p<0.005), methionine (r=0.97009, p<0.01),
isoleucine (r=0.89007, p<0.05), and beta-alanine (r=0.96221, p<0.005). In particular, sucrose had a
strong positive correlation with 12 anthocyanins identified (r>0.9, p<0.0001).
Sucrose is one of the main regulators of plant growth processes [
39
] and acts as an energy
source and an intermediate for metabolic processes [
36
]. The correlations between sucrose and
12 anthocyanins identified revealed a positive eect of sucrose on anthocyanin production, as supported
by previous studies reporting the eect of sucrose on anthocyanin biosynthesis. Shin et al. reported
Foods 2020,9, 1079 10 of 13
that the calcium-dependent sucrose uptake, activated by the external sucrose treatment, increased
the endogenous sugar pools, which induced anthocyanin accumulation by activating anthocyanin
biosynthetic regulatory genes (production of anthocyanin pigment 1 (PAP1) and PAP2) and structural
(CHS,DFR,ANS, and UF3GT) genes [
40
]. Additionally, the pho3 mutant showed large pools of sugars
(starch, fructose, sucrose, and glucose) and increased anthocyanin production [
41
], and the endogenous
sucrose pool had a strong positive correlation with anthocyanin in mulberry fruits [
42
]. The exogenous
sucrose supply enhanced the levels of pelargonidin derivatives in postharvest strawberry fruits [
43
]
and anthocyanin production in grapevine cell cultures [44].
Foods 2020, 9, x FOR PEER REVIEW 10 of 13
Figure 3. Correlation matrix of metabolites from green and red mizuna cultivars. Each square
indicates the Pearson’s correlation coefficient of a pair of compounds, and the value of the correlation
coefficient is represented by the intensity of the color ranging from deep blue to deep red, as indicated
on the color scale. 1, Cyanidin 3-diglucoside-5-glucoside; 2, Cyanidin 3-(sinapoyl)diglucoside-5-
glucoside; 3, Cyanidin 3-(caffeoyl)(p-coumaroyl)diglucoside-5-glucoside; 4, Cyanidin 3-
(glycolpyranosyl-sinapoyl)diglucoside-5-glucoside; 5, Cyanidin 3-(p-
coumaroyl)(sinapoyl)triglucoside-5-glucoside; 6, Cyanidin 3-(sinapoyl)glucoside-5-glucoside; 7,
Cyanidin 3-(p-coumaroyl)diglucoside-5-glucoside; 8, Cyanidin 3-(sinapoyl)diglucoside-5-glucoside;
9, Cyanidin 3-(p-coumaroyl)(sinapoyl)diglucoside-5-glucoside; 10, Cyanidin 3-
(feruloyl)(sinapoyl)diglucoside-5-glucoside; 11, Cyanidin 3-(sinapoyl)(sinapoyl)diglucoside-5-
glucoside; 12, Cyanidin 3-(feruloyl)(sinapoyl)diglucoside-5-glucoside.
Sucrose is one of the main regulators of plant growth processes [39] and acts as an energy source
and an intermediate for metabolic processes [36]. The correlations between sucrose and 12
anthocyanins identified revealed a positive effect of sucrose on anthocyanin production, as supported
by previous studies reporting the effect of sucrose on anthocyanin biosynthesis. Shin et al. reported
that the calcium-dependent sucrose uptake, activated by the external sucrose treatment, increased
the endogenous sugar pools, which induced anthocyanin accumulation by activating anthocyanin
biosynthetic regulatory genes (production of anthocyanin pigment 1 (PAP1) and PAP2) and
structural (CHS, DFR, ANS, and UF3GT) genes [40]. Additionally, the pho3 mutant showed large
pools of sugars (starch, fructose, sucrose, and glucose) and increased anthocyanin production [41],
and the endogenous sucrose pool had a strong positive correlation with anthocyanin in mulberry
fruits [42]. The exogenous sucrose supply enhanced the levels of pelargonidin derivatives in
postharvest strawberry fruits [43] and anthocyanin production in grapevine cell cultures [44].
4. Conclusions
To our knowledge, this is the first study to provide a comprehensive transcriptome and
metabolome analysis of primary and secondary metabolites in green and red mizuna. Based on the
high-throughput transcriptome data, the primary metabolite biosynthesis genes, including three
genes related to sucrose metabolism and one gene related to glutamine metabolism, as well as
Figure 3.
Correlation matrix of metabolites from green and red mizuna cultivars. Each square indicates
the Pearson’s correlation coecient of a pair of compounds, and the value of the correlation coecient
is represented by the intensity of the color ranging from deep blue to deep red, as indicated on the
color scale. 1, Cyanidin 3-diglucoside-5-glucoside; 2, Cyanidin 3-(sinapoyl)diglucoside-5-glucoside;
3, Cyanidin 3-(caeoyl)(p-coumaroyl)diglucoside-5-glucoside; 4, Cyanidin 3-(glycolpyranosyl-sinapoyl)
diglucoside-5-glucoside; 5, Cyanidin 3-(p-coumaroyl)(sinapoyl)triglucoside-5-glucoside; 6, Cyanidin
3-(sinapoyl)glucoside-5-glucoside; 7, Cyanidin 3-(p-coumaroyl)diglucoside-5-glucoside; 8, Cyanidin
3-(sinapoyl)diglucoside-5-glucoside; 9, Cyanidin 3-(p-coumaroyl)(sinapoyl)diglucoside-5-glucoside;
10, Cyanidin 3-(feruloyl)(sinapoyl)diglucoside-5-glucoside; 11, Cyanidin 3-(sinapoyl)(sinapoyl)
diglucoside-5-glucoside; 12, Cyanidin 3-(feruloyl)(sinapoyl)diglucoside-5-glucoside.
4. Conclusions
To our knowledge, this is the first study to provide a comprehensive transcriptome and
metabolome analysis of primary and secondary metabolites in green and red mizuna. Based on
the high-throughput transcriptome data, the primary metabolite biosynthesis genes, including three
genes related to sucrose metabolism and one gene related to glutamine metabolism, as well as
secondary metabolite biosynthesis genes, include 12 genes involved in glucosinolate biosynthesis
and 10 genes responsible for phenylpropanoid and flavonoid biosynthesis in mizuna. Furthermore,
14 glucosinolates, 12 anthocyanins, five phenolics, two organic acids, and 43 hydrophilic were detected
Foods 2020,9, 1079 11 of 13
in red and green mizuna cultivars using the HPLC, ESI-LC/MS/MS, and GC-TOFMS analyses. Through
a comparative transcriptome and metabolome analysis, this study showed that the green mizuna
contained a higher content of aliphatic glucosinolates in accordance with the expression of genes
involved in aliphatic glucosinolate biosynthesis. In contrast, the red cultivar had a higher content
of indolic glucosinolates and anthocyanin, consistent with the expression of genes responsible for
indolic glucosinolate and flavonoid biosynthesis. Furthermore, a strong positive correlation between
sucrose and anthocyanins was observed to support the positive eect of sucrose on anthocyanin
biosynthesis. Taken together, these findings may help to develop breeding strategies and also to
improve the biosynthesis of glucosinolates and anthocyanins in mizuna.
Supplementary Materials:
The following are available online at http://www.mdpi.com/2304-8158/9/8/1079/s1.
Figure S1: Volcano plot of dierentially accumulated metabolites between green and red mizuna. The y-axis is the
negative log10 of pvalues and the x-axis is log2 of fold change. Red indicates that the metabolites identified in
green mizuna were significantly higher than those of red mizuna, blue indicates that the metabolites identified
in green mizuna were significantly lower than those of red mizuna, and grey indicates metabolites with no
significant dierence. Table S1: Summary of RNA sequence data, Table S2: Validation of HPLC analysis of
phenolic compounds, Table S3: Summary of genome mapping, Table S4: Putative glucosinolate biosynthetic genes
in the mizuna transcriptome., Table S5: Putative phenylpropanoid and anthocyanin biosynthetic genes in the
mizuna transcriptome., Table S6: Identified metabolites in GC-TOFMS chromatograms from mizuna extract.,
Table S7: Putative sucrose and glutamine biosynthetic genes in the mizuna transcriptome., Table S8. The fold
changes of the red relative to the green mizuna corresponding to Figure S1.
Author Contributions:
S.U.P. and J.K.K. designed the experiments and analyzed the data. C.H.P., S.J.B., and C.J.L.
performed the experiments and analyzed the data. C.H.P. wrote the manuscript. All authors read and approved
the final manuscript.
Funding:
This research was supported by a grant from the Next-generation BioGreen 21 Program (PJ01368602),
Republic of Korea and Golden Seed Project (213006051WTE11) funded by Ministry of Agriculture, Food and Rural
Aairs (MAFRA), Ministry of Oceans and Fisheries (MOF), Rural Development Administration (RDA) and Korea
Forest Service (KFS), Korea.
Conflicts of Interest: The authors declare no conflict of interest.
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... Anthocyanins are flavonoid-class pigments that play an important role in the coloration of different plant organs. In particular, anthocyanins are essential for the coloration of flowers, fruits, and seeds and facilitate flower pollination and seed dispersal (Park et al., 2020a). These pigments can be biosynthesized through phenylpropanoid and flavonoid biosynthesis pathways. ...
... Illumina RNA sequencing (RNA-seq) was done as described in our previous study (Park et al., 2020a(Park et al., , 2019d. Briefly, total RNA was extracted from the powders of the white, pink, and violet flowers, stored at -80 • C, using the total RNA mini kit for plants, followed by RNA quantification by nanodrop (NanoVue Plus, General Electric, Frieburg, Germany) and an integrity measurement through the use of 1% agarose gel electrophoresis. ...
... Assembly and functional annotation were performed as described in our previous study (Park et al., 2020a(Park et al., , 2019d. The trinity de novo assembly program was used to combine overlapping reads into contigs without gaps. ...
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... Similarly, previous studies have reported a strong positive correlation between glutamic acid and other amino acids in Morus alba fruits [40], Lycoris radiata flowers [22], and Brassica rapa L. var. japonica plants [41]. Furthermore, the larger pools of glutamic acid and phenylalanine, which are initial precursors for chlorophyll metabolism and phenolic compound metabolism, respectively, reflected the higher levels of chlorophyll a and chlorophyll b and phenolic compounds detected in green radish roots, supported by the strong positive correlations between glutamic acid and chlorophylls and between phenylalanine and phenolics, respectively. ...
... pekinensis) [51] and mizuna (Brassica rapa L. var. japonica) [41]. ...
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... Phenolic acid analysis was performed using a previously reported method [22]. Dried powders (0.1 g) of L. radiata flowers from the different developmental stages were extracted using 80% methanol (1 mL) and sonicated for 30 min at 25 • C. ...
... An HPLC analysis system, consisting of an OptimaPak C18 column (250 × 4.6 mm, 5 µm; RStech Co., Daejeon, Korea), a NS-4000 HPLC system, a NS-6000 auto-sampler (Futecs Co., Daejeon, Korea), a degasser, and a UV-Vis detector, was used to separate and quantify the polyphenol compounds in the sample extracts. The analytical conditions for the phenolic acid analysis were carried out based on our previous study [22]. Phenolic acids were identified by comparison with the retention time of gallic acid, 4-hydroxybenzoic acid, chlorogenic acid, caffeic acid, and pcoumaric acid standard chemical (Sigma-Aldrich Korea, Yongin, Korea) using the spiking test and were quantified with the corresponding calibration curves. ...
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... A colorimeter (Konica Minolta, CR-400, Japan) was used to determine the color of the mayonnaise, with L* denoting brightness, a* denoting redness, and b* denoting yellowness [53]. To get an average reading, measurements were made three times at different places. ...
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... Anthocyanin is one of the most significant pigments that decide leaf color. Anthocyanin-related studies in Brassica crops have focused on the isolation and identification of metabolites [33]. In this regard, Chiu et al. found that the purple cauliflower (Brassica oleracea var botrytis) contained cyanidin 3-(coumaryl-caffeyl) glucoside-5-(malonyl)-glucoside using high-performance liquid chromatography (HPLC)-ESI-MS/MS analysis [34]. ...
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... This result was consistent with our previous results, wherein the glucosinolates levels in PGK and PK varied significantly between the two cultivars [1]. In mizuna, compared to the red cultivar, the green cultivar showed the highest accumulation of glucosinolates content [38]. Similarly, a comparison of PCs between green and purple kenaf showed that the leaves of green kenaf had the highest phenolic content; however, the carotenoid content was the highest in the purple cultivar [39]. ...
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Kohlrabi is considered an important dietary vegetable worldwide. In this study, we investigated the growth and accumulation of phenolic compounds (PCs) and glucosinolates in sprouts of pale green and purple kohlrabi (Brassica oleracea var. gongylodes) in response to light and dark conditions. Pale green kohlrabi presented high fresh weight and root length irrespective of light treatment, whereas under dark conditions, it presented higher fresh weight and shoot length than purple kohlrabi. In contrast, the root length of both kohlrabies increased markedly under light conditions compared to that under dark conditions. Thirteen PCs and eight glucosinolates were detected and quantified in 10-day-old pale green and purple kohlrabies. In both kohlrabies, the individual and total phenolic levels were much higher under the light treatment than under the dark treatment. Under light and dark conditions, the total phenolic content was 6362.13 and 5475.04 µg/g dry weight in the pale green kohlrabi, respectively, whereas in the purple kohlrabi, it was 10,115.76 and 9361.74 µg/g dry weight, respectively. Dark conditions favored higher accumulation of glucosinolates than light conditions. Progoitrin, neoglucobrassicin, glucoerucin, and 4-methoxyglucobrassicin were the predominant glucosinolates in both kohlrabies and were present in much higher amounts in the pale green kohlrabi. In pale green kohlrabi under dark conditions, the total glucosinolates content was 4.75 and 2.62 times higher than that of the purple kohlrabi under light and dark conditions, respectively. Among individual glucosinolates, in the pale green kohlrabi under the dark condition, progoitrin was found to have the highest content, which was 90.28 and 54.51 times higher than that in the purple kohlrabi under light and dark conditions, respectively. These results show that the phenolic and glucosinolates levels varied widely, and these variations between the two types of kohlrabi under both light and dark conditions were significant. Our findings suggest that light and dark conditions enhance the accumulation of PCs and glucosinolates, respectively, during the development of kohlrabi seedlings.
... Furthermore, integration of transcriptome and metabolome analysis is a good way to comprehensively explore the metabolic differences between different cultivars (Park et al. 2020). With respect to evolution, comparative genome sequence confers the possibility to investigate evolutionary processes affecting genome structure and protein function that lead to the repeated evolution of GSL metabolism and diversity (Barco and Clay 2019). ...
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... This globally important agronomic and bioeconomic crop is the second-largest cultivated oilseed around the world, supplying about 15% of the global consumption of edible vegetable oils [1,2]. In addition to oil production, Brassica crop species are consumed as edible leafy vegetables, stems, roots, buds, flowers and seeds, including B. rapa (rapeseed, European turnip, turnip rape, field mustard, Chinese cabbage and mizuna), B. oleracea (broccoli, cabbage, Chinese kale, kale rape, cauliflower and kohlrabi), B. nigra (black or brown mustard), B. napus (winter oilseed, kohlrabi, cauliflower, broccoli and Chinese kale), B. juncea (Asian mustard) and Sinapis alba L. (white mustard) [3][4][5][6]. Demographic and lineage analyses suggested that these species might have evolved from a common ancestor and have similar seed morphologies [4]. The proteins constitute up to 50% of the seed and remain in the seed meal following oil extraction as a waste stream product [7]. ...
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Lycoris radiata belongs to the Amaryllidaceae family and is a bulbous plant native to South Korea, China, and Japan. Galantamine, a representative alkaloid of Amaryllidaceae plants, including L. radiata, exhibits selective and dominant acetylcholinesterase inhibition. In spite of the economic and officinal importance of L. radiata, the molecular biological and biochemical information on L. radiata is relatively deficient. Therefore, this study provides functional information of L. radiata, describe galantamine biosynthesis in the various organs, and provide transcriptomic and metabolic datasets to support elucidation of galantamine biosynthesis pathway in future studies. The results of studies conducted in duplicate revealed the presence of a total of 325,609 and 404,019 unigenes, acquired from 9,913,869,968 and 10,162,653,038 raw reads, respectively, after trimming the raw reads using CutAdapt, assembly using Trinity package, and clustering using CD-Hit-EST. All of the assembled unigenes were aligned to the public databases, including National Center for Biotechnology Information (NCBI) non-redundant protein (NR) and nucleotide (Nt) database, SWISS-PROT (UniProt) protein sequence data bank, The Arabidopsis Information Resource (TAIR), the Swiss-Prot protein database, Gene Ontology (GO), and Clusters of Orthologous Groups (COG) database to predict potential genes and provide their functional information. Based on our transcriptome data and published literatures, eight full-length cDNA clones encoding LrPAL2, LrPAL3, LrC4H2, LrC3H, LrTYDC2, LrNNR, LrN4OMT, and LrCYP96T genes, involved in galantamine biosynthesis, were identified in L. radiata. In order to investigate galantamine biosynthesis in different plant parts of L. radiata grown in a growth chamber, gene expression levels were measured through quantitative real-time polymerase chain reaction (qRT-PCR) analysis using these identified genes and galantamine levels were quantified by high-performance liquid chromatography (HPLC) analysis. The qRT-PCR data revealed high expression levels of LrNNR, LrN4OMT, and LrCYP96T in the bulbs, and, as expected, we observed higher amounts of galantamine in the bulbs than in the root and leaves. Additionally, a total of 40 hydrophilic metabolites were detected in the different organs using gas-chromatography coupled with time-of-flight mass spectrometry. In particular, a strong positive correlation between galantamine and sucrose, which provides energy for the secondary metabolite biosynthesis, was observed.
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Glucosinolates are Brassicaceae-specific secondary metabolites that act as crop protectants, flavor precursors, and cancer-prevention agents, which shows strong evidences of anticarcinogentic, antioxidant, and antimicrobial activities. MYB28, the R2R3-MYB28 transcription factor, directly activates genes involved in aliphatic glucosinolate biosynthesis. In this study, the MYB28 homology (BoaMYB28) was identified in Chinese kale (Brassica oleracea var. alboglabra Bailey). Analysis of the nucleotide sequence indicated that the cDNA of BoaMYB28 was 1257 bp with an ORF of 1020 bp. The deduced BoaMYB28 protein was a polypeptide of 339 amino acid with a putative molecular mass of 38 kDa and a pI of 6.87. Sequence homology and phylogenetic analysis showed that BoaMYB28 was most closely related to MYB28 homologs from the Brassicaceae family. The expression levels of BoaMYB28 varies across the tissues and developmental stages. BoaMYB28 transcript levels were higher in leaves and stems compared with those in cotyledons, flowers, and siliques. BoaMYB28 was expressed across all developmental leaf stages, with higher transcript accumulation in mature and inflorescence leaves. Over-expression and RNAi studies showed that BoaMYB28 retains the basic MYB28 gene function as a major transcriptional regulator of aliphatic glucosinolate pathway. The results indicated that over-expression and RNAi lines showed no visible difference on plant morphology. The contents of aliphatic glucosinolates and transcript levels of aliphatic glucosinolate biosynthesis genes increased in over-expression lines and decreased in RNAi lines. In over-expression lines, aliphatic glucosinolate contents were 1.5- to 3-fold higher than those in the wild-type, while expression levels of aliphatic glucosinolate biosynthesis genes were 1.5- to 4-fold higher than those in the wild-type. In contrast, the contents of aliphatic glucosinolates and transcript levels of aliphatic glucosinolate biosynthesis genes in RNAi lines were considerably lower than those in the wild-type. The results suggest that BoaMYB28 has the potential to alter the aliphatic glucosinolates contents in Chinese kale at the genetic level.
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Sucrose acts as a vital signal that modulates fruit ripening. In current study, 50 mM sucrose was applied in strawberry fruit to investigate the regulation of sucrose in anthocyanin synthesis after harvest. The results showed that sucrose treatment increased the contents of glucose, fructose and sucrose, which were 19.76 %, 15.83 % and 16.50 % higher, respectively, compared with control at the end of storage. The increase of glucose and fructose contents resulted from the activation of acid invertase by sucrose treatment. In addition, sucrose treatment specifically increased four pelargonidin derivatives, pelargonidin 3-glucoside, pelargonidin 3-rutinoside, pelargonidin 3-malonylglucoside and pelargonidin 3-methylmalonyglucoside, during the storage. Further, transcriptional profiles and enzyme activities analysis revealed that the accumulation of pelargonidin derivatives was related to the activation of the pentose phosphate pathway, shikimate pathway, phenylpropanoid pathway, and flavonoid pathway. These results provided new insights into the regulation of sucrose on the accumulation of individual anthocyanins.
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To better understand the molecular mechanism of color formation in different varieties of the mulberry fruit, we investigated the functional genes related to anthocyanin and betulinic acid biosynthesis using high-throughput transcriptome sequencing and detected the primary and secondary metabolites in the white (Morus alba L. cv. ‘Turkey’) and red (Morus alba L. cv. ‘Cheongil’) mulberry cultivars. We obtained 171,702,058 high-quality reads with an average read length of 125 bp. These reads were assembled into 51,272 and 51,159 unigenes in Turkey and Cheongil, respectively. We also identified the genes related to anthocyanin and triterpene biosynthesis and investigated their expression and metabolite profiles. Overall, our transcriptome sequencing provides valuable information that could be used in gene discovery, marker-assisted selection, and investigation of metabolic pathways in mulberry. Additionally, gene expression and metabolite profiles provide new insights into the underlying mechanism of anthocyanin and betulinic acid biosynthesis and relationship between primary and secondary metabolites.
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Kale (Brassica oleracea var. acephala) is a rich source of numerous health-benefiting compounds, including vitamins, glucosinolates, phenolic compounds, and carotenoids. However, the genetic resources for exploiting the phyto-nutritional traits of kales are limited. To acquire precise information on secondary metabolites in kales, we performed a comprehensive analysis of the transcriptome and metabolome of green and red kale seedlings. Kale transcriptome datasets revealed 37,149 annotated genes and several secondary metabolite biosynthetic genes. HPLC analysis revealed 14 glucosinolates, 20 anthocyanins, 3 phenylpropanoids, and 6 carotenoids in the kale seedlings that were examined. Red kale contained more glucosinolates, anthocyanins, and phenylpropanoids than green kale, whereas the carotenoid contents were much higher in green kale than in red kale. Ultimately, our data will be a valuable resource for future research on kale bio-engineering and will provide basic information to define gene-to-metabolite networks in kale.
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Kohlrabi (Brassica oleracea var. gongylodes) is a dietary Brassica vegetable with noted health-beneficial properties associated with its numerous metabolites. The aim of this study was to elucidate phenotypic variation between the two cultivars through comprehensive analysis of the relationship of their primary and secondary metabolites. High-performance liquid chromatography (HPLC) and gas chromatography time-of-flight mass spectrometry (GC-TOFMS) are considered useful tools for profiling primary and secondary metabolites. A total of 45 metabolites, including organic acids, amino acids, sugars, and an amine, were identified in pale green and purple kohlrabies using GC-TOFMS-based metabolic profiling. The resulting data sets were analyzed by principal component analysis to determine the overall variation, and the purple and pale green vegetables were separated by the score plots generated. Additionally, HPLC analysis of anthocyanins in both cultivars revealed that green kohlrabies did not contain any anthocyanidins, while 11 anthocyanins were quantified in the purple ones. Cyanidin was the dominant anthocyanin found in the purple cultivar, with cyanidin-3-(feruloyl)-diglucoside-5-glucoside being the major one. This study suggests that GC-TOFMS and HPLC are suitable tools to determine metabolic connection among various metabolites and describe phenotypic variation between green and purple kohlrabies.