Journal Pre-proof Transcriptomic and targeted metabolomic analysis identifies genes and metabolites involved in anthocyanin accumulation in tuberous roots of sweetpotato (Ipomoea batatas L.) Liheng He, Xiayu Liu, Shifang Liu, Jie Zhang, Yi Zhang, Yan Sun, Ruimin Tang, Wenbin Wang, Hongli Cui, Runzhi Li, Hongyan Zhu, Xiaoyun Jia PII:
To appear in:
Plant Physiology and Biochemistry
Received Date: 16 July 2020 Accepted Date: 15 September 2020
Please cite this article as: L. He, X. Liu, S. Liu, J. Zhang, Y. Zhang, Y. Sun, R. Tang, W. Wang, H. Cui, R. Li, H. Zhu, X. Jia, Transcriptomic and targeted metabolomic analysis identifies genes and metabolites involved in anthocyanin accumulation in tuberous roots of sweetpotato (Ipomoea batatas L.), Plant Physiology et Biochemistry, https://doi.org/10.1016/j.plaphy.2020.09.021. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Elsevier Masson SAS. All rights reserved.
Author Contributions: Xiaoyun Jia, Hongyan Zhu, Runzhi Li and Liheng He conceived the original research plans. Xiaoyun Jia and Liheng He designed the experiments. Liheng He, Xiayu Liu, Shifang Liu, Jie Zhang and Yan Sun collected the materials; Liheng He, Xiayu Liu, Shifang Liu and Yi Zhang conducted the experiments and analyzed the data. Liheng He and Xiaoyun Jia drafted the manuscript; Ruimin Tang, Wenbin Wang, Hongli Cui, Xiaoyun Jia, Runzhi Li and Hongyan Zhu modified the manuscript. All authors read and approved the manuscript. Funding: This study was funded by National Key Research and Development Program of China (2018YFD1000700, 2018YFD1000705), Key Research and
Development Project of Shanxi Province (201803D221008-6), Natural Science
Foundation of Shanxi Province (201801D121238), Science and Technology Innovation project of Shanxi Agricultural University (2018yz001), Shanxi Provincial
Leading Talents in Emerging Industries Project, Special Plan of Scientific Research
for Shanxi Agriculture Valley Construction of China (SXNGJSKYZX201701-03).
Transcriptomic and targeted metabolomic analysis identifies genes and
metabolites involved in anthocyanin accumulation in tuberous roots of
sweetpotato (Ipomoea batatas L.)
4 6 7 8 9 10 11 12
Liheng Hea#, Xiayu Liua#, ShifangLiub, Jie Zhanga, Yi Zhangb, Yan Suna, Ruimin Tangb, Wenbin Wanga, Hongli Cuia, Runzhi Lia, Hongyan Zhuc*, Xiaoyun Jiab,* a College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China b College of Life Sciences, Shanxi Agricultural University, Taigu, Shanxi, China c Department of Plant and Soil Sciences, University of Kentucky, Lexington, KY, United States * Correspondence: [email protected]
or [email protected]
Liheng He and Xiayu Liu contributed equally to this work.
Abstract: Purple-fleshed sweetpotato (PFSP) accumulates high amounts of
anthocyanins that are beneficial to human health. Although biosynthesis of such
secondary metabolites has been well studied in aboveground organs of many plants,
the mechanisms underlying anthocyanin accumulation in underground tuberous roots
of sweetpotato are less understood. To identify genes and metabolites involved in
anthocyanin accumulation in sweetpotato, we performed comparative transcriptomic
and metabolomic analysis of purple-fleshed sweetpotato (PFSP) and white-fleshed
sweetpotato (WFSP). Anthocyanin-targeted metabolome analysis revealed that
delphinidin, petunidin, and rosinidin were the key metabolites conferring purple
pigmentation in PFSP as they were highly enriched in PFSP but absent in WFSP.
Transcriptomic analysis identified 358 genes that were potentially implicated in
multiple pathways for the biosynthesis of anthocyanins. Although most of the genes
were previously known for their roles in anthocyanin biosynthesis, we identified 26
differentially expressed genes that are involved in Aux/IAA-ARF signaling.
Gene-metabolite correlation analysis also revealed novel genes that are potentially
involved in the anthocyanin accumulation in sweetpotato. Taken together, this study
provides insights into the genes and metabolites underlying anthocyanin enrichment
in underground tuberous roots of sweetpotato.
32 33 34
Keywords: Transcriptome; Metabolome; Sweetpotato; Anthocyanin accumulation; Underground tuberous roots
Sweetpotato (Ipomoea batatas L.; 2n = 6x = 90) is an important food crop worldwide
(Bovell‐Benjamin, 2007). While most sweetpotato cultivars are white or yellow
fleshed, others are purple fleshed because of accumulation of high amounts of anthocyanins. Anthocyanins are a major subclass of flavonoids that contribute to various pigmentations in plants (Moreau and Lampi, 2012). Anthocyanins have strong antioxidant activity and other bioactive properties that are beneficial to human health
benefits (Chalker‐Scott, 1999; Pojer et al., 2013). As such, purple-fleshed sweetpotato
(PFSP) is becoming a popular food.
Anthocyanin accumulation is regulated by the trade-off between biosynthesis and
breakdown. The biosynthetic pathway has been widely studied in model plants,
consisting of numerous enzymes that catalyze sequential reactions of anthocyanin
synthesis in cytoplasm (Koes et al., 2005). The pathway begins with the synthesis of
4-coumaroyl-CoA from phenylalaline catalyzed by phenylalanine ammonia lyase
(PAL), cinnamate 4-hydroxylase (C4H), and 4-coumaryol CoA ligase (4CL).
4-coumaroyl-CoA is first converted into naringenin chalcone by chalcone synthase
(CHS) and then isomerized by chalcone flavanone isomerase (CHI) into naringenin,
followed by conversion to dihydrokaempferol by flavanone 3-hydroxylase (F3H). In
most plants, dihydrokaempferol can be further hydroxylated by flavonoid
3′-hydroxylase (F3′H) or flavonoid 3′, 5′-hydroxylase (F3′5′H) into dihydroquercetin
or dihydromyricetin, respectively. Dihydrokaempferol, dihydroquercetin, and
dihydromyricetin form colored anthocyanidins (pelargonidin, cyanidin, and
delphinidin, respectively) by dihydroflavonol 4-reductase (DFR) and anthocyanidin
synthase (ANS, also known as leucoanthocyadinin dioxygenase or LDOX). The core
anthocyanidins found in plants are pelargonidin, cyanidin, delphinidin, peonidin,
petunidin, and malvidin, of which peonidin is 3’-methylated cyanidin, petunidin is
3’-methylated delphinidin, and malvidin is 3’- and 5’-methylated delphinidin.
Anthocyanidins are unstable and easily degraded, thus requiring glycosylation by
UDP-glucose anthocyanidin 3-O-glycosyltransferase (UFGT) for stabilization.
Anthocyanins refer to glycosylated forms of anthocyanidins. Subsequently,
glutathione S-transferases (GST) proteins catalyze the conjugation of glutathione to
anthocyanins. At the final step, the conjugated anthocyanins were pumped into
tonoplast by Multidrug and Toxic Compound Extrusion (MATE) transporters, where
they were accumulated and stored (Koes et al., 2005).Natural anthocyanins can carry
a wide variety of side chain decorations, resulting in various functionalities, including
pigmentations, interactions with pathogenic and symbiotic microbes, and their health
promoting effects (Croft, 1998).
Transcription of the genes encoding the enzymes in the anthocyanin pathway is
mainly regulated by three families of transcription factors (TFs), including MYB,
basic helix-loop-helix (bHLH) and WD40. These TFs form MYB-bHLH-WD40
(MBW) complexes, in which MYB TFs are primarily responsible for activation or
repression of the conserved MBW complexes by binding with the promoter regions of
the enzyme genes (Jaakola, 2013). Transcriptome sequencing identified numerous
MYB TFs associated with anthocyanin biosynthesis and their mode of action is
beginning to be revealed (Lotkowska et al., 2015; Hu et al., 2016; Lai et al., 2016;
Wang et al., 2018). For example, R2R3-MYB forms a complex with JAF13 (bHLH)
and WD40 to activate the transcription of AN1, a bHLH transcription factor. Then, the
R2R3-MYB activator interacts with AN1 and WD40 to activate anthocyanin
biosynthesis. In contrast, the MYB repressor negatively regulates anthocyanin
biosynthesis by competitive binding to the JAF13 and AN1, leading to reduced
formation of MBW activation complexes (Albert et al., 2014; D'Amelia et al., 2014).
In sweetpotato, IbMYB1 is expressed predominantly in the purple-fleshed storage
roots and plays an important role in anthocyanin biosynthesis. Ectopic overexpression
of IbMYB1 in Arabidopsis, tobacco and sweetpotato upregulated the expression of the
accumulation (Mano et al., 2007; Kim et al., 2010; Kim et al., 2020; Park et al.,
Additional regulatory factors have also been identified, such as CONSTITUTIVELY
PHOTOMORPHOGENIC1 (COP1), JASMONATE ZIM DOMAIN (JAZ) proteins,
SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) proteins, and the NAC
(NAM, ATAF1,2 and CUC2) proteins (Gou et al., 2011; Qi et al., 2011; Maier et al.,
2013; Zhou et al., 2015). In sweetpotato, the accumulation of anthocyanins appeared
to be also regulated by MADS-box transcriptional factors because the majority of the
sweetpotato calli became pigmented after transformation with the IbMADS10 gene
(Lalusin et al., 2006). Recently, anthocyanin biosynthesis was also found to be
influenced by auxin/indole acetic acids (Aux/IAA) and their cognate auxin response
factors (ARFs) (Qi et al., 2011; Wang et al., 2018).
Although anthocyanin metabolism has been well studied in aboveground plant organs
(e.g., flowers, fruits and leaves), the mechanisms underlying anthocyanin
accumulation in underground tuberous roots of sweetpotato are less understood.
Despite the identification of a large number of differentially expressed genes, their
role in the regulation of anthocyanin biosynthesis and accumulation remains obscure.
Integrative analysis of the differentially accumulated metabolites (DAMs) and
differentially expressed genes (DEGs) has proved to be a powerful tool to correlate
phenotypes and genes (Zhang et al., 2020; Zhou et al., 2020). To gain a better
understanding of the molecular and metabolic mechanisms of anthocyanin
pigmentation in sweetpotato, we carried out comparative analysis of the transcriptome
and anthocyanin-targeted metabolome data derived from the tuberous roots of a PFSP
cultivar and a WFSP cultivar. This analysis revealed genes and key metabolites that
contribute to anthocyanin pigmentation in underground tuberous roots of sweetpotato.
2. Materials and methods
2.1. Plant materials
The white-fleshed sweetpotato cultivar Xushu-18 (hereafter referred to as XS-18 or
WFSP) and the purple-fleshed sweetpotato cultivar Xuzishu-3 (hereafter referred to as
XZS-3 or PFSP) were used for anthocyanin-targeted metabolome and transcriptome
analysis. Field experiments were performed at the Shanxi Agricultural University
campus (Taigu, Shanxi, China). Three months after planting, tuberous roots with
similar shape and size were sampled. After gentle washing, they were cut into small
pieces and immediately frozen in liquid nitrogen and stored in a -80℃ ultra-low
freezer. Three tuberous roots from different plants were pooled together to form a
single biological replicate. For each cultivar, three biological replicates were used for
2.2 Spectrophotometric measurement of total anthocyanin content
The frozen tuberous roots were ground into a fine powder and 1.0 g powder was
incubated in 50 mL HCl/methanol (1% v/v) at 4℃. After dark incubation for 24 h, the
mixtures were first centrifuged at 12,000 rpm for 15 min, and then the absorbance of
aqueous extracts was determined by a UV-2450 spectrophotometer at a wavelength of
530nm and 657nm (Thermo Fisher, Vantaa, Finland). The total anthocyanin content
(QAnthocyanins) was calculated as (A530 - 0.25×A657) / g, where A530 and A657 are the
absorption values at the indicated wavelengths and g is the weight of the material used
(Mehrtens et al., 2005; Jia et al., 2015).
2.3 Anthocyanin-targeted metabolome analysis
The experiment was conducted at MetWare Biotechnology (Wuhan, China) following
the protocols described by Yuan et al. (2018). Prior to data analysis, the data reliability
was subjected to quality control (QC) assessment. Statistical analysis of the data
matrices containing the metabolite measurement values was performed with Analyst
software (version 1.6.1). Partial least squares-discriminant analysis (PLS-DA) was
performed to identify differentially accumulated metabolites (DAMs) between
samples. DAMs were defined by the parameter known as variable importance in
projection (VIP); metabolites with VIP ≥ 1 and fold change (FC) ≥ 2 or ≤ 0.5 between
samples were considered as differential metabolites.
2.4 RNA sequencing, expression data, GO and KEGG analysis
RNA sequencing was conducted by Novo Bioinformatics (Beijing, China). The raw
sequence data were deposited at NCBI with the accession number SRP268967.
Mapped reads for each gene were counted by HTSeq (version 0.6.1). FPKM
(fragments per kilobase of transcript per million mapped reads) values were used to
identify differentially expressed genes (DEGs). Transcripts with a |log2 (FC)| > 1 and
P-value 0.9), and then visualized using Cytoscape
3.1 Purple sweetpotato traits and targeted metabolome determination
The tuberous roots of XZS-3 display dark purple flesh while those of XS-18 are
white-fleshed (Fig. 1a). Consistent with this phenotypic difference, a higher content of
anthocyanin was detected in the tuberous roots of XZS-3 (Fig. 1b). In order to gain
insights into the differences in anthocyanin biosynthesis and accumulation, the two
cultivars were subjected to anthocyanin-targeted metabolome analysis. Metabolite
annotations based on a variety of metabolite information databases identified nine
anthocyanin-related metabolites, including peonidin O-hexoside, rosinidin O-hexoside,
cyanidin 3-O-glucoside, peonidin, peonidin O-malonylhexoside, delphinidin, cyanidin
3-O-rutinoside, petunidin 3-O-glucoside, and cyanidin (Table S2, Fig. 1c). Cluster and
differential analysis singled out six differentially accumulated metabolites (DAMs)
with log (FC) > 1 and p < 0.05 (Fig. 1c). In particular, rosinidin O-hexoside,
delphinidin, and petunidin-O-glucoside were widely present in XZS-3 (PFSP) but
absent in XS-18 (WFSP), while the contents of peonidin O-malonylhexoside and
cyanidin were much higher in PFSP than in WFSP (Fig. 1c, Table S3).
Fig. 1. Analysis of phenotype, anthocyanin content and metabolites of XS-18 and
XZS-3. (a) Overview of tuberous roots of purple-fleshed XZS-3 and white-fleshed
XS-18 used for anthocyanin quantification, anthocyanin-targeted metabolome and
transcriptome. (b) Total anthocyanin content in XS-18 and XZS-3. Each value was
indicated as mean values ±SD. (c) Clustering heatmap of anthocyanin metabolites.
The abscissa represented the samples. The ordinate represented different metabolite
3.2 Characterization of the PFSP and WFSP transcriptomes
We obtained the transcriptomes of XS-18 (WFSP) and XZS-3 (PFSP) cultivars by
RNA sequencing. A total of 181.3 million clean reads from XS-18 and XZS-3 can be
aligned with the sweetpotato reference genome (Table S4), of which 133.4 million
(73.4%) were mapped to unique genomic locations (Table S4). This experiment
generated 7,361 novel transcripts, 4,313 of which were annotated as protein-coding
genes (Table S5). These annotations enriched the genomic information for
sweetpotato. Overall, a total of 44,633 and 44,025 expressed genes (FPKM > 1.0)
were identified in WFSP and PFSP (Table S6), respectively. Veen diagram showed
that 40,132 genes were expressed in both WFSP and PFSP libraries, A total of 4,501
transcripts expressed uniquely in XS-18, and 3,893 transcripts only expressed in
cultivar XZS-3 (Fig. S1; Table S7).
3.3 Identification of DEGs between WFSP and PFSP
We performed comparative analysis of the PFSP (XZS-3) and WFSP (XS-18)
transcriptomes to identify DEGs that are potentially associated with phenotypic
differences between the two cultivars, especially those involved in anthocyanin
pathways. This analysis revealed 11,355 transcripts that were differentially expressed
between WFSP and PFSP, of which 5,980 were up-regulated and 5,374 were
down-regulated in PFSP (Table S8, Fig. 2a and Fig. 2b).
of ro -p re lP na ur Jo
Fig. 2. Expression profiling and GO analysis of DEGs between cultivars of XS-18
and XZS-3. (a) Volcanic map of DEGs, (b) A general Heatmap overview of the
expression pattern of DEGs between cultivars of XZS-3 and XS-18. (c) GO terms of
up-regulated transcripts in XZS-3. (d) GO terms of down-regulated transcripts in
XZS-3. The criteria for screening differential genes were log2 (FC) > 1, p < 0.05.
3.4 GO enrichment and KEGG pathway analysis of DEGs
The DEGs between the WFSP and PFSP cultivars were subjected to Gene Ontology
(GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These
analyses identified 358 genes that are implicated in multiple pathways involved in
biosynthesis of secondary metabolites (Table S8). The enriched genes were grouped
into three main GO categories: biological process, molecular function, and cellular
component. The genes with increased expression in PFSP were greatly enriched in
biological process category (Fig. 2c), while the genes with reduced expression in
PFSP were greatly enriched in molecular function category (Fig. 2d).
Among the genes with enhanced expression in PFSP, the GO terms enriched in the
biological process category included cellular amide and peptide metabolic process,
peptide biosynthetic process, and protein translation. In the molecular function
category, structural constituent of ribosome and structural molecule activity were
significantly enriched (Fig. 2c). The up-regulated genes are significantly enriched in
translation-related functions, suggesting that translation of regulatory and enzyme
genes may be enhanced to promote anthocyanin biosynthesis and accumulation.
Among the genes down-regulated in PFSP, RNA modification is enriched in
biological process, and ADP binding and “serine-type endopeptidase inhibitor activity”
are enriched in molecular function, and no obvious enrichment was detected in the
cellular component process (Fig. 2d). These genes may play a negative role in
anthocyanin biosynthesis and accumulation. The top 20-ranked KEGG pathways were
presented in Fig. S2. The DEGs were mainly enriched in biosynthesis of ubiquinone
and other terpenoid−quinone, biosynthesis of secondary metabolites, tyrosine
metabolism, glycolysis/gluconeogenesis and alanine, aspartate and glutamate
metabolism (Fig. S2).
3.5 Expression profiling of the enzyme and transporter genes related to
anthocyanin biosynthesis and accumulation
The transcription levels of the anthocyanin pathway-related enzyme and transporter
genes were compared between the PFSP (XZS-3) and WFSP (XS-18) cultivars (Fig. 3,
Table S9). This comparison revealed a higher level of expression for most of the
homologous enzyme genes in XZS-3, including two of the three PAL genes
(Tai6.52988 and Tai6.29387), five of the six 4CL genes (Tai6.8930, Tai6.45910,
Tai6.37076, Tai6.6371, and Novel06268), six of the seven CHS genes (Tai6.29634,
Tai6.46186, Tai6.53503, Tai6.45381, Tai6.1734, and Tai6.1732), three of the four
DFR genes (Tai6.3022, Tai6.16429, and Tai6.3019), all three LDOX genes
(Tai6.40394, Tai6.53285, and Tai6.42091), and all five UFGT genes (Tai6.16002,
Tai6.17387, Tai6.34855, Tai6.47630, and Tai6.47631). One CHI (Tai6.7312) and one
F3H (Tai6.9545) genes were identified in the sweetpotato genome, both of which
showed a higher level of expression in XZS-3. We also identified two
O-methyltransferase (OMT) genes, and one was up-regulated while the other one was
down-regulated in XZS-3. Among the 23 glutathione S-transferase (GST) genes, 13
were up-regulated while the other ten were down-regulated in XZS-3. In addition, five
multidrug and toxic compound extrusion (MATE) genes were identified and all
showed a lower expression level in XZS-3.
Fig. 3. Expression profiling of the representative enzyme and transporter genes
involved in anthocyanin pathways between XS-18 and XZS-3. In the middle of the
figure was the schematic of anthocyanin pathway. The outside of the figure was
heatmap diagrams showing the expression differences of the main genes between
XS-18 and XZS-3. Expressions of the genes validated by qRT-PCR were highlighted
in bold font. Phenylalanine ammonia lyase (PAL), 4-coumaroyl, CoA ligase (4CL),
chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), chalcone isomerase (CHI),
dihydroflavonol-4-reductase (DFR), leucoanthocyanidin dioxygenase (LDOX),
(UFGT), glutathione S-transferase (GST), multidrug and toxic compound extrusion
3.6 Expression profiling of TFs involved in anthocyanin pathways
TFs play important roles in regulation of anthocyanin biosynthesis by modulating the
expression of enzyme genes and other related genes. RNA-seq analysis identified a
total of 87 differentially expressed TF genes, including 21, 19, 16, 15, and 6 members
from the bHLH, MYB, C3H, ZF, and WD subfamilies, respectively (Fig. 4a, Table
S10), consistent with that the biosynthesis of anthocyanins is associated with the
formation of the MYB-bHLH-WD40 (MBW) activation/repression complexes. A
similar number of bHLH, MYB, and C3H genes were up- or down-regulated in PFSP.
Of the six WD genes, four were up-regulated while the other two were
down-regulated in XZS-3. Of the 15 ZF genes, 11 showed significant up-regulation in
XZS-3. In addition, 4, 3, and 2 members were identified from the TCP, bZIP, and
NAC subfamilies, respectively (Fig. 4A, Table S10). One of the four TCP genes and
two of the three bZIP genes showed a higher level of expression in XZS-3. Both of
NAC genes showed a lower level of expression in XZS-3. One far-red impaired
response1 (FAR1) gene was identified and up-regulated in XZS-3.
Fig. 4. Heatmap diagrams of TFs involved in anthocyanin and Aux/IAA-ARF
Pathways. (a) Profiling of differentially expressed anthocyanin-related TFs pathway,
(b) Profiling of differentially expressed auxin-related TFs. The nine different colors of
the first column corresponds to the nine different gene subfamilies. The other columns
in the heatmap represented the samples. The color scale bar on the right side
represented the average FPKM value of log-transformed. basic helix-loop-helix
(bHLH), MYB proteins (MYB), WD40 repeat proteins (WD), cys3His zinc finger
(C3H), zinc finger proteins (ZF protein), TCP proteins (TCP), basic region/leucine
zipper (bZIP), NAC transcription factor (NAC), far-red impaired response1 (FAR1).
3.7 Expression profiling of TFs associated with Aux/IAA-ARF Signaling Pathways
Auxin is an important plant hormone, but the relationship between auxin and
anthocyanin biosynthesis is unclear in sweetpotato. In this study, we identified 26
differentially expressed Aux/IAA and ARF TF genes associated with the auxin signal
pathway (Fig. 4b, Table S11), of which 21 showed elevated expression in the PFSP
cultivar, including Auxin-responsive proteins IAA13, IAA14, IAA16, IAA27, ARF4,
ARF6, ARF9, ARF12 and AUX22D. However, the other five appeared to be
down-regulated, including IAA26, ARF5, AUL1 and two AUX1.
3.8 Quantitative RT-PCR of DEGs
A total of 22 representative DEGs between WFSP and PFSP cultivars were selected
for qRT-PCR analysis. In general, the expression patterns of the 22 DEGs revealed by
qRT-PCR matched those derived from RNA-seq (Fig. 5). Notably, the expression of
the eleven enzyme genes were about 270-25,000 times higher in XZS-3 than in
of ro -p re lP na ur Jo 343 344
Fig. 5. Comparison of expression profiling of 22 representative genes profiled by
anthocyanin-related TFs and four auxin-related TFs. Columns above and below y-axis
0 represented expression determined by qRT-PCR and by RNA-seq in FPKM values,
respectively. IbActin was used as reference control. Relative gene expressions were
determined by the comparative 2-ΔΔCt method Bars represented the average values ±
SE of three separate biological replicates in triplicate. For statistical analysis,
two-tailed t-test of Dunnett was applied. The differences were defined to be
statistically significant when p ≤ 0.05 (indicate as *) and p ≤ 0.01 (indicate as **).
3.9 SNP identification
We assembled all the transcripts and found that 7,361 transcripts did not exist in the
standard annotation library (Table S13). We used Tophat2 to map the reads to the
reference genome (a WFSP genotype) and identified high-confidence SNPs based on
multiple criteria including read depth and allele frequency. Among these SNPs, we
focused on the sequence variability of enzyme genes related to anthocyanin
biosynthesis (Table S12). When compared with the reference genome, the UFGT,
A3G, DFR, and F3H alleles from PFSP are more polymorphic than the alleles from
WFSP. As shown in Fig. S3, the number of SNPs in PFSP is nearly twice that in
WFSP. In contrast, the numbers of SNPs in LDOX, CHS, F3'M, 3GGT, F3′,5′H, and
ANR were similar and did not show significant difference between PFSP and WFSP.
Therefore, there may be many functional SNPs in UGFT, A3G, DFR and F3H genes
that affect the expression or activity of these genes, resulting in natural variation in
3.10 Correlation analysis between transcriptome and metabolites
To further characterize the metabolic pathways for anthocyanin synthesis, we
constructed gene-metabolite networks by integrative analysis of the metabolome and
transcriptome data. For this purpose, six DAMs (peonidin O-hexoside, rosinidin
O-hexoside, peonidin O-malonylhexoside, delphinidin, petunidin 3-O-glucoside, and
cyanidin) and the top 1000 DEGs were used for association analysis (Fig. 6, Table
S13). Each DAM was significantly correlated with the DEGs, and we selected the
top100 web links for further analysis. Among these genes, GST (Tai6.17033,
Tai6.19248, Tai6.25547, and Tai6.24771), F3H (Tai6.9545), starch synthase 2 (SS2,
Tai6.26337), quinone oxidoreductase (QOR, Tai6.41481), wall-associated receptor
kinase 3 (WAK3, Tai6.36254), WRKY transcription factor 20 (WRKY20 and
Tai6.3520), serine carboxypeptidase-like 41 (SCPL41 and Tai6.35008), LDOX/ANT
(Tai6.42091), bHLH (Tai6.36440 and Tai6.28734), CHI (Tai6.15773), CHS
(Tai6.29634), and Zerumbone synthase (ZSD1, Tai6.5425) were found to be highly
correlated with the metabolites.
of ro -p re lP na
Fig. 6. Correlation network diagram of DAMs and DEGs. The larger the point, the
stronger the correlation. peonidin O-hexoside (POH), rosinidin O-hexoside (ROH),
peonidin O-malonylhexoside (POM), petunidin 3-O-glucoside (P3G).
Sweetpotato, a member of the Convolvulaceae family, has become one of the most
popular foods (Kwak, 2019). In PFSP, the purple flesh accumulates abundant
understanding the anthocyanin biosynthesis in sweetpotato will facilitate breeding or
engineering plants to boost the anthocyanin production (Kim et al., 2020). In this
study, the metabolome and transcriptome of PFSP and WFSP were characterized, in
order to gain insights into the genes and metabolites that are associated with
anthocyanin biosynthesis, accumulation, and regulation.
Analysis of the differentially accumulated metabolites between PFSP and WFSP
O-malonylhexoside, delphinidin, and cyanidin were specifically present or more
abundant in PFSP, indicating that anthocyanin metabolism is more active in PFSP
than in WFSP. In particular, delphinidin, peonidin and rosinidin, which contribute to
red or blue colors in plant organs, were highly present in PFSP but absent in WFSP
(Fig. 1, Table S2 and S3), suggesting that they are the key anthocyanin derivatives
conferring the purple pigmentation in PFSP.
The biosynthesis of anthocyanin involves numerous enzyme genes. Many of these
enzyme genes were differentially expressed between the PFSP and WFSP genotypes.
In particular, most of the CHS, CHI, F3H, DFR, and LDOX homologs showed a
higher level of expression in PFSP than in WFSP, indicating that these genes play key
roles in anthocyanin biosynthesis and accumulation in PFSP. In addition, five UFGT
genes, which are required for glycosylation to stabilize anthocyanins, also showed a
higher level of expression in PFSP when compared with WFSP, consistent with the
important roles that UFGT genes play in the anthocyanin pathway in other plants
(Kobayashi et al., 2004; Wang et al., 2013; Zhang et al., 2020; Zhou et al., 2020).
Glutathione S-transferases (GSTs) act as non-enzymatic carrier proteins to escort
conjugated anthocyanins to the MATE transporters at tonoplast (Edwards et al., 2000)
(Alfenito et al., 1998). Interestingly, among 23 differentially expressed GST genes
identified in this study, three (Tai6.30213, Tai6.17033, and Tai6.29612) were
significantly up-regulated (>500 times) in PFSP, suggesting that the three GSTs may
play important roles in anthocyanin transport in sweetpotato.
The expression of the enzyme genes in anthocyanin pathways is modulated by TFs.
This is achieved by physical interactions between R2R3-MYB, bHLH, and WD TFs,
forming ternary complexes (MBWs) responsible for the coordination of anthocyanin
biosynthesis (Jaakola, 2013). Consistent with this, more than half (46) of the 87
differentially expressed TFs belong to the R2R3-MYB, bHLH, and WD subfamilies,
highlighting their important roles in regulation of the anthocyanin pathway.
addition, we found two NAC100 genes that were significantly down-regulated in PFSP.
NAC TFs have a variety of biological functions. In peach, ppNAC1 activates the
transcription of ppMYB10.1 to promote anthocyanin pigmentation (Zhou et al., 2015).
The low expression of NAC100 genes in PFSP than in WFSP might suggest negative
roles of these genes in the anthocyanin biosynthesis or accumulation; similar
expression patterns were also observed for the NAC1 and NAC2 in purple-fleshed
sweetpotato (Chen et al., 2016).
Phytohormones are also an important factor affecting accumulation of anthocyanins in
plants (Qi et al., 2011; Wang et al., 2018). In carrot, increasing auxin concentrations
within a certain range inhibits the accumulation of anthocyanins (Ozeki and
Komamine, 1986). High concentrations of auxin significantly inhibited anthocyanin
biosynthesis in cultured callus of red-fleshed apple (M. sieversii f.niedzwetzkyana) (Ji
et al., 2014). In the apple fruit skin of ‘Red Delicious’ and its four generation bud
sport mutants, IAA and ABA had a positive regulatory effect on the anthocyanin
formation, while GA had an inhibitory effect (Li et al., 2018). Wang et al. (2018)
reported that the increasing NAA concentrations increased the expression of
Aux/IAA-ARF and decreased anthocyanin accumulation in apple. Interestingly, we
observed that 21 of the 26 auxin-related genes in the Aux/IAA-ARF family exhibited
significant up-regulation in PFSP (Fig. 4b, Table S11), suggesting that these
Aux/IAA-ARF signaling factors may modulate the expression of transcripts involved
in anthocyanin pathways. Specifically, auxin may trigger the expression of the
homologous genes encoding IAA13, IAA14, IAA16, IAA27, ARF4, and ARF6, which
act as activators in anthocyanin biosynthesis in PFSP. In contrast, IAA26, ARF5,
AUL1, AUX1, and LAX2 were down-regulated in PFSP and these genes may function
as repressors in anthocyanin biosynthesis. Aux/IAA-ARF TFs exhibit dynamic
functions in plants and have a central role in the hub of transcriptional networks. The
altered expressions of Aux/IAA-ARF TFs between WFSP and PFSP suggested a
novel metabolic function for Aux/IAA-ARF proteins.
In summary, our study revealed anthocyanin metabolites that contribute to the purple
pigmentation in purple-fleshed sweetpotato. We also showed that the altered
expression of the anthocyanin pathway genes and regulatory transcription factors
account for the difference in anthocyanin accumulation in PFSP and WFSP.
Furthermore, we identified DEGs, including TFs and enzyme genes that were not
previously implicated in anthocyanin biosynthesis. Functional study should be
performed in the future to validate their role in regulation of anthocyanin biosynthesis
in sweetpotato. Knowledge gained from this study will facilitate breeding and
engineering sweetpotato plants for enhanced anthocyanin accumulation.
470 471 472
Table S1 Primer sequences used for qRT-PCR analysis
Table S2 Determination of anthocyanin-targeted metabolites in sweetpotato
Table S3 Differentially accumulated metabolites in XS-18 and XZS-3
Table S4 The transcriptome profiling of XS-18 and XZS-3
Table S5 Annotated novel transcripts
Table S6 Expressed genes within XS-18 and XZS-3
Table S7 Co-expressed and specifically expressed genes between XS-18 and XZS-3
Table S8 DEGs between XS-18 and XZS-3
Table S9 The transcription levels of anthocyanin pathway-related structural genes
Table S10 Expression profiling of TFs associated with anthocyanin biosynthesis
Table S11 Expression profiling of auxin-related TF genes
Table S12 SNP numbers of structural genes related to anthocyanin biosynthesis
Table S13 Correlation analysis of the DAMs and DEGs
Fig. S1. Venn diagram of co-expressed and specifically expressed genes between
XS-18 and XZS-3.
Fig. S2. Functional Enrichment of DEG by KEGG analysis.
Fig. S3. The differences in the number of SNPs in the structural genes of anthocyanin
synthesis between PFSF and WFSF.
Author Contributions: Xiaoyun Jia, Hongyan Zhu, Runzhi Li and Liheng He
conceived the original research plans. Xiaoyun Jia and Liheng He designed the
experiments. Liheng He, Xiayu Liu, Shifang Liu, Jie Zhang and Yan Sun collected the
materials; Liheng He, Xiayu Liu, Shifang Liu and Yi Zhang conducted the
experiments and analyzed the data. Liheng He and Xiaoyun Jia drafted the manuscript;
Ruimin Tang, Wenbin Wang, Hongli Cui, Xiaoyun Jia, Runzhi Li and Hongyan Zhu
modified the manuscript. All authors read and approved the manuscript.
Funding: This study was funded by National Key Research and Development
Program of China (2018YFD1000700, 2018YFD1000705), Key Research and
Development Project of Shanxi Province (201803D221008-6), Natural Science
Foundation of Shanxi Province (201801D121238), Science and Technology
Innovation project of Shanxi Agricultural University (2018yz001), Shanxi Provincial
Leading Talents in Emerging Industries Project, Special Plan of Scientific Research
for Shanxi Agriculture Valley Construction of China (SXNGJSKYZX201701-03).
508 509 510 511 512 513 514
Albert, N.W., Davies, K.M., Lewis, D.H., Zhang, H., Montefiori, M., Brendolise, C., Boase, M.R., Ngo,
H., Jameson, P.E., Schwinn, K.E., 2014. A conserved network of transcriptional activators and repressors regulates anthocyanin pigmentation in eudicots. Plant Cell. 26, 962-980. http://doi.org/10.1105/tpc.113.122069. Alfenito, M.R., Souer, E., Goodman, C.D., Buell, R., Mol, J., Koes, R., Walbot, V., 1998. Functional complementation of anthocyanin sequestration in the vacuole by widely divergent glutathione S-transferases. Plant Cell. 10, 1135-1149. http://doi.org/10.1105/tpc.10.7.1135.
Anders, S., Huber, W., 2012. Differential expression of RNA-Seq data at the gene level–the DESeq package. Heidelberg, Germany: European Molecular Biology Laboratory (EMBL). Bovell‐Benjamin, A.C., 2007. Sweet potato: a review of its past, present, and future role in human nutrition. Advances in food and nutrition research. 52, 1-59. Chalker‐Scott, L., 1999. Environmental significance of anthocyanins in plant stress responses. Photochem. Photobiol. 70, 1-9. Chen, S.P., Lin, I.W., Chen, X., Huang, Y.H., Chang, S.C., Lo, H.S., Lu, H.H., Yeh, K.W., 2016. Sweet potato NAC transcription factor, IbNAC1, upregulates sporamin gene expression by binding the SWRE motif against mechanical wounding and herbivore attack. Plant J. 86, 234-248. http://doi.org/10.1111/tpj.13171. Croft, K.D., 1998. The chemistry and biological effects of flavonoids and phenolic acids. Ann N Y Acad Sci. 854, 435-442. http://doi.org/10.1111/j.1749-6632.1998.tb09922.x.
D'amelia, V., Aversano, R., Batelli, G., Caruso, I., Castellano Moreno, M., Castro-Sanz, A.B., Chiaiese, P., Fasano, C., Palomba, F., Carputo, D., 2014. High AN1 variability and interaction with basic
helix-loop-helix co-factors related to anthocyanin biosynthesis in potato leaves. Plant J. 80, 527-540. http://doi.org/10.1111/tpj.12653. functions
Edwards, R., Dixon, D.P., Walbot, V., 2000. Plant glutathione S-transferases: enzymes with multiple health.
Gou, J.Y., Felippes, F.F., Liu, C.J., Weigel, D., Wang, J.W., 2011. Negative regulation of anthocyanin
biosynthesis in Arabidopsis by a miR156-targeted SPL transcription factor. Plant Cell. 23, 1512-1522. http://doi.org/10.1105/tpc.111.084525.
He, L., Tang, R., Shi, X., Wang, W., Cao, Q., Liu, X., Wang, T., Sun, Y., Zhang, H., Li, R., Jia, X., 2019. Uncovering anthocyanin biosynthesis related microRNAs and their target genes by small RNA
and degradome sequencing in tuberous roots of sweetpotato. BMC Plant Biol. 19, 232. http://doi.org/10.1186/s12870-019-1790-2. Hu, D.G., Sun, C.H., Ma, Q.J., You, C.X., Cheng, L., Hao, Y.J., 2016. MdMYB1 regulates anthocyanin
515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558
and malate accumulation by directly facilitating their transport into vacuoles in apples. Plant Physiol. 170, 1315-1330. http://doi.org/10.1104/pp.15.01333.
Jaakola, L., 2013. New insights into the regulation of anthocyanin biosynthesis in fruits. Trends Plant Sci. 18, 477-483. http://doi.org/10.1016/j.tplants.2013.06.003. Ji, X.-H., Wang, Y.-T., Zhang, R., Wu, S.-J., An, M.-M., Li, M., Wang, C.-Z., Chen, X.-L., Zhang, Y.-M., Chen, X.-S., 2014. Effect of auxin, cytokinin and nitrogen on anthocyanin biosynthesis in callus cultures of red-fleshed apple (Malus sieversii f.niedzwetzkyana). Plant Cell Tissue & Organ Culture. 120, 325-337. http://doi.org/10.1007/s11240-014-0609-y. Jia, X., Shen, J., Liu, H., Li, F., Ding, N., Gao, C., Pattanaik, S., Patra, B., Li, R., Yuan, L., 2015. Small tandem target mimic-mediated blockage of microRNA858 induces anthocyanin accumulation in tomato. Planta. 242, 283-293. http://doi.org/10.1007/s00425-015-2305-5. Kim, C.Y., Ahn, Y.O., Kim, S.H., Kim, Y.H., Lee, H.S., Catanach, A.S., Jacobs, J.M., Conner, A.J., Kwak, S.S., 2010. The sweet potato IbMYB1 gene as a potential visible marker for sweet potato
http://doi.org/10.1111/j.1399-3054.2010.01365.x. Kim, H.S., Wang, W., Kang, L., Kim, S.-E., Lee, C.-J., Park, S.-C., Park, W.S., Ahn, M.-J., Kwak, S.-S., 2020. Metabolic engineering of low-molecular-weight antioxidants in sweetpotato. Plant
Biotechnology Reports. 14, 193-205. http://doi.org/10.1007/s11816-020-00621-w. Kobayashi, S., Goto-Yamamoto, N., Hirochika, H., 2004. Retrotransposon-induced mutations in grape skin color. Science. 304, 982. http://doi.org/10.1126/science.1095011. Koes, R., Verweij, W., Quattrocchio, F., 2005. Flavonoids: a colorful model for the regulation and evolution
http://doi.org/10.1016/j.tplants.2005.03.002. Kwak, S.S., 2019. Biotechnology of the sweetpotato: ensuring global food and nutrition security in the face
http://doi.org/10.1007/s00299-019-02468-0. Lai, B., Du, L.N., Liu, R., Hu, B., Su, W.B., Qin, Y.H., Zhao, J.T., Wang, H.C., Hu, G.B., 2016. Two LcbHLH transcription factors interacting with LcMYB1 in regulating late structural genes of anthocyanin biosynthesis in Nicotiana and Litchi chinensis during anthocyanin accumulation.
Front Plant Sci. 7, 166. http://doi.org/10.3389/fpls.2016.00166. Lalusin, A.G., Nishita, K., Kim, S.H., Ohta, M., Fujimura, T., 2006. A new MADS-box gene
(IbMADS10) from sweet potato (Ipomoea batatas (L.) Lam) is involved in the accumulation of anthocyanin. Mol Genet Genomics. 275, 44-54. http://doi.org/10.1007/s00438-005-0080-x.
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., Genome Project Data Processing, S., 2009. The sequence alignment/map format and
SAMtools. Bioinformatics. 25, 2078-2079. http://doi.org/10.1093/bioinformatics/btp352. Li, Y., Fang, J., Qi, X., Lin, M., Zhong, Y., Sun, L., Cui, W., 2018. Combined analysis of the fruit
metabolome and transcriptome reveals candidate genes involved in flavonoid biosynthesis in actinidia arguta. Int J Mol Sci. 19, 1471. http://doi.org/10.3390/ijms19051471.
Lotkowska, M.E., Tohge, T., Fernie, A.R., Xue, G.P., Balazadeh, S., Mueller-Roeber, B., 2015. The Arabidopsis transcription factor MYB112 promotes anthocyanin formation during salinity and
under high light stress. Plant Physiol. 169, 1862-1880. http://doi.org/10.1104/pp.15.00605. Maier, A., Schrader, A., Kokkelink, L., Falke, C., Welter, B., Iniesto, E., Rubio, V., Uhrig, J.F., Hulskamp, M., Hoecker, U., 2013. Light and the E3 ubiquitin ligase COP1/SPA control the
559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602
protein stability of the MYB transcription factors PAP1 and PAP2 involved in anthocyanin accumulation in Arabidopsis. Plant J. 74, 638-651. http://doi.org/10.1111/tpj.12153.
Mano, H., Ogasawara, F., Sato, K., Higo, H., Minobe, Y., 2007. Isolation of a regulatory gene of anthocyanin biosynthesis in tuberous roots of purple-fleshed sweet potato. Plant Physiol. 143, 1252-1268. http://doi.org/10.1104/pp.106.094425. Mehrtens, F., Kranz, H., Bednarek, P., Weisshaar, B., 2005. The Arabidopsis transcription factor MYB12 is a flavonol-specific regulator of phenylpropanoid biosynthesis. Plant Physiol. 138, 1083-1096. http://doi.org/10.1104/pp.104.058032. Moreau, R.A., Lampi, A.-M., Analysis methods for tocopherols and tocotrienols, in:
antioxidant-rich phytochemicals, John Wiley & Sons, Ltd., 2012, pp. 353-386. Ozeki, Y., Komamine, A., 1986. Effects of growth regulators on the induction of anthocyanin synthesis in carrot suspension cultures. Plant Cell Physiol. 27, 1361-1368. Park, S.C., Kim, Y.H., Kim, S.H., Jeong, Y.J., Kim, C.Y., Lee, J.S., Bae, J.Y., Ahn, M.J., Jeong, J.C., Lee, H.S., Kwak, S.S., 2015. Overexpression of the IbMYB1 gene in an orange-fleshed sweet potato cultivar produces a dual-pigmented transgenic sweet potato with improved antioxidant activity. Physiol Plant. 153, 525-537. http://doi.org/10.1111/ppl.12281. Pojer, E., Mattivi, F., Johnson, D., Stockley, C.S., 2013. The case for anthocyanin consumption to
483-508. http://doi.org/10.1111/1541-4337.12024. Qi, T., Song, S., Ren, Q., Wu, D., Huang, H., Chen, Y., Fan, M., Peng, W., Ren, C., Xie, D., 2011. The jasmonate-ZIM-domain proteins interact with the WD-Repeat/bHLH/MYB complexes to regulate jasmonate-mediated anthocyanin accumulation and trichome initiation in Arabidopsis thaliana. Plant Cell. 23, 1795-1814. http://doi.org/10.1105/tpc.111.083261. Wang, Y.C., Wang, N., Xu, H.F., Jiang, S.H., Fang, H.C., Su, M.Y., Zhang, Z.Y., Zhang, T.L., Chen, X.S., 2018. Auxin regulates anthocyanin biosynthesis through the Aux/IAA-ARF signaling pathway in apple. Hortic Res. 5, 59. http://doi.org/10.1038/s41438-018-0068-4. Wang, Z., Meng, D., Wang, A., Li, T., Jiang, S., Cong, P., Li, T., 2013. The methylation of the PcMYB10 promoter is associated with green-skinned sport in max red bartlett pear. Plant Physiol. 162, 885-896. http://doi.org/10.1104/pp.113.214700.
Young, M.D., Wakefield, M.J., Smyth, G.K., Oshlack, A., 2010. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 11, R14. http://doi.org/10.1186/gb-2010-11-2-r14.
Yuan, H., Zeng, X., Shi, J., Xu, Q., Wang, Y., Jabu, D., Sang, Z., Nyima, T., 2018. Time-course comparative metabolite profiling under osmotic stress in tolerant and sensitive tibetan hulless
barley. Biomed Res Int. 2018, 9415409. http://doi.org/10.1155/2018/9415409. Zhang, Q., Wang, L., Liu, Z., Zhao, Z., Zhao, J., Wang, Z., Zhou, G., Liu, P., Liu, M., 2020.
Transcriptome and metabolome profiling unveil the mechanisms of Ziziphus jujuba Mill. peel coloration. Food Chem. 312, 125903. http://doi.org/10.1016/j.foodchem.2019.125903.
Zhou, H., Lin-Wang, K., Wang, H., Gu, C., Dare, A.P., Espley, R.V., He, H., Allan, A.C., Han, Y., 2015. Molecular genetics of blood-fleshed peach reveals activation of anthocyanin biosynthesis by
NAC transcription factors. Plant J. 82, 105-121. http://doi.org/10.1111/tpj.12792. Zhou, W., Niu, Y., Ding, X., Zhao, S., Li, Y., Fan, G., Zhang, S., Liao, K., 2020. Analysis of carotenoid content and diversity in apricots (Prunus armeniaca L.) grown in China. Food Chem. 330,
promote human health: a review. Comprehensive Reviews in Food ence & Food Safety. 12,
603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628
A landscape of metabolites & genes in anthocyanin metabolism in sweetpotato tubers Delphinidin, petunidin & rosinidin were the key anthocyanins in purple sweetpotato A number of novel genes may function in anthocyanin pathway in purple sweetpotato 26 genes in Aux/IAA-ARF signaling may regulate anthocyanin in purple sweetpotato
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: