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:
S0981-9428(20)30470-8
DOI:
https://doi.org/10.1016/j.plaphy.2020.09.021
Reference:
PLAPHY 6396
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
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Development Project of Shanxi Province (201803D221008-6), Natural Science
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Foundation of Shanxi Province (201801D121238), Science and Technology Innovation project of Shanxi Agricultural University (2018yz001), Shanxi Provincial
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Leading Talents in Emerging Industries Project, Special Plan of Scientific Research
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for Shanxi Agriculture Valley Construction of China (SXNGJSKYZX201701-03).
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Transcriptomic and targeted metabolomic analysis identifies genes and
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metabolites involved in anthocyanin accumulation in tuberous roots of
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sweetpotato (Ipomoea batatas L.)
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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.
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Abstract: Purple-fleshed sweetpotato (PFSP) accumulates high amounts of
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anthocyanins that are beneficial to human health. Although biosynthesis of such
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secondary metabolites has been well studied in aboveground organs of many plants,
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the mechanisms underlying anthocyanin accumulation in underground tuberous roots
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of sweetpotato are less understood. To identify genes and metabolites involved in
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anthocyanin accumulation in sweetpotato, we performed comparative transcriptomic
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and metabolomic analysis of purple-fleshed sweetpotato (PFSP) and white-fleshed
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sweetpotato (WFSP). Anthocyanin-targeted metabolome analysis revealed that
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delphinidin, petunidin, and rosinidin were the key metabolites conferring purple
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pigmentation in PFSP as they were highly enriched in PFSP but absent in WFSP.
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Transcriptomic analysis identified 358 genes that were potentially implicated in
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multiple pathways for the biosynthesis of anthocyanins. Although most of the genes
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were previously known for their roles in anthocyanin biosynthesis, we identified 26
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differentially expressed genes that are involved in Aux/IAA-ARF signaling.
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Gene-metabolite correlation analysis also revealed novel genes that are potentially
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involved in the anthocyanin accumulation in sweetpotato. Taken together, this study
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provides insights into the genes and metabolites underlying anthocyanin enrichment
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in underground tuberous roots of sweetpotato.
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Keywords: Transcriptome; Metabolome; Sweetpotato; Anthocyanin accumulation; Underground tuberous roots
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1. Introduction
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Sweetpotato (Ipomoea batatas L.; 2n = 6x = 90) is an important food crop worldwide
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(Bovell‐Benjamin, 2007). While most sweetpotato cultivars are white or yellow
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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
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benefits (Chalker‐Scott, 1999; Pojer et al., 2013). As such, purple-fleshed sweetpotato
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(PFSP) is becoming a popular food.
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Anthocyanin accumulation is regulated by the trade-off between biosynthesis and
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breakdown. The biosynthetic pathway has been widely studied in model plants,
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consisting of numerous enzymes that catalyze sequential reactions of anthocyanin
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synthesis in cytoplasm (Koes et al., 2005). The pathway begins with the synthesis of
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4-coumaroyl-CoA from phenylalaline catalyzed by phenylalanine ammonia lyase
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(PAL), cinnamate 4-hydroxylase (C4H), and 4-coumaryol CoA ligase (4CL).
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4-coumaroyl-CoA is first converted into naringenin chalcone by chalcone synthase
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(CHS) and then isomerized by chalcone flavanone isomerase (CHI) into naringenin,
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followed by conversion to dihydrokaempferol by flavanone 3-hydroxylase (F3H). In
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most plants, dihydrokaempferol can be further hydroxylated by flavonoid
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3′-hydroxylase (F3′H) or flavonoid 3′, 5′-hydroxylase (F3′5′H) into dihydroquercetin
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or dihydromyricetin, respectively. Dihydrokaempferol, dihydroquercetin, and
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dihydromyricetin form colored anthocyanidins (pelargonidin, cyanidin, and
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delphinidin, respectively) by dihydroflavonol 4-reductase (DFR) and anthocyanidin
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synthase (ANS, also known as leucoanthocyadinin dioxygenase or LDOX). The core
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anthocyanidins found in plants are pelargonidin, cyanidin, delphinidin, peonidin,
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petunidin, and malvidin, of which peonidin is 3’-methylated cyanidin, petunidin is
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3’-methylated delphinidin, and malvidin is 3’- and 5’-methylated delphinidin.
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Anthocyanidins are unstable and easily degraded, thus requiring glycosylation by
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UDP-glucose anthocyanidin 3-O-glycosyltransferase (UFGT) for stabilization.
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Anthocyanins refer to glycosylated forms of anthocyanidins. Subsequently,
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glutathione S-transferases (GST) proteins catalyze the conjugation of glutathione to
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anthocyanins. At the final step, the conjugated anthocyanins were pumped into
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tonoplast by Multidrug and Toxic Compound Extrusion (MATE) transporters, where
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they were accumulated and stored (Koes et al., 2005).Natural anthocyanins can carry
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a wide variety of side chain decorations, resulting in various functionalities, including
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pigmentations, interactions with pathogenic and symbiotic microbes, and their health
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promoting effects (Croft, 1998).
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Transcription of the genes encoding the enzymes in the anthocyanin pathway is
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mainly regulated by three families of transcription factors (TFs), including MYB,
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basic helix-loop-helix (bHLH) and WD40. These TFs form MYB-bHLH-WD40
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(MBW) complexes, in which MYB TFs are primarily responsible for activation or
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repression of the conserved MBW complexes by binding with the promoter regions of
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the enzyme genes (Jaakola, 2013). Transcriptome sequencing identified numerous
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MYB TFs associated with anthocyanin biosynthesis and their mode of action is
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beginning to be revealed (Lotkowska et al., 2015; Hu et al., 2016; Lai et al., 2016;
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Wang et al., 2018). For example, R2R3-MYB forms a complex with JAF13 (bHLH)
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and WD40 to activate the transcription of AN1, a bHLH transcription factor. Then, the
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R2R3-MYB activator interacts with AN1 and WD40 to activate anthocyanin
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biosynthesis. In contrast, the MYB repressor negatively regulates anthocyanin
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biosynthesis by competitive binding to the JAF13 and AN1, leading to reduced
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formation of MBW activation complexes (Albert et al., 2014; D'Amelia et al., 2014).
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In sweetpotato, IbMYB1 is expressed predominantly in the purple-fleshed storage
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roots and plays an important role in anthocyanin biosynthesis. Ectopic overexpression
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of IbMYB1 in Arabidopsis, tobacco and sweetpotato upregulated the expression of the
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anthocyanin
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accumulation (Mano et al., 2007; Kim et al., 2010; Kim et al., 2020; Park et al.,
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2015).
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Additional regulatory factors have also been identified, such as CONSTITUTIVELY
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PHOTOMORPHOGENIC1 (COP1), JASMONATE ZIM DOMAIN (JAZ) proteins,
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SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) proteins, and the NAC
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(NAM, ATAF1,2 and CUC2) proteins (Gou et al., 2011; Qi et al., 2011; Maier et al.,
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2013; Zhou et al., 2015). In sweetpotato, the accumulation of anthocyanins appeared
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to be also regulated by MADS-box transcriptional factors because the majority of the
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sweetpotato calli became pigmented after transformation with the IbMADS10 gene
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(Lalusin et al., 2006). Recently, anthocyanin biosynthesis was also found to be
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influenced by auxin/indole acetic acids (Aux/IAA) and their cognate auxin response
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factors (ARFs) (Qi et al., 2011; Wang et al., 2018).
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Although anthocyanin metabolism has been well studied in aboveground plant organs
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(e.g., flowers, fruits and leaves), the mechanisms underlying anthocyanin
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accumulation in underground tuberous roots of sweetpotato are less understood.
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Despite the identification of a large number of differentially expressed genes, their
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role in the regulation of anthocyanin biosynthesis and accumulation remains obscure.
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Integrative analysis of the differentially accumulated metabolites (DAMs) and
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differentially expressed genes (DEGs) has proved to be a powerful tool to correlate
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phenotypes and genes (Zhang et al., 2020; Zhou et al., 2020). To gain a better
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understanding of the molecular and metabolic mechanisms of anthocyanin
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pigmentation in sweetpotato, we carried out comparative analysis of the transcriptome
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and anthocyanin-targeted metabolome data derived from the tuberous roots of a PFSP
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cultivar and a WFSP cultivar. This analysis revealed genes and key metabolites that
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contribute to anthocyanin pigmentation in underground tuberous roots of sweetpotato.
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2. Materials and methods
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2.1. Plant materials
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The white-fleshed sweetpotato cultivar Xushu-18 (hereafter referred to as XS-18 or
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WFSP) and the purple-fleshed sweetpotato cultivar Xuzishu-3 (hereafter referred to as
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XZS-3 or PFSP) were used for anthocyanin-targeted metabolome and transcriptome
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analysis. Field experiments were performed at the Shanxi Agricultural University
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campus (Taigu, Shanxi, China). Three months after planting, tuberous roots with
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similar shape and size were sampled. After gentle washing, they were cut into small
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pieces and immediately frozen in liquid nitrogen and stored in a -80℃ ultra-low
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freezer. Three tuberous roots from different plants were pooled together to form a
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single biological replicate. For each cultivar, three biological replicates were used for
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experimental analysis.
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2.2 Spectrophotometric measurement of total anthocyanin content
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The frozen tuberous roots were ground into a fine powder and 1.0 g powder was
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incubated in 50 mL HCl/methanol (1% v/v) at 4℃. After dark incubation for 24 h, the
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mixtures were first centrifuged at 12,000 rpm for 15 min, and then the absorbance of
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aqueous extracts was determined by a UV-2450 spectrophotometer at a wavelength of
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530nm and 657nm (Thermo Fisher, Vantaa, Finland). The total anthocyanin content
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(QAnthocyanins) was calculated as (A530 - 0.25×A657) / g, where A530 and A657 are the
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absorption values at the indicated wavelengths and g is the weight of the material used
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(Mehrtens et al., 2005; Jia et al., 2015).
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2.3 Anthocyanin-targeted metabolome analysis
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The experiment was conducted at MetWare Biotechnology (Wuhan, China) following
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the protocols described by Yuan et al. (2018). Prior to data analysis, the data reliability
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was subjected to quality control (QC) assessment. Statistical analysis of the data
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matrices containing the metabolite measurement values was performed with Analyst
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software (version 1.6.1). Partial least squares-discriminant analysis (PLS-DA) was
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performed to identify differentially accumulated metabolites (DAMs) between
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samples. DAMs were defined by the parameter known as variable importance in
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projection (VIP); metabolites with VIP ≥ 1 and fold change (FC) ≥ 2 or ≤ 0.5 between
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samples were considered as differential metabolites.
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2.4 RNA sequencing, expression data, GO and KEGG analysis
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RNA sequencing was conducted by Novo Bioinformatics (Beijing, China). The raw
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sequence data were deposited at NCBI with the accession number SRP268967.
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Mapped reads for each gene were counted by HTSeq (version 0.6.1). FPKM
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(fragments per kilobase of transcript per million mapped reads) values were used to
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identify differentially expressed genes (DEGs). Transcripts with a |log2 (FC)| > 1 and
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P-value 0.9), and then visualized using Cytoscape
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(version 3.3.0).
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3. Results
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3.1 Purple sweetpotato traits and targeted metabolome determination
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The tuberous roots of XZS-3 display dark purple flesh while those of XS-18 are
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white-fleshed (Fig. 1a). Consistent with this phenotypic difference, a higher content of
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anthocyanin was detected in the tuberous roots of XZS-3 (Fig. 1b). In order to gain
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insights into the differences in anthocyanin biosynthesis and accumulation, the two
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cultivars were subjected to anthocyanin-targeted metabolome analysis. Metabolite
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annotations based on a variety of metabolite information databases identified nine
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anthocyanin-related metabolites, including peonidin O-hexoside, rosinidin O-hexoside,
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cyanidin 3-O-glucoside, peonidin, peonidin O-malonylhexoside, delphinidin, cyanidin
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3-O-rutinoside, petunidin 3-O-glucoside, and cyanidin (Table S2, Fig. 1c). Cluster and
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differential analysis singled out six differentially accumulated metabolites (DAMs)
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with log (FC) > 1 and p < 0.05 (Fig. 1c). In particular, rosinidin O-hexoside,
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delphinidin, and petunidin-O-glucoside were widely present in XZS-3 (PFSP) but
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absent in XS-18 (WFSP), while the contents of peonidin O-malonylhexoside and
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cyanidin were much higher in PFSP than in WFSP (Fig. 1c, Table S3).
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Fig. 1. Analysis of phenotype, anthocyanin content and metabolites of XS-18 and
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XZS-3. (a) Overview of tuberous roots of purple-fleshed XZS-3 and white-fleshed
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XS-18 used for anthocyanin quantification, anthocyanin-targeted metabolome and
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transcriptome. (b) Total anthocyanin content in XS-18 and XZS-3. Each value was
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indicated as mean values ±SD. (c) Clustering heatmap of anthocyanin metabolites.
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The abscissa represented the samples. The ordinate represented different metabolite
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species.
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3.2 Characterization of the PFSP and WFSP transcriptomes
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We obtained the transcriptomes of XS-18 (WFSP) and XZS-3 (PFSP) cultivars by
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RNA sequencing. A total of 181.3 million clean reads from XS-18 and XZS-3 can be
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aligned with the sweetpotato reference genome (Table S4), of which 133.4 million
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(73.4%) were mapped to unique genomic locations (Table S4). This experiment
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generated 7,361 novel transcripts, 4,313 of which were annotated as protein-coding
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genes (Table S5). These annotations enriched the genomic information for
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sweetpotato. Overall, a total of 44,633 and 44,025 expressed genes (FPKM > 1.0)
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were identified in WFSP and PFSP (Table S6), respectively. Veen diagram showed
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that 40,132 genes were expressed in both WFSP and PFSP libraries, A total of 4,501
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transcripts expressed uniquely in XS-18, and 3,893 transcripts only expressed in
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cultivar XZS-3 (Fig. S1; Table S7).
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3.3 Identification of DEGs between WFSP and PFSP
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We performed comparative analysis of the PFSP (XZS-3) and WFSP (XS-18)
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transcriptomes to identify DEGs that are potentially associated with phenotypic
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differences between the two cultivars, especially those involved in anthocyanin
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pathways. This analysis revealed 11,355 transcripts that were differentially expressed
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between WFSP and PFSP, of which 5,980 were up-regulated and 5,374 were
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down-regulated in PFSP (Table S8, Fig. 2a and Fig. 2b).
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Fig. 2. Expression profiling and GO analysis of DEGs between cultivars of XS-18
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and XZS-3. (a) Volcanic map of DEGs, (b) A general Heatmap overview of the
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expression pattern of DEGs between cultivars of XZS-3 and XS-18. (c) GO terms of
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up-regulated transcripts in XZS-3. (d) GO terms of down-regulated transcripts in
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XZS-3. The criteria for screening differential genes were log2 (FC) > 1, p < 0.05.
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3.4 GO enrichment and KEGG pathway analysis of DEGs
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The DEGs between the WFSP and PFSP cultivars were subjected to Gene Ontology
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(GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These
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analyses identified 358 genes that are implicated in multiple pathways involved in
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biosynthesis of secondary metabolites (Table S8). The enriched genes were grouped
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into three main GO categories: biological process, molecular function, and cellular
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component. The genes with increased expression in PFSP were greatly enriched in
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biological process category (Fig. 2c), while the genes with reduced expression in
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PFSP were greatly enriched in molecular function category (Fig. 2d).
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Among the genes with enhanced expression in PFSP, the GO terms enriched in the
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biological process category included cellular amide and peptide metabolic process,
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peptide biosynthetic process, and protein translation. In the molecular function
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category, structural constituent of ribosome and structural molecule activity were
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significantly enriched (Fig. 2c). The up-regulated genes are significantly enriched in
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translation-related functions, suggesting that translation of regulatory and enzyme
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genes may be enhanced to promote anthocyanin biosynthesis and accumulation.
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Among the genes down-regulated in PFSP, RNA modification is enriched in
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biological process, and ADP binding and “serine-type endopeptidase inhibitor activity”
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are enriched in molecular function, and no obvious enrichment was detected in the
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cellular component process (Fig. 2d). These genes may play a negative role in
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anthocyanin biosynthesis and accumulation. The top 20-ranked KEGG pathways were
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presented in Fig. S2. The DEGs were mainly enriched in biosynthesis of ubiquinone
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and other terpenoid−quinone, biosynthesis of secondary metabolites, tyrosine
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metabolism, glycolysis/gluconeogenesis and alanine, aspartate and glutamate
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metabolism (Fig. S2).
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3.5 Expression profiling of the enzyme and transporter genes related to
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anthocyanin biosynthesis and accumulation
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The transcription levels of the anthocyanin pathway-related enzyme and transporter
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genes were compared between the PFSP (XZS-3) and WFSP (XS-18) cultivars (Fig. 3,
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Table S9). This comparison revealed a higher level of expression for most of the
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homologous enzyme genes in XZS-3, including two of the three PAL genes
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(Tai6.52988 and Tai6.29387), five of the six 4CL genes (Tai6.8930, Tai6.45910,
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Tai6.37076, Tai6.6371, and Novel06268), six of the seven CHS genes (Tai6.29634,
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Tai6.46186, Tai6.53503, Tai6.45381, Tai6.1734, and Tai6.1732), three of the four
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DFR genes (Tai6.3022, Tai6.16429, and Tai6.3019), all three LDOX genes
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(Tai6.40394, Tai6.53285, and Tai6.42091), and all five UFGT genes (Tai6.16002,
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Tai6.17387, Tai6.34855, Tai6.47630, and Tai6.47631). One CHI (Tai6.7312) and one
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F3H (Tai6.9545) genes were identified in the sweetpotato genome, both of which
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showed a higher level of expression in XZS-3. We also identified two
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O-methyltransferase (OMT) genes, and one was up-regulated while the other one was
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down-regulated in XZS-3. Among the 23 glutathione S-transferase (GST) genes, 13
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were up-regulated while the other ten were down-regulated in XZS-3. In addition, five
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multidrug and toxic compound extrusion (MATE) genes were identified and all
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showed a lower expression level in XZS-3.
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Fig. 3. Expression profiling of the representative enzyme and transporter genes
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involved in anthocyanin pathways between XS-18 and XZS-3. In the middle of the
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figure was the schematic of anthocyanin pathway. The outside of the figure was
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heatmap diagrams showing the expression differences of the main genes between
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XS-18 and XZS-3. Expressions of the genes validated by qRT-PCR were highlighted
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in bold font. Phenylalanine ammonia lyase (PAL), 4-coumaroyl, CoA ligase (4CL),
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chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), chalcone isomerase (CHI),
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dihydroflavonol-4-reductase (DFR), leucoanthocyanidin dioxygenase (LDOX),
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O-methyltransferase
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(UFGT), glutathione S-transferase (GST), multidrug and toxic compound extrusion
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(MATE).
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(OMT),
UDP-glucose
anthocyanin 3-o-glycosyltransferase
3.6 Expression profiling of TFs involved in anthocyanin pathways
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TFs play important roles in regulation of anthocyanin biosynthesis by modulating the
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expression of enzyme genes and other related genes. RNA-seq analysis identified a
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total of 87 differentially expressed TF genes, including 21, 19, 16, 15, and 6 members
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from the bHLH, MYB, C3H, ZF, and WD subfamilies, respectively (Fig. 4a, Table
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S10), consistent with that the biosynthesis of anthocyanins is associated with the
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formation of the MYB-bHLH-WD40 (MBW) activation/repression complexes. A
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similar number of bHLH, MYB, and C3H genes were up- or down-regulated in PFSP.
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Of the six WD genes, four were up-regulated while the other two were
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down-regulated in XZS-3. Of the 15 ZF genes, 11 showed significant up-regulation in
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XZS-3. In addition, 4, 3, and 2 members were identified from the TCP, bZIP, and
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NAC subfamilies, respectively (Fig. 4A, Table S10). One of the four TCP genes and
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two of the three bZIP genes showed a higher level of expression in XZS-3. Both of
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NAC genes showed a lower level of expression in XZS-3. One far-red impaired
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response1 (FAR1) gene was identified and up-regulated in XZS-3.
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Fig. 4. Heatmap diagrams of TFs involved in anthocyanin and Aux/IAA-ARF
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Pathways. (a) Profiling of differentially expressed anthocyanin-related TFs pathway,
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(b) Profiling of differentially expressed auxin-related TFs. The nine different colors of
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the first column corresponds to the nine different gene subfamilies. The other columns
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in the heatmap represented the samples. The color scale bar on the right side
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represented the average FPKM value of log-transformed. basic helix-loop-helix
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(bHLH), MYB proteins (MYB), WD40 repeat proteins (WD), cys3His zinc finger
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(C3H), zinc finger proteins (ZF protein), TCP proteins (TCP), basic region/leucine
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zipper (bZIP), NAC transcription factor (NAC), far-red impaired response1 (FAR1).
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3.7 Expression profiling of TFs associated with Aux/IAA-ARF Signaling Pathways
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Auxin is an important plant hormone, but the relationship between auxin and
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anthocyanin biosynthesis is unclear in sweetpotato. In this study, we identified 26
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differentially expressed Aux/IAA and ARF TF genes associated with the auxin signal
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pathway (Fig. 4b, Table S11), of which 21 showed elevated expression in the PFSP
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cultivar, including Auxin-responsive proteins IAA13, IAA14, IAA16, IAA27, ARF4,
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ARF6, ARF9, ARF12 and AUX22D. However, the other five appeared to be
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down-regulated, including IAA26, ARF5, AUL1 and two AUX1.
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3.8 Quantitative RT-PCR of DEGs
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A total of 22 representative DEGs between WFSP and PFSP cultivars were selected
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for qRT-PCR analysis. In general, the expression patterns of the 22 DEGs revealed by
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qRT-PCR matched those derived from RNA-seq (Fig. 5). Notably, the expression of
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the eleven enzyme genes were about 270-25,000 times higher in XZS-3 than in
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XS-18.
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Fig. 5. Comparison of expression profiling of 22 representative genes profiled by
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qRT-PCR
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anthocyanin-related TFs and four auxin-related TFs. Columns above and below y-axis
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0 represented expression determined by qRT-PCR and by RNA-seq in FPKM values,
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respectively. IbActin was used as reference control. Relative gene expressions were
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determined by the comparative 2-ΔΔCt method Bars represented the average values ±
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SE of three separate biological replicates in triplicate. For statistical analysis,
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two-tailed t-test of Dunnett was applied. The differences were defined to be
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statistically significant when p ≤ 0.05 (indicate as *) and p ≤ 0.01 (indicate as **).
and
transcriptome,
including
eleven
structure
genes,
seven
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3.9 SNP identification
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We assembled all the transcripts and found that 7,361 transcripts did not exist in the
356
standard annotation library (Table S13). We used Tophat2 to map the reads to the
357
reference genome (a WFSP genotype) and identified high-confidence SNPs based on
358
multiple criteria including read depth and allele frequency. Among these SNPs, we
359
focused on the sequence variability of enzyme genes related to anthocyanin
360
biosynthesis (Table S12). When compared with the reference genome, the UFGT,
361
A3G, DFR, and F3H alleles from PFSP are more polymorphic than the alleles from
362
WFSP. As shown in Fig. S3, the number of SNPs in PFSP is nearly twice that in
363
WFSP. In contrast, the numbers of SNPs in LDOX, CHS, F3'M, 3GGT, F3′,5′H, and
364
ANR were similar and did not show significant difference between PFSP and WFSP.
365
Therefore, there may be many functional SNPs in UGFT, A3G, DFR and F3H genes
366
that affect the expression or activity of these genes, resulting in natural variation in
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anthocyanin biosynthesis.
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3.10 Correlation analysis between transcriptome and metabolites
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To further characterize the metabolic pathways for anthocyanin synthesis, we
371
constructed gene-metabolite networks by integrative analysis of the metabolome and
372
transcriptome data. For this purpose, six DAMs (peonidin O-hexoside, rosinidin
373
O-hexoside, peonidin O-malonylhexoside, delphinidin, petunidin 3-O-glucoside, and
374
cyanidin) and the top 1000 DEGs were used for association analysis (Fig. 6, Table
375
S13). Each DAM was significantly correlated with the DEGs, and we selected the
376
top100 web links for further analysis. Among these genes, GST (Tai6.17033,
377
Tai6.19248, Tai6.25547, and Tai6.24771), F3H (Tai6.9545), starch synthase 2 (SS2,
378
Tai6.26337), quinone oxidoreductase (QOR, Tai6.41481), wall-associated receptor
379
kinase 3 (WAK3, Tai6.36254), WRKY transcription factor 20 (WRKY20 and
380
Tai6.3520), serine carboxypeptidase-like 41 (SCPL41 and Tai6.35008), LDOX/ANT
381
(Tai6.42091), bHLH (Tai6.36440 and Tai6.28734), CHI (Tai6.15773), CHS
382
(Tai6.29634), and Zerumbone synthase (ZSD1, Tai6.5425) were found to be highly
383
correlated with the metabolites.
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Fig. 6. Correlation network diagram of DAMs and DEGs. The larger the point, the
387
stronger the correlation. peonidin O-hexoside (POH), rosinidin O-hexoside (ROH),
388
peonidin O-malonylhexoside (POM), petunidin 3-O-glucoside (P3G).
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4. Discussion
391
Sweetpotato, a member of the Convolvulaceae family, has become one of the most
392
popular foods (Kwak, 2019). In PFSP, the purple flesh accumulates abundant
393
anthocyanins
394
understanding the anthocyanin biosynthesis in sweetpotato will facilitate breeding or
395
engineering plants to boost the anthocyanin production (Kim et al., 2020). In this
396
study, the metabolome and transcriptome of PFSP and WFSP were characterized, in
397
order to gain insights into the genes and metabolites that are associated with
398
anthocyanin biosynthesis, accumulation, and regulation.
that
are
important
health-promoting
compounds.
Therefore,
399 400
Analysis of the differentially accumulated metabolites between PFSP and WFSP
401
revealed
402
O-malonylhexoside, delphinidin, and cyanidin were specifically present or more
403
abundant in PFSP, indicating that anthocyanin metabolism is more active in PFSP
that
peonidin
O-hexoside,
rosinidin
O-hexoside,
peonidin
404
than in WFSP. In particular, delphinidin, peonidin and rosinidin, which contribute to
405
red or blue colors in plant organs, were highly present in PFSP but absent in WFSP
406
(Fig. 1, Table S2 and S3), suggesting that they are the key anthocyanin derivatives
407
conferring the purple pigmentation in PFSP.
408
The biosynthesis of anthocyanin involves numerous enzyme genes. Many of these
410
enzyme genes were differentially expressed between the PFSP and WFSP genotypes.
411
In particular, most of the CHS, CHI, F3H, DFR, and LDOX homologs showed a
412
higher level of expression in PFSP than in WFSP, indicating that these genes play key
413
roles in anthocyanin biosynthesis and accumulation in PFSP. In addition, five UFGT
414
genes, which are required for glycosylation to stabilize anthocyanins, also showed a
415
higher level of expression in PFSP when compared with WFSP, consistent with the
416
important roles that UFGT genes play in the anthocyanin pathway in other plants
417
(Kobayashi et al., 2004; Wang et al., 2013; Zhang et al., 2020; Zhou et al., 2020).
418
Glutathione S-transferases (GSTs) act as non-enzymatic carrier proteins to escort
419
conjugated anthocyanins to the MATE transporters at tonoplast (Edwards et al., 2000)
420
(Alfenito et al., 1998). Interestingly, among 23 differentially expressed GST genes
421
identified in this study, three (Tai6.30213, Tai6.17033, and Tai6.29612) were
422
significantly up-regulated (>500 times) in PFSP, suggesting that the three GSTs may
423
play important roles in anthocyanin transport in sweetpotato.
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The expression of the enzyme genes in anthocyanin pathways is modulated by TFs.
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This is achieved by physical interactions between R2R3-MYB, bHLH, and WD TFs,
427
forming ternary complexes (MBWs) responsible for the coordination of anthocyanin
428
biosynthesis (Jaakola, 2013). Consistent with this, more than half (46) of the 87
429
differentially expressed TFs belong to the R2R3-MYB, bHLH, and WD subfamilies,
430
highlighting their important roles in regulation of the anthocyanin pathway.
431
addition, we found two NAC100 genes that were significantly down-regulated in PFSP.
432
NAC TFs have a variety of biological functions. In peach, ppNAC1 activates the
433
transcription of ppMYB10.1 to promote anthocyanin pigmentation (Zhou et al., 2015).
434
The low expression of NAC100 genes in PFSP than in WFSP might suggest negative
435
roles of these genes in the anthocyanin biosynthesis or accumulation; similar
436
expression patterns were also observed for the NAC1 and NAC2 in purple-fleshed
437
sweetpotato (Chen et al., 2016).
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In
438 439
Phytohormones are also an important factor affecting accumulation of anthocyanins in
440
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
442
Komamine, 1986). High concentrations of auxin significantly inhibited anthocyanin
443
biosynthesis in cultured callus of red-fleshed apple (M. sieversii f.niedzwetzkyana) (Ji
444
et al., 2014). In the apple fruit skin of ‘Red Delicious’ and its four generation bud
445
sport mutants, IAA and ABA had a positive regulatory effect on the anthocyanin
446
formation, while GA had an inhibitory effect (Li et al., 2018). Wang et al. (2018)
447
reported that the increasing NAA concentrations increased the expression of
448
Aux/IAA-ARF and decreased anthocyanin accumulation in apple. Interestingly, we
449
observed that 21 of the 26 auxin-related genes in the Aux/IAA-ARF family exhibited
450
significant up-regulation in PFSP (Fig. 4b, Table S11), suggesting that these
451
Aux/IAA-ARF signaling factors may modulate the expression of transcripts involved
452
in anthocyanin pathways. Specifically, auxin may trigger the expression of the
453
homologous genes encoding IAA13, IAA14, IAA16, IAA27, ARF4, and ARF6, which
454
act as activators in anthocyanin biosynthesis in PFSP. In contrast, IAA26, ARF5,
455
AUL1, AUX1, and LAX2 were down-regulated in PFSP and these genes may function
456
as repressors in anthocyanin biosynthesis. Aux/IAA-ARF TFs exhibit dynamic
457
functions in plants and have a central role in the hub of transcriptional networks. The
458
altered expressions of Aux/IAA-ARF TFs between WFSP and PFSP suggested a
459
novel metabolic function for Aux/IAA-ARF proteins.
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In summary, our study revealed anthocyanin metabolites that contribute to the purple
462
pigmentation in purple-fleshed sweetpotato. We also showed that the altered
463
expression of the anthocyanin pathway genes and regulatory transcription factors
464
account for the difference in anthocyanin accumulation in PFSP and WFSP.
465
Furthermore, we identified DEGs, including TFs and enzyme genes that were not
466
previously implicated in anthocyanin biosynthesis. Functional study should be
467
performed in the future to validate their role in regulation of anthocyanin biosynthesis
468
in sweetpotato. Knowledge gained from this study will facilitate breeding and
469
engineering sweetpotato plants for enhanced anthocyanin accumulation.
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Supplementary Materials:
473
Table S1 Primer sequences used for qRT-PCR analysis
474
Table S2 Determination of anthocyanin-targeted metabolites in sweetpotato
475
Table S3 Differentially accumulated metabolites in XS-18 and XZS-3
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Table S4 The transcriptome profiling of XS-18 and XZS-3
477
Table S5 Annotated novel transcripts
Table S6 Expressed genes within XS-18 and XZS-3
479
Table S7 Co-expressed and specifically expressed genes between XS-18 and XZS-3
480
Table S8 DEGs between XS-18 and XZS-3
481
Table S9 The transcription levels of anthocyanin pathway-related structural genes
482
Table S10 Expression profiling of TFs associated with anthocyanin biosynthesis
483
Table S11 Expression profiling of auxin-related TF genes
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Table S12 SNP numbers of structural genes related to anthocyanin biosynthesis
485
Table S13 Correlation analysis of the DAMs and DEGs
486
Fig. S1. Venn diagram of co-expressed and specifically expressed genes between
487
XS-18 and XZS-3.
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Fig. S2. Functional Enrichment of DEG by KEGG analysis.
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Fig. S3. The differences in the number of SNPs in the structural genes of anthocyanin
490
synthesis between PFSF and WFSF.
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Author Contributions: Xiaoyun Jia, Hongyan Zhu, Runzhi Li and Liheng He
493
conceived the original research plans. Xiaoyun Jia and Liheng He designed the
494
experiments. Liheng He, Xiayu Liu, Shifang Liu, Jie Zhang and Yan Sun collected the
495
materials; Liheng He, Xiayu Liu, Shifang Liu and Yi Zhang conducted the
496
experiments and analyzed the data. Liheng He and Xiaoyun Jia drafted the manuscript;
497
Ruimin Tang, Wenbin Wang, Hongli Cui, Xiaoyun Jia, Runzhi Li and Hongyan Zhu
498
modified the manuscript. All authors read and approved the manuscript.
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Funding: This study was funded by National Key Research and Development
501
Program of China (2018YFD1000700, 2018YFD1000705), Key Research and
502
Development Project of Shanxi Province (201803D221008-6), Natural Science
503
Foundation of Shanxi Province (201801D121238), Science and Technology
504
Innovation project of Shanxi Agricultural University (2018yz001), Shanxi Provincial
505
Leading Talents in Emerging Industries Project, Special Plan of Scientific Research
506
for Shanxi Agriculture Valley Construction of China (SXNGJSKYZX201701-03).
507
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Highlights
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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.
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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
S0981-9428(20)30470-8
DOI:
https://doi.org/10.1016/j.plaphy.2020.09.021
Reference:
PLAPHY 6396
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
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Development Project of Shanxi Province (201803D221008-6), Natural Science
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Foundation of Shanxi Province (201801D121238), Science and Technology Innovation project of Shanxi Agricultural University (2018yz001), Shanxi Provincial
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Leading Talents in Emerging Industries Project, Special Plan of Scientific Research
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for Shanxi Agriculture Valley Construction of China (SXNGJSKYZX201701-03).
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Transcriptomic and targeted metabolomic analysis identifies genes and
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metabolites involved in anthocyanin accumulation in tuberous roots of
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sweetpotato (Ipomoea batatas L.)
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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.
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Abstract: Purple-fleshed sweetpotato (PFSP) accumulates high amounts of
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anthocyanins that are beneficial to human health. Although biosynthesis of such
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secondary metabolites has been well studied in aboveground organs of many plants,
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the mechanisms underlying anthocyanin accumulation in underground tuberous roots
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of sweetpotato are less understood. To identify genes and metabolites involved in
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anthocyanin accumulation in sweetpotato, we performed comparative transcriptomic
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and metabolomic analysis of purple-fleshed sweetpotato (PFSP) and white-fleshed
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sweetpotato (WFSP). Anthocyanin-targeted metabolome analysis revealed that
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delphinidin, petunidin, and rosinidin were the key metabolites conferring purple
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pigmentation in PFSP as they were highly enriched in PFSP but absent in WFSP.
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Transcriptomic analysis identified 358 genes that were potentially implicated in
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multiple pathways for the biosynthesis of anthocyanins. Although most of the genes
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were previously known for their roles in anthocyanin biosynthesis, we identified 26
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differentially expressed genes that are involved in Aux/IAA-ARF signaling.
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Gene-metabolite correlation analysis also revealed novel genes that are potentially
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involved in the anthocyanin accumulation in sweetpotato. Taken together, this study
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provides insights into the genes and metabolites underlying anthocyanin enrichment
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in underground tuberous roots of sweetpotato.
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Keywords: Transcriptome; Metabolome; Sweetpotato; Anthocyanin accumulation; Underground tuberous roots
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1. Introduction
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Sweetpotato (Ipomoea batatas L.; 2n = 6x = 90) is an important food crop worldwide
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(Bovell‐Benjamin, 2007). While most sweetpotato cultivars are white or yellow
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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
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benefits (Chalker‐Scott, 1999; Pojer et al., 2013). As such, purple-fleshed sweetpotato
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(PFSP) is becoming a popular food.
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Anthocyanin accumulation is regulated by the trade-off between biosynthesis and
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breakdown. The biosynthetic pathway has been widely studied in model plants,
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consisting of numerous enzymes that catalyze sequential reactions of anthocyanin
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synthesis in cytoplasm (Koes et al., 2005). The pathway begins with the synthesis of
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4-coumaroyl-CoA from phenylalaline catalyzed by phenylalanine ammonia lyase
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(PAL), cinnamate 4-hydroxylase (C4H), and 4-coumaryol CoA ligase (4CL).
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4-coumaroyl-CoA is first converted into naringenin chalcone by chalcone synthase
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(CHS) and then isomerized by chalcone flavanone isomerase (CHI) into naringenin,
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followed by conversion to dihydrokaempferol by flavanone 3-hydroxylase (F3H). In
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most plants, dihydrokaempferol can be further hydroxylated by flavonoid
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3′-hydroxylase (F3′H) or flavonoid 3′, 5′-hydroxylase (F3′5′H) into dihydroquercetin
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or dihydromyricetin, respectively. Dihydrokaempferol, dihydroquercetin, and
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dihydromyricetin form colored anthocyanidins (pelargonidin, cyanidin, and
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delphinidin, respectively) by dihydroflavonol 4-reductase (DFR) and anthocyanidin
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synthase (ANS, also known as leucoanthocyadinin dioxygenase or LDOX). The core
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anthocyanidins found in plants are pelargonidin, cyanidin, delphinidin, peonidin,
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petunidin, and malvidin, of which peonidin is 3’-methylated cyanidin, petunidin is
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3’-methylated delphinidin, and malvidin is 3’- and 5’-methylated delphinidin.
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Anthocyanidins are unstable and easily degraded, thus requiring glycosylation by
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UDP-glucose anthocyanidin 3-O-glycosyltransferase (UFGT) for stabilization.
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Anthocyanins refer to glycosylated forms of anthocyanidins. Subsequently,
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glutathione S-transferases (GST) proteins catalyze the conjugation of glutathione to
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anthocyanins. At the final step, the conjugated anthocyanins were pumped into
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tonoplast by Multidrug and Toxic Compound Extrusion (MATE) transporters, where
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they were accumulated and stored (Koes et al., 2005).Natural anthocyanins can carry
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a wide variety of side chain decorations, resulting in various functionalities, including
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pigmentations, interactions with pathogenic and symbiotic microbes, and their health
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promoting effects (Croft, 1998).
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Transcription of the genes encoding the enzymes in the anthocyanin pathway is
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mainly regulated by three families of transcription factors (TFs), including MYB,
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basic helix-loop-helix (bHLH) and WD40. These TFs form MYB-bHLH-WD40
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(MBW) complexes, in which MYB TFs are primarily responsible for activation or
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repression of the conserved MBW complexes by binding with the promoter regions of
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the enzyme genes (Jaakola, 2013). Transcriptome sequencing identified numerous
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MYB TFs associated with anthocyanin biosynthesis and their mode of action is
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beginning to be revealed (Lotkowska et al., 2015; Hu et al., 2016; Lai et al., 2016;
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Wang et al., 2018). For example, R2R3-MYB forms a complex with JAF13 (bHLH)
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and WD40 to activate the transcription of AN1, a bHLH transcription factor. Then, the
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R2R3-MYB activator interacts with AN1 and WD40 to activate anthocyanin
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biosynthesis. In contrast, the MYB repressor negatively regulates anthocyanin
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biosynthesis by competitive binding to the JAF13 and AN1, leading to reduced
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formation of MBW activation complexes (Albert et al., 2014; D'Amelia et al., 2014).
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In sweetpotato, IbMYB1 is expressed predominantly in the purple-fleshed storage
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roots and plays an important role in anthocyanin biosynthesis. Ectopic overexpression
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of IbMYB1 in Arabidopsis, tobacco and sweetpotato upregulated the expression of the
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anthocyanin
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accumulation (Mano et al., 2007; Kim et al., 2010; Kim et al., 2020; Park et al.,
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2015).
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Additional regulatory factors have also been identified, such as CONSTITUTIVELY
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PHOTOMORPHOGENIC1 (COP1), JASMONATE ZIM DOMAIN (JAZ) proteins,
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SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) proteins, and the NAC
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(NAM, ATAF1,2 and CUC2) proteins (Gou et al., 2011; Qi et al., 2011; Maier et al.,
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2013; Zhou et al., 2015). In sweetpotato, the accumulation of anthocyanins appeared
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to be also regulated by MADS-box transcriptional factors because the majority of the
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sweetpotato calli became pigmented after transformation with the IbMADS10 gene
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(Lalusin et al., 2006). Recently, anthocyanin biosynthesis was also found to be
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influenced by auxin/indole acetic acids (Aux/IAA) and their cognate auxin response
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factors (ARFs) (Qi et al., 2011; Wang et al., 2018).
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Although anthocyanin metabolism has been well studied in aboveground plant organs
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(e.g., flowers, fruits and leaves), the mechanisms underlying anthocyanin
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accumulation in underground tuberous roots of sweetpotato are less understood.
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Despite the identification of a large number of differentially expressed genes, their
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role in the regulation of anthocyanin biosynthesis and accumulation remains obscure.
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Integrative analysis of the differentially accumulated metabolites (DAMs) and
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differentially expressed genes (DEGs) has proved to be a powerful tool to correlate
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phenotypes and genes (Zhang et al., 2020; Zhou et al., 2020). To gain a better
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understanding of the molecular and metabolic mechanisms of anthocyanin
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pigmentation in sweetpotato, we carried out comparative analysis of the transcriptome
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and anthocyanin-targeted metabolome data derived from the tuberous roots of a PFSP
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cultivar and a WFSP cultivar. This analysis revealed genes and key metabolites that
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contribute to anthocyanin pigmentation in underground tuberous roots of sweetpotato.
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2. Materials and methods
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2.1. Plant materials
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The white-fleshed sweetpotato cultivar Xushu-18 (hereafter referred to as XS-18 or
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WFSP) and the purple-fleshed sweetpotato cultivar Xuzishu-3 (hereafter referred to as
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XZS-3 or PFSP) were used for anthocyanin-targeted metabolome and transcriptome
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analysis. Field experiments were performed at the Shanxi Agricultural University
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campus (Taigu, Shanxi, China). Three months after planting, tuberous roots with
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similar shape and size were sampled. After gentle washing, they were cut into small
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pieces and immediately frozen in liquid nitrogen and stored in a -80℃ ultra-low
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freezer. Three tuberous roots from different plants were pooled together to form a
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single biological replicate. For each cultivar, three biological replicates were used for
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experimental analysis.
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2.2 Spectrophotometric measurement of total anthocyanin content
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The frozen tuberous roots were ground into a fine powder and 1.0 g powder was
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incubated in 50 mL HCl/methanol (1% v/v) at 4℃. After dark incubation for 24 h, the
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mixtures were first centrifuged at 12,000 rpm for 15 min, and then the absorbance of
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aqueous extracts was determined by a UV-2450 spectrophotometer at a wavelength of
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530nm and 657nm (Thermo Fisher, Vantaa, Finland). The total anthocyanin content
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(QAnthocyanins) was calculated as (A530 - 0.25×A657) / g, where A530 and A657 are the
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absorption values at the indicated wavelengths and g is the weight of the material used
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(Mehrtens et al., 2005; Jia et al., 2015).
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2.3 Anthocyanin-targeted metabolome analysis
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The experiment was conducted at MetWare Biotechnology (Wuhan, China) following
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the protocols described by Yuan et al. (2018). Prior to data analysis, the data reliability
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was subjected to quality control (QC) assessment. Statistical analysis of the data
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matrices containing the metabolite measurement values was performed with Analyst
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software (version 1.6.1). Partial least squares-discriminant analysis (PLS-DA) was
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performed to identify differentially accumulated metabolites (DAMs) between
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samples. DAMs were defined by the parameter known as variable importance in
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projection (VIP); metabolites with VIP ≥ 1 and fold change (FC) ≥ 2 or ≤ 0.5 between
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samples were considered as differential metabolites.
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2.4 RNA sequencing, expression data, GO and KEGG analysis
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RNA sequencing was conducted by Novo Bioinformatics (Beijing, China). The raw
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sequence data were deposited at NCBI with the accession number SRP268967.
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Mapped reads for each gene were counted by HTSeq (version 0.6.1). FPKM
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(fragments per kilobase of transcript per million mapped reads) values were used to
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identify differentially expressed genes (DEGs). Transcripts with a |log2 (FC)| > 1 and
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P-value 0.9), and then visualized using Cytoscape
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(version 3.3.0).
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3. Results
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3.1 Purple sweetpotato traits and targeted metabolome determination
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The tuberous roots of XZS-3 display dark purple flesh while those of XS-18 are
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white-fleshed (Fig. 1a). Consistent with this phenotypic difference, a higher content of
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anthocyanin was detected in the tuberous roots of XZS-3 (Fig. 1b). In order to gain
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insights into the differences in anthocyanin biosynthesis and accumulation, the two
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cultivars were subjected to anthocyanin-targeted metabolome analysis. Metabolite
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annotations based on a variety of metabolite information databases identified nine
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anthocyanin-related metabolites, including peonidin O-hexoside, rosinidin O-hexoside,
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cyanidin 3-O-glucoside, peonidin, peonidin O-malonylhexoside, delphinidin, cyanidin
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3-O-rutinoside, petunidin 3-O-glucoside, and cyanidin (Table S2, Fig. 1c). Cluster and
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differential analysis singled out six differentially accumulated metabolites (DAMs)
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with log (FC) > 1 and p < 0.05 (Fig. 1c). In particular, rosinidin O-hexoside,
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delphinidin, and petunidin-O-glucoside were widely present in XZS-3 (PFSP) but
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absent in XS-18 (WFSP), while the contents of peonidin O-malonylhexoside and
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cyanidin were much higher in PFSP than in WFSP (Fig. 1c, Table S3).
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Fig. 1. Analysis of phenotype, anthocyanin content and metabolites of XS-18 and
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XZS-3. (a) Overview of tuberous roots of purple-fleshed XZS-3 and white-fleshed
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XS-18 used for anthocyanin quantification, anthocyanin-targeted metabolome and
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transcriptome. (b) Total anthocyanin content in XS-18 and XZS-3. Each value was
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indicated as mean values ±SD. (c) Clustering heatmap of anthocyanin metabolites.
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The abscissa represented the samples. The ordinate represented different metabolite
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species.
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3.2 Characterization of the PFSP and WFSP transcriptomes
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We obtained the transcriptomes of XS-18 (WFSP) and XZS-3 (PFSP) cultivars by
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RNA sequencing. A total of 181.3 million clean reads from XS-18 and XZS-3 can be
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aligned with the sweetpotato reference genome (Table S4), of which 133.4 million
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(73.4%) were mapped to unique genomic locations (Table S4). This experiment
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generated 7,361 novel transcripts, 4,313 of which were annotated as protein-coding
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genes (Table S5). These annotations enriched the genomic information for
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sweetpotato. Overall, a total of 44,633 and 44,025 expressed genes (FPKM > 1.0)
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were identified in WFSP and PFSP (Table S6), respectively. Veen diagram showed
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that 40,132 genes were expressed in both WFSP and PFSP libraries, A total of 4,501
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transcripts expressed uniquely in XS-18, and 3,893 transcripts only expressed in
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cultivar XZS-3 (Fig. S1; Table S7).
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3.3 Identification of DEGs between WFSP and PFSP
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We performed comparative analysis of the PFSP (XZS-3) and WFSP (XS-18)
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transcriptomes to identify DEGs that are potentially associated with phenotypic
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differences between the two cultivars, especially those involved in anthocyanin
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pathways. This analysis revealed 11,355 transcripts that were differentially expressed
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between WFSP and PFSP, of which 5,980 were up-regulated and 5,374 were
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down-regulated in PFSP (Table S8, Fig. 2a and Fig. 2b).
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Fig. 2. Expression profiling and GO analysis of DEGs between cultivars of XS-18
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and XZS-3. (a) Volcanic map of DEGs, (b) A general Heatmap overview of the
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expression pattern of DEGs between cultivars of XZS-3 and XS-18. (c) GO terms of
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up-regulated transcripts in XZS-3. (d) GO terms of down-regulated transcripts in
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XZS-3. The criteria for screening differential genes were log2 (FC) > 1, p < 0.05.
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3.4 GO enrichment and KEGG pathway analysis of DEGs
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The DEGs between the WFSP and PFSP cultivars were subjected to Gene Ontology
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(GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. These
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analyses identified 358 genes that are implicated in multiple pathways involved in
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biosynthesis of secondary metabolites (Table S8). The enriched genes were grouped
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into three main GO categories: biological process, molecular function, and cellular
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component. The genes with increased expression in PFSP were greatly enriched in
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biological process category (Fig. 2c), while the genes with reduced expression in
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PFSP were greatly enriched in molecular function category (Fig. 2d).
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Among the genes with enhanced expression in PFSP, the GO terms enriched in the
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biological process category included cellular amide and peptide metabolic process,
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peptide biosynthetic process, and protein translation. In the molecular function
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category, structural constituent of ribosome and structural molecule activity were
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significantly enriched (Fig. 2c). The up-regulated genes are significantly enriched in
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translation-related functions, suggesting that translation of regulatory and enzyme
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genes may be enhanced to promote anthocyanin biosynthesis and accumulation.
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Among the genes down-regulated in PFSP, RNA modification is enriched in
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biological process, and ADP binding and “serine-type endopeptidase inhibitor activity”
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are enriched in molecular function, and no obvious enrichment was detected in the
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cellular component process (Fig. 2d). These genes may play a negative role in
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anthocyanin biosynthesis and accumulation. The top 20-ranked KEGG pathways were
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presented in Fig. S2. The DEGs were mainly enriched in biosynthesis of ubiquinone
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and other terpenoid−quinone, biosynthesis of secondary metabolites, tyrosine
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metabolism, glycolysis/gluconeogenesis and alanine, aspartate and glutamate
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metabolism (Fig. S2).
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3.5 Expression profiling of the enzyme and transporter genes related to
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anthocyanin biosynthesis and accumulation
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The transcription levels of the anthocyanin pathway-related enzyme and transporter
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genes were compared between the PFSP (XZS-3) and WFSP (XS-18) cultivars (Fig. 3,
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Table S9). This comparison revealed a higher level of expression for most of the
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homologous enzyme genes in XZS-3, including two of the three PAL genes
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(Tai6.52988 and Tai6.29387), five of the six 4CL genes (Tai6.8930, Tai6.45910,
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Tai6.37076, Tai6.6371, and Novel06268), six of the seven CHS genes (Tai6.29634,
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Tai6.46186, Tai6.53503, Tai6.45381, Tai6.1734, and Tai6.1732), three of the four
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DFR genes (Tai6.3022, Tai6.16429, and Tai6.3019), all three LDOX genes
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(Tai6.40394, Tai6.53285, and Tai6.42091), and all five UFGT genes (Tai6.16002,
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Tai6.17387, Tai6.34855, Tai6.47630, and Tai6.47631). One CHI (Tai6.7312) and one
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F3H (Tai6.9545) genes were identified in the sweetpotato genome, both of which
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showed a higher level of expression in XZS-3. We also identified two
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O-methyltransferase (OMT) genes, and one was up-regulated while the other one was
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down-regulated in XZS-3. Among the 23 glutathione S-transferase (GST) genes, 13
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were up-regulated while the other ten were down-regulated in XZS-3. In addition, five
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multidrug and toxic compound extrusion (MATE) genes were identified and all
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showed a lower expression level in XZS-3.
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Fig. 3. Expression profiling of the representative enzyme and transporter genes
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involved in anthocyanin pathways between XS-18 and XZS-3. In the middle of the
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figure was the schematic of anthocyanin pathway. The outside of the figure was
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heatmap diagrams showing the expression differences of the main genes between
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XS-18 and XZS-3. Expressions of the genes validated by qRT-PCR were highlighted
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in bold font. Phenylalanine ammonia lyase (PAL), 4-coumaroyl, CoA ligase (4CL),
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chalcone synthase (CHS), flavanone 3-hydroxylase (F3H), chalcone isomerase (CHI),
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dihydroflavonol-4-reductase (DFR), leucoanthocyanidin dioxygenase (LDOX),
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O-methyltransferase
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(UFGT), glutathione S-transferase (GST), multidrug and toxic compound extrusion
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(MATE).
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(OMT),
UDP-glucose
anthocyanin 3-o-glycosyltransferase
3.6 Expression profiling of TFs involved in anthocyanin pathways
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TFs play important roles in regulation of anthocyanin biosynthesis by modulating the
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expression of enzyme genes and other related genes. RNA-seq analysis identified a
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total of 87 differentially expressed TF genes, including 21, 19, 16, 15, and 6 members
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from the bHLH, MYB, C3H, ZF, and WD subfamilies, respectively (Fig. 4a, Table
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S10), consistent with that the biosynthesis of anthocyanins is associated with the
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formation of the MYB-bHLH-WD40 (MBW) activation/repression complexes. A
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similar number of bHLH, MYB, and C3H genes were up- or down-regulated in PFSP.
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Of the six WD genes, four were up-regulated while the other two were
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down-regulated in XZS-3. Of the 15 ZF genes, 11 showed significant up-regulation in
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XZS-3. In addition, 4, 3, and 2 members were identified from the TCP, bZIP, and
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NAC subfamilies, respectively (Fig. 4A, Table S10). One of the four TCP genes and
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two of the three bZIP genes showed a higher level of expression in XZS-3. Both of
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NAC genes showed a lower level of expression in XZS-3. One far-red impaired
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response1 (FAR1) gene was identified and up-regulated in XZS-3.
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Fig. 4. Heatmap diagrams of TFs involved in anthocyanin and Aux/IAA-ARF
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Pathways. (a) Profiling of differentially expressed anthocyanin-related TFs pathway,
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(b) Profiling of differentially expressed auxin-related TFs. The nine different colors of
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the first column corresponds to the nine different gene subfamilies. The other columns
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in the heatmap represented the samples. The color scale bar on the right side
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represented the average FPKM value of log-transformed. basic helix-loop-helix
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(bHLH), MYB proteins (MYB), WD40 repeat proteins (WD), cys3His zinc finger
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(C3H), zinc finger proteins (ZF protein), TCP proteins (TCP), basic region/leucine
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zipper (bZIP), NAC transcription factor (NAC), far-red impaired response1 (FAR1).
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3.7 Expression profiling of TFs associated with Aux/IAA-ARF Signaling Pathways
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Auxin is an important plant hormone, but the relationship between auxin and
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anthocyanin biosynthesis is unclear in sweetpotato. In this study, we identified 26
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differentially expressed Aux/IAA and ARF TF genes associated with the auxin signal
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pathway (Fig. 4b, Table S11), of which 21 showed elevated expression in the PFSP
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cultivar, including Auxin-responsive proteins IAA13, IAA14, IAA16, IAA27, ARF4,
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ARF6, ARF9, ARF12 and AUX22D. However, the other five appeared to be
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down-regulated, including IAA26, ARF5, AUL1 and two AUX1.
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3.8 Quantitative RT-PCR of DEGs
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A total of 22 representative DEGs between WFSP and PFSP cultivars were selected
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for qRT-PCR analysis. In general, the expression patterns of the 22 DEGs revealed by
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qRT-PCR matched those derived from RNA-seq (Fig. 5). Notably, the expression of
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the eleven enzyme genes were about 270-25,000 times higher in XZS-3 than in
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XS-18.
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Fig. 5. Comparison of expression profiling of 22 representative genes profiled by
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qRT-PCR
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anthocyanin-related TFs and four auxin-related TFs. Columns above and below y-axis
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0 represented expression determined by qRT-PCR and by RNA-seq in FPKM values,
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respectively. IbActin was used as reference control. Relative gene expressions were
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determined by the comparative 2-ΔΔCt method Bars represented the average values ±
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SE of three separate biological replicates in triplicate. For statistical analysis,
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two-tailed t-test of Dunnett was applied. The differences were defined to be
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statistically significant when p ≤ 0.05 (indicate as *) and p ≤ 0.01 (indicate as **).
and
transcriptome,
including
eleven
structure
genes,
seven
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3.9 SNP identification
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We assembled all the transcripts and found that 7,361 transcripts did not exist in the
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standard annotation library (Table S13). We used Tophat2 to map the reads to the
357
reference genome (a WFSP genotype) and identified high-confidence SNPs based on
358
multiple criteria including read depth and allele frequency. Among these SNPs, we
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focused on the sequence variability of enzyme genes related to anthocyanin
360
biosynthesis (Table S12). When compared with the reference genome, the UFGT,
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A3G, DFR, and F3H alleles from PFSP are more polymorphic than the alleles from
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WFSP. As shown in Fig. S3, the number of SNPs in PFSP is nearly twice that in
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WFSP. In contrast, the numbers of SNPs in LDOX, CHS, F3'M, 3GGT, F3′,5′H, and
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ANR were similar and did not show significant difference between PFSP and WFSP.
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Therefore, there may be many functional SNPs in UGFT, A3G, DFR and F3H genes
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that affect the expression or activity of these genes, resulting in natural variation in
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anthocyanin biosynthesis.
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3.10 Correlation analysis between transcriptome and metabolites
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To further characterize the metabolic pathways for anthocyanin synthesis, we
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constructed gene-metabolite networks by integrative analysis of the metabolome and
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transcriptome data. For this purpose, six DAMs (peonidin O-hexoside, rosinidin
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O-hexoside, peonidin O-malonylhexoside, delphinidin, petunidin 3-O-glucoside, and
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cyanidin) and the top 1000 DEGs were used for association analysis (Fig. 6, Table
375
S13). Each DAM was significantly correlated with the DEGs, and we selected the
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top100 web links for further analysis. Among these genes, GST (Tai6.17033,
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Tai6.19248, Tai6.25547, and Tai6.24771), F3H (Tai6.9545), starch synthase 2 (SS2,
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Tai6.26337), quinone oxidoreductase (QOR, Tai6.41481), wall-associated receptor
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kinase 3 (WAK3, Tai6.36254), WRKY transcription factor 20 (WRKY20 and
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Tai6.3520), serine carboxypeptidase-like 41 (SCPL41 and Tai6.35008), LDOX/ANT
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(Tai6.42091), bHLH (Tai6.36440 and Tai6.28734), CHI (Tai6.15773), CHS
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(Tai6.29634), and Zerumbone synthase (ZSD1, Tai6.5425) were found to be highly
383
correlated with the metabolites.
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Fig. 6. Correlation network diagram of DAMs and DEGs. The larger the point, the
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stronger the correlation. peonidin O-hexoside (POH), rosinidin O-hexoside (ROH),
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peonidin O-malonylhexoside (POM), petunidin 3-O-glucoside (P3G).
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4. Discussion
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Sweetpotato, a member of the Convolvulaceae family, has become one of the most
392
popular foods (Kwak, 2019). In PFSP, the purple flesh accumulates abundant
393
anthocyanins
394
understanding the anthocyanin biosynthesis in sweetpotato will facilitate breeding or
395
engineering plants to boost the anthocyanin production (Kim et al., 2020). In this
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study, the metabolome and transcriptome of PFSP and WFSP were characterized, in
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order to gain insights into the genes and metabolites that are associated with
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anthocyanin biosynthesis, accumulation, and regulation.
that
are
important
health-promoting
compounds.
Therefore,
399 400
Analysis of the differentially accumulated metabolites between PFSP and WFSP
401
revealed
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O-malonylhexoside, delphinidin, and cyanidin were specifically present or more
403
abundant in PFSP, indicating that anthocyanin metabolism is more active in PFSP
that
peonidin
O-hexoside,
rosinidin
O-hexoside,
peonidin
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than in WFSP. In particular, delphinidin, peonidin and rosinidin, which contribute to
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red or blue colors in plant organs, were highly present in PFSP but absent in WFSP
406
(Fig. 1, Table S2 and S3), suggesting that they are the key anthocyanin derivatives
407
conferring the purple pigmentation in PFSP.
408
The biosynthesis of anthocyanin involves numerous enzyme genes. Many of these
410
enzyme genes were differentially expressed between the PFSP and WFSP genotypes.
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In particular, most of the CHS, CHI, F3H, DFR, and LDOX homologs showed a
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higher level of expression in PFSP than in WFSP, indicating that these genes play key
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roles in anthocyanin biosynthesis and accumulation in PFSP. In addition, five UFGT
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genes, which are required for glycosylation to stabilize anthocyanins, also showed a
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higher level of expression in PFSP when compared with WFSP, consistent with the
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important roles that UFGT genes play in the anthocyanin pathway in other plants
417
(Kobayashi et al., 2004; Wang et al., 2013; Zhang et al., 2020; Zhou et al., 2020).
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Glutathione S-transferases (GSTs) act as non-enzymatic carrier proteins to escort
419
conjugated anthocyanins to the MATE transporters at tonoplast (Edwards et al., 2000)
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(Alfenito et al., 1998). Interestingly, among 23 differentially expressed GST genes
421
identified in this study, three (Tai6.30213, Tai6.17033, and Tai6.29612) were
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significantly up-regulated (>500 times) in PFSP, suggesting that the three GSTs may
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play important roles in anthocyanin transport in sweetpotato.
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The expression of the enzyme genes in anthocyanin pathways is modulated by TFs.
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This is achieved by physical interactions between R2R3-MYB, bHLH, and WD TFs,
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forming ternary complexes (MBWs) responsible for the coordination of anthocyanin
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biosynthesis (Jaakola, 2013). Consistent with this, more than half (46) of the 87
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differentially expressed TFs belong to the R2R3-MYB, bHLH, and WD subfamilies,
430
highlighting their important roles in regulation of the anthocyanin pathway.
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addition, we found two NAC100 genes that were significantly down-regulated in PFSP.
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NAC TFs have a variety of biological functions. In peach, ppNAC1 activates the
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transcription of ppMYB10.1 to promote anthocyanin pigmentation (Zhou et al., 2015).
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The low expression of NAC100 genes in PFSP than in WFSP might suggest negative
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roles of these genes in the anthocyanin biosynthesis or accumulation; similar
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expression patterns were also observed for the NAC1 and NAC2 in purple-fleshed
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sweetpotato (Chen et al., 2016).
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In
438 439
Phytohormones are also an important factor affecting accumulation of anthocyanins in
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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
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Komamine, 1986). High concentrations of auxin significantly inhibited anthocyanin
443
biosynthesis in cultured callus of red-fleshed apple (M. sieversii f.niedzwetzkyana) (Ji
444
et al., 2014). In the apple fruit skin of ‘Red Delicious’ and its four generation bud
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sport mutants, IAA and ABA had a positive regulatory effect on the anthocyanin
446
formation, while GA had an inhibitory effect (Li et al., 2018). Wang et al. (2018)
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reported that the increasing NAA concentrations increased the expression of
448
Aux/IAA-ARF and decreased anthocyanin accumulation in apple. Interestingly, we
449
observed that 21 of the 26 auxin-related genes in the Aux/IAA-ARF family exhibited
450
significant up-regulation in PFSP (Fig. 4b, Table S11), suggesting that these
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Aux/IAA-ARF signaling factors may modulate the expression of transcripts involved
452
in anthocyanin pathways. Specifically, auxin may trigger the expression of the
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homologous genes encoding IAA13, IAA14, IAA16, IAA27, ARF4, and ARF6, which
454
act as activators in anthocyanin biosynthesis in PFSP. In contrast, IAA26, ARF5,
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AUL1, AUX1, and LAX2 were down-regulated in PFSP and these genes may function
456
as repressors in anthocyanin biosynthesis. Aux/IAA-ARF TFs exhibit dynamic
457
functions in plants and have a central role in the hub of transcriptional networks. The
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altered expressions of Aux/IAA-ARF TFs between WFSP and PFSP suggested a
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novel metabolic function for Aux/IAA-ARF proteins.
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In summary, our study revealed anthocyanin metabolites that contribute to the purple
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pigmentation in purple-fleshed sweetpotato. We also showed that the altered
463
expression of the anthocyanin pathway genes and regulatory transcription factors
464
account for the difference in anthocyanin accumulation in PFSP and WFSP.
465
Furthermore, we identified DEGs, including TFs and enzyme genes that were not
466
previously implicated in anthocyanin biosynthesis. Functional study should be
467
performed in the future to validate their role in regulation of anthocyanin biosynthesis
468
in sweetpotato. Knowledge gained from this study will facilitate breeding and
469
engineering sweetpotato plants for enhanced anthocyanin accumulation.
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Supplementary Materials:
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Table S1 Primer sequences used for qRT-PCR analysis
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Table S2 Determination of anthocyanin-targeted metabolites in sweetpotato
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Table S3 Differentially accumulated metabolites in XS-18 and XZS-3
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Table S4 The transcriptome profiling of XS-18 and XZS-3
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Table S5 Annotated novel transcripts
Table S6 Expressed genes within XS-18 and XZS-3
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Table S7 Co-expressed and specifically expressed genes between XS-18 and XZS-3
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Table S8 DEGs between XS-18 and XZS-3
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Table S9 The transcription levels of anthocyanin pathway-related structural genes
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Table S10 Expression profiling of TFs associated with anthocyanin biosynthesis
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Table S11 Expression profiling of auxin-related TF genes
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Table S12 SNP numbers of structural genes related to anthocyanin biosynthesis
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Table S13 Correlation analysis of the DAMs and DEGs
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Fig. S1. Venn diagram of co-expressed and specifically expressed genes between
487
XS-18 and XZS-3.
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Fig. S2. Functional Enrichment of DEG by KEGG analysis.
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Fig. S3. The differences in the number of SNPs in the structural genes of anthocyanin
490
synthesis between PFSF and WFSF.
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Author Contributions: Xiaoyun Jia, Hongyan Zhu, Runzhi Li and Liheng He
493
conceived the original research plans. Xiaoyun Jia and Liheng He designed the
494
experiments. Liheng He, Xiayu Liu, Shifang Liu, Jie Zhang and Yan Sun collected the
495
materials; Liheng He, Xiayu Liu, Shifang Liu and Yi Zhang conducted the
496
experiments and analyzed the data. Liheng He and Xiaoyun Jia drafted the manuscript;
497
Ruimin Tang, Wenbin Wang, Hongli Cui, Xiaoyun Jia, Runzhi Li and Hongyan Zhu
498
modified the manuscript. All authors read and approved the manuscript.
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Funding: This study was funded by National Key Research and Development
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Program of China (2018YFD1000700, 2018YFD1000705), Key Research and
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Development Project of Shanxi Province (201803D221008-6), Natural Science
503
Foundation of Shanxi Province (201801D121238), Science and Technology
504
Innovation project of Shanxi Agricultural University (2018yz001), Shanxi Provincial
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Leading Talents in Emerging Industries Project, Special Plan of Scientific Research
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for Shanxi Agriculture Valley Construction of China (SXNGJSKYZX201701-03).
507
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Highlights
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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.
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☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
![[No title available]](/assets/img/hold.png)
