Anthocyanins, a kind of secondary metabolites, impart vivid colors of fruits, flowers and vegetative tissues of higher plants (Bradshaw and Schemske, 2003; Hatier and Gould, 2009; Speciale et al., 2010). Anthocyanins possess antioxidant, anti-carcinogenic, anti-inflammatory, and anti-microbial properties (Hatier and Gould, 2009; Speciale et al., 2010). Anthocyanins were reported to increase plant resistance to abotic stresses and diseases (Hatier and Gould, 2009; Li et al., 2017), serve as attractants for insects and animals(Gould and Lister, 2006), and prevent people suffering from some diseases (Jing et al., 2008; Speciale et al., 2010; Fairlie-Jones et al., 2017), making anthocyanin biosynthesis and accumulation of important.

Anthocyanin i a member of flavonoid family and its biosynthesis pathway thaliana, has been well determined in Arabidopsis. The key enzymes mainly are: pheylalanine ammonialyase (PAL), cinnamate 4-hydroxylase (C4H), 4-coumarate CoA-ligase (4CL), chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavonoid 3-hydroxylase (F3′H), flavonoid 3′5′-hydroxylase (F3′5′H), dihydroflavonol 4-reductase (DFR), leucoanthocyanidin dioxygenase (LDOX), and UDP-glucose:flavonoid 3-O-glucosyltransferase (UFGT) (Winkel-Shirley, 2001; Ai and Zhu, 2018). After a series enzymatic reactions catalyzed by different enzymes, anthocyanins finally are synthesized from L-phenylalanine (L-Phe) (Winkel-Shirley, 2001). Similar flavonoid pathway is also observed in Zea mays, Solanum melongena, and Petunia hydrida etc. (Hloton and Cornish, 1995; Winkel-Shirley, 2001; Zhang et al., 2014).

Generally, anthocyanin biosynthesis is regulated by genetical and environmental factors, including structural genes, transcription factors (TFs) (Stracke et al., 2007; Lloyd et al., 2017), plant hormones (Carvalho et al., 2010), temperature (de Rosas et al., 2017), and light (Ma et al., 2019). Structural genes encode enzymes directly participating in anthocyanin biosynthesis, such as PAL and C4H (Davies and Schwinn, 2003; Takos and Walker, 2006). TFs directly activate or repress the expression of structural genes to modulate flavonoid metabolites, including basic helix-loop-helix(bHLH), WD40, WRYK, Zinc finger, and R2R3 MYB families (Hichri et al., 2011; Fairlie-Jones et al., 2017). R2R3MYB, bHLH, and WD40 forming MBW complex are considerate as major regulators though the potential mechanisms of this complex are still unknow (Hichri et al., 2011).

Among environmental factors, both light and temperature have been identified to affect anthocyanin biosynthesis. Researches have revealed that light contributes to anthocyanin biosynthesis in Lc petunia and apple (Takos et al., 2006; Albert et al., 2009). It has been verified that low temperature (LT) promotes anthocyanin production in maize (Christie et al., 1994), red oranges (Lo Piero et al., 2005), and apples (Ubi et al., 2006), while high temperature inhibits anthocyanin accumulation (Mori et al., 2007). LT positively regulates MdMYBA expression, encoding an apple TF, which binds to ANS promoter and activates ANS expression, resulting in anthocyanin accumulation in apple skin (Ban et al., 2007). A PA1 -type MYB TF MdMYBPA1, was identified to response to low temperature and anthocyanin in red-fleshed apple (Wang et al., 2018). In potato (Solanum tuberosum L.), StMYB44 was characterized to repress anthocyanin accumulation under high temperature (Liu et al., 2019).

Purple pakchoi (Brassica rapa ssp, B.rapa, Chinensis Makion) , rich of anthocyanins, is one of the most popular vegetables (Simone et al., 2006). In purple pakchoi, LT was reported to induce distinct anthocyanin metabolic pathways (Christie et al., 1994; Chalker-Scott, 1999) [10,9] [10,9]. In this study, we presented a purple pakchoi cultivar, 'ziyi', whose purple leaf color started to deepen at day 10 after LT treatment. To further study the mechanism of color change, we detected anthocyanin content in leaves. Results showed that the darker color leaves were of higher anthocyanin content. Leaves maintained at 5°C for 10 d were collected to extract total RNA for RNA sequencing (RNA-Seq). RNA-Seq results showed that anthocyanin biosynthesis related genes were differentially expressed in leaves at 5°C than that of control. qRT-PCR further confirmed that the expression levels of C4H, CHS, F3H, HY5, UGT75C1, and FLS, were increased after 5°C. Collectively, low temperature promotes leaf color deepening through anthocyanin biosynthesis pathway, causing anthocyanin accumulation in purple pakchoi.

1 Results

1.1 Temperature affects leaf color and anthocyanin content

To study the effect of temperature on leaf color, a purple pakchoi cultivar “yizi” was treated with LT, HT and NT conditions for 2 d, 4 d, 6 d, 8 d, 10 d, and 12 d, respectively. Results showed that leaf color of plants started to deepen after 2d-LT treatment and positively correlated with the time expose to LT (Figure 1A; Figure 1B). Contrarily, the leaf color of plants treated with HT turned to lighter at day 2 compared to that of plants treated with NT (Figure 1A). As leaf color associates with anthocyanin content, we measured the anthocyanin content in plant leaves exposed to different temperature conditions. It revealed that anthocyanin level gradually increased after LT from 3.79 mg/g to 13.41 mg/g at 5°C and gradually decreased after HT from 3.78 mg/g to 1.52 mg/g from day 2 to day 12 (Figure 1B). These data reveal that LT plays a positive regulator and HT is a negative regulator during anthocyanin biosynthesis and accumulation.

Figure 1 Anthocyanin content and the color of purple pakchoi at LT (5°C), NT (20°C), and HT (35°C). (A) Change of leaf color treated with LT, NT and HT for indicated days. (B) Anthocyanin content in purple pakchoi treated with different temperatures from 0 d to 12 d

1.2 High-through put sequencing and de novo assembly

To further investigate the mechanism of changed anthocyanin content after different temperature treatment, transcriptome profiles of pakchoi at day 10 under NT, LT, and HT conditions were analyzed, respectively. After RNA-Seq, a total of 148 517 620 135 058 374 and 132 198 886 raw reads were obtained from sample of NT, LT, and HT, respectively. After filtering reads with low quality, a total of 146 935 754 of NT 133 743 948 of LT and 130 788 732 of HTclean reads (a base quality greater than 20) were obtained (Table 1). All clean reads were de nove assembled by Trinity software, after which 51008 unigenes were obtained with an average length of 762.96 bp, a maximum length of 7 750 bp, a minimum length of 201 bp, an N50 of 1 074 bp, and an E90N50 of 1 333 bp (Table 1).

Table 1 Statics of high-through put sequencing

1.3 Functional annotation and classification of assembled transcripts

To further annotate these unigenes and understand the overall expression profiles of ‘ziyi’, all unigenes were searched against the NR, GO, KEGG, Pfam, COG, and Swiss-Prot. Totally, 51 008 unigenes had homologous sequences in at least one of the six mentioned databases. Among them, 42 828 (83.96%), 33 883 (66.43%), 30 426 (59.65%), 13 358 (26.19%), 25 998 (50.97%), and 20 882 (40.82%) unigenes were found in the NR, SwissProt, Pfam, COG, GO, and KEGG databases, respectively (Figure 2).

Figure 2 Functional annotation of unigenes

1.4 Temperature affects anthocyanin homeostatic genes

To calculate the expression levels of unigenes, we employed expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced (FPKM) method (Trapnell et al., 2010). The DEGs were defined with P ≤ 0.05 and fold change ≥ 2. Totally, 8 455 and 4 321unigenes were differentially expressed in LT and HT treatment, respectively (Figure 3). Among these DEG, a total of 391 unigens responded to LT and HT simultaneously of which 173 unigenes were upregulated in HT and downregulated in LT whereas 218 were downregulated in HT and upregulated in LT. These data indicated that the 391 unigenes might involve in temperature-associated anthocyanin biosynthesis and accumulation.

Figure 3 Venn analysis of differentially expressed unigenes

To further understand the 391 unigenes’ functions, GO functional enrichment and KEGG pathway analyses were performed. The 391 unigenes were categorized into 44 functional groups in three main categories of “biologica process”, “cellular component”, and “molecular function”. A total of 132 unigenes were assigned to binding, 129 were to catalytic activity, 98 were to metabolic process, and 97 were to cell (Figure 4). Ninety-five unigenes were categorized to cellular process, membrane, and cell part, respectively (Figure 4). These data revealed that unigenes involved in anthocyanin accumulation were functional diverse.

Figure 4 GO enrichment analysis of DEGs in response to LT and HT

By analyzing the KEGG pathways related to the DEGs, it was revealed that 295 unigenes were mapped to KEGG pathways to reveal the biological pathways that unigenes were involved. The largest group was pheylpropanoid biosynthesis which 10 unigenes were mapped to (Figure 5). Phenylalaninsurves as the substrate for flavonoids biosynthesis via phenylpropanoid pathway (Hichri et al., 2011). Eleven unigenes were mapped to anthocyanin biosynthesis or related pathways (Figure 5).

Figure 5 Analysis of KEGG pathway of the 391 DEGs

1.5 Discovery of anthocyanin-associated genes

As anthocyanin biosynthesis is affected by structural genes encoding diversity enzymes were analyzed. Structural genes, including PAL2 (TRINITY_DN16735_c1_g7), CHS (TRINITY_DN18090_c2_g1), 4CL (TRINITY_ DN13099__c0__g2), F3H (TRINITY_DN11496_c0_g2), CHI (TRINITY_DN 18244_c0_g1), and UGT75C1 (TRINITY_DN6415_c0_g1), were found to be up-regulated in LT and down-regulated in up-regulated, (Figure 6A). Additionally, transcription factors play vital roles in anthocyanin homeostatics, therefore we also analyzed the differentially expressed transcription factors. Among DEGs, 20 unigenes might encode transcription factors based GO and KEGG analyses. Three unigenes, MYB6 (TRINITY_DN17146_c0_g5), bZIP1 (TRINITY_ DN12420_c0_g1), and COL2 (COSTANs-LIKE 2), were up-regulated after HT and down-regulated after LT (Figure 6B). Contrarily, fourteen unigenes, encoding MYB4, bZIP22, bHLH44, bHLH128, ERF9, DREB1B, ERF043, ERF023, ERF72, TOE1, TOE3, WRKY44, GATA7, and GATA22, were down-regulated after HT and up-regulated in LT (Figure 6C). These results indicated that these transcription factors might be involved in anthocyanin biosynthesis or accumulation to response to temperature stress.

Figure 6 Relative expression (log2) of structural genes (A) and transcription factors (B) and (C) in LT and HT in RNA-Seq. (A-C) Gene expression level was analyzed by RSEM, P -adjust <0.05

2 Discussion

Low temperature has been described to be important for increasing anthocyanin production. In Arabidopsis, apples, and pears, anthocyanins was reported to be induced by LT (Leyva et al., 1995). LT increased anthocyanin concentration through promoting the expression of anthocyanin biosynthesis-related genes (Lo Piero et al., 2005; Steyn et al., 2009; Ubi et al., 2006). In our study, anthocyanin concentration of purple pakchoi gradually increased over time from day 0 to day 12 following LT treatment and decreased following HT treatment (Figure 1). Similar anthocyanin concentration alteration was found in Brasscica rapa, indicating temperature plays a vital role in enhancing anthocyanin concentration in these plants (Ahmed et al., 2015).

Because of the development of next generation sequencing (NGS), transcriptome sequencing has become an effective research tool with low cost and high throughput (Galla et al., 2009; Kang et al., 2013). Through RNA-Seq analysis, we observed lots of genes altered their expression levels after LT treatment. Among DEGs, PAL, CHS, CHI, F3H, 4CL, and UGT75C expression levels, involved in anthocyanin biosynthesis, were identified to be induced by LT and inhibited by HT (Figure 6). These results suggested that these genes play important roles in temperature-mediated anthocyanin biosynthesis in pakchoi, consistent with the findings of Qu et al. (2015). Previous researches revealed that CHS were differentially expressed between red and yellow flesh sweet cherry (Prunus avium L.) (Wei et al., 2015). Similar results were obtained in arctic mustard and purple lettuce transcriptomes (Butler et al., 2014; Zhang et al., 2016). In our study, we proved that most enzymes were also involved in anthocyanin biosynthesis in purple pakchoi.

Among these genes, MYB TFs have been identified as key determinants of the color differences among cultivated plant varieties. In Arabidopsis, AtMYB11/PFG2, AtMYB12/PFG1, AtMYB111/PFG3, AtMYB75/PAP1, AtMYB90/PAP2, AtMYB113, and AtMYB114 have been identified to have the ability to activate the expression of anthocyanin biosynthetic genes, while AtMYB3, AtMYB4, AtMYB7, and AtMYB32 repress the expression of these genes (Dubos et al., 2010). In horticultural plants, many MYB TFs, such as Chinese cabbage BrMYB2, Tricyrtis sp. TrMYB1, and purple cauliflower BoMYB2, were identified to be involved in anthocyanin biosynthesis (He et al., 2016; Kanemaki et al., 2018). In our study, we found 6 unigenes were differentially expressed, which annotated to MYB or MYB-like family, including MYB4 and MYB6. These data suggested that MYB4 and MYB6 might be also involved in temperature-mediated anthocyanin biosynthesis in pakchoi, which are deserved to be further studied.

Collectively, using a high-throughput sequencing platform, the transcriptomes of purple pakchoi at 5°C, 20°C, and 35°C were surveyed. 8 571 differentially expressed unigenes were observed between two treatments. We revealed the mechanism of anthocyanin biosynthesis and accumulation under different temperature. Purple pakchoi adjusts gene expression levels to accumulate anthocyanin to response to temperature stress. These findings provide the first global insights into the mechanisms of anthocyanin metabolism in purple pakchoi. In addition, this study involves pakchoi sequencing data, for which there is no sequenced genome, for future investigations of the molecular biological mechanisms of this species.

3 Materials and Methods

3.1 Plant material and growth conditions

The purple pakchoi, 'ziyi', seeds were supplied by Protected Horticultural Research Institute, Shanghai Academy of Agricultural Sciences (China). The seeds were sown in plastic plates containing peat: vermiculite (2 : 1, v/v) in a growth chamber for temperature treatment or harvest seeds.

3.2 Temperature treatment

Four-week-old leaves were used after germination in the growth chamber (PGX-350A, Shenxian thermostatic equipment factory, Shanghai). The growth chamber was set to ~60% relative humidity and the photo period was 6-h light/8-h darkness using a photosynthetic photon flux density (PPFD) of 800~1 000 μmol m-2s-1. Plants were treated with LT (5°C, LT) or NT (control) for 2, 4, 6, 8, 10 and 12 d and each group had 60 plants. After treatment, leaves were harvested to detect anthocyanin content and extract total RNA for RNA-Seq or detecting gene expression.

3.3 Anthocyanin content measurement

Total anthocyanin content was measured with the modified pH differential method (AOAC office method 2005.2) (Sukwattanasinit et al., 2007; Jungmin et al., 2008). Briefly, a total of 20 mg of leaf samples was used to extract with 10 mL of extraction buffer [95% ethanol and 1.5 mol·L^-1HCl (V/V=85:15)] at room temperature in the dark for 24 h. The extracted solution (1mL) was added with 2 mL of 0.025 M KCl buffer at pH 1.0 and 0.4 M NaAc at pH 4.5, adjusted to a pH value of 1.0 or 4.5 with hydrochloride. Absorbance was measured with a nucleic acid/protein analyzer (Beckman Coulter, Inc. USA) at 536 nm and 700 nm in the buffers with pH 1.0 and pH 4.5 buffers, respectively. The total absorbance (A) was calculated as follows:

A=(A₅₃₆-A₇₀₀)pH1.0-(A₅₃₆-A₇₀₀)pH4.5

The TAC was derived using cyanidin-3-glucoside, which has a molar extinction coefficient of 26 900 Lcm^-1mol^-1 and a molecular weight of 449.2 gmol^-1. The results are expressed as milligrams of cyanidin-3-glucoside equivalent per gram of the fresh sample weight.

3.4 RNA extraction and gene expression analysis

Total RNA was isolated from control and LT samples using TRIzol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer's protocol. RNA quality and quantity were detected using an Agilent 2100 Bioanalyzer (Agilent, MN，US). The qualified total RNA was used to synthesize first strand cDNA, which used as templates for qRT-PCR. The qRT-PCR was conducted and SYBR Green PCR Kit (ABI7300) in a MicroAmp™ 96-well plate were measured on a StepOnePlus™ Real-Time PCR System (ABI, US). The 2 ^-ΔΔCt method was used to calculate the relative expression levels of the target genes. Primers used are listed in Table 1.

3.5 RNA-Seq

The extracted total RNA was isolated from plants treated with NT, 10-day LTand 10-day HT. RNA concentration and quality were detected using Agilent 2 100 Bioanalyzer. The synthesized cDNA libraries were sequenced by Illumina NextSeq 500 instrument (Personalbio, China). The transcriptome sequence processing was previously described (Jia et al., 2015). Briefly, raw data with low quality (reads with a base quality less than 20) were filtered to obtain clean data, followed by de novo assembly with Trinity software (version: r20140717, k-mer 25 bp, http://trinityrnaseq.sf.net). Transcipt abundance was normalized using a k-mer value of 25 reads per kilobase of exon model per million mapped reads (RPKM) (Wagner et al., 2012). Differentially expressed genes (DEGs) were defined with fold change≥2.00 and P ≤0.05.

3.6 Gene annotation and ontology

The functional annotations were performed by comparing the sequences with those in public databases, including NCBI nonredundant protein database (NR), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Groups of proteins (COG), Pfam, and Swiss-prot database. According to GO term, unigenes were classified within molecular functions, cellular components, and biological processes (Conesa et al., 2005). To investigate metabolic and cellular pathways, unigenes were also assigned to special biochemical pathways based on KEGG database.

Authors’ contributions

Hongfang Zhu conducted detected the anthocyanin contents under LT and HT, harvested samples for RNA-Seq and analysis the results of RNA-Seq. Dandan Xi prepared this manuscript. Xiaofeng Li and Lu Gao helped Hongfang Zhu to carry out these experiments. Yuying Zhu designed all experiments and directed experiments. All authors read and approved the final manuscript.

Acknowledgments

This study was supported by Shanghai Science and Technology Development Committee (18391900700) and Agriculture Research System of Shanghai, China (Grant No. 202002). We thank MajorBio (China) for analysis of RNA-Seq.

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