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. 2022 Feb 20;28(2):315–331. doi: 10.1007/s12298-022-01142-2

Comparative transcriptome analysis revealed the molecular mechanism of the effect of light intensity on the accumulation of rhynchophylline and isorhynchophylline in Uncaria rhynchophylla

Xiao-Hong Wang 1,2, Xue Li 1, Wei Qiang 1, Xiao-Song Yu 1, Hao-Jie Zheng 1, Ming-Sheng Zhang 1,✉
PMCID: PMC8943091  PMID: 35400883

Abstract

Rhynchophylline (RIN) and isorhynchophylline (IRN), the main medicinal components in plant Uncaria rhynchophylla, have potential effects on Alzheimer’s disease. Understanding the influence of environmental factors, especially light intensity, on the production of these active ingredients will help to improve cultivation techniques. Compared with the 100% light intensity (CK), the contents of RIN and IRN in U. rhynchophylla leaves significantly increased at 20% light intensity (HS) after 7 and 21 days. Short-term shading (21d) changed some morphological indicators of U. rhynchophylla, but did not affect its biomass. Transcriptome profile analysis was performed on data from two groups (7 and 21 days) of CK and HS samples and yielded 79,817 unigenes with an average length of 1023 bp. Concurrently, 2391 and 2136 differentially expressed genes were identified in the transcriptome data for, respectively, 7 and 21 days of shade treatment. Notably, unigenes known to be involved upstream in the biosynthesis of RIN and IRN, such as G8O, IO, 7-DLGT, LAMT, TDC, and STR, were mostly upregulated. In addition, 1065 putative transcription factors (TFs) were identified and grouped into 55 TF families; 26 TFs showed differential expression in the shade treatment after 7 and 21 days. HY5 and PIFs, two important TFs of the light signaling pathway, also showed differential expression. This study provides insight into how gene expression was affected by light intensity during RIN and IRN accumulation in U. rhynchophylla.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01142-2.

Keywords: Uncaria rhynchophylla, Light intensity, Transcriptome, Terpenoid indole alkaloids

Introduction

Uncaria rhynchophylla (Miq.) Miq. ex Havil., belonging to the family Rubiaceae, is an important traditional Chinese medicine plant. Fragments of dried stems with hooks have been used to treat convulsion, epilepsy, eclampsia, hypertension, and brain diseases (Ndagijimana et al. 2013; Zhang et al. 2015). The studies on pharmacological activity showed that indole alkaloids were not only the characteristic components of U. rhynchophylla, but also the main active components. Rhynchophylline (RIN) and isorhynchophylline (IRN), a pair of stereoisomers, are the main indole alkaloid constituents of the plant responsible for various therapeutic effects (Zhou and Zhou. 2010; Zhang et al. 2015; Wang et al. 2017). Recently, RIN and IRN have attracted increasing research attention for their neuroprotective actions. Research has shown they may be suitable for the treatment of Alzheimer’s disease (AD) through a variety of mechanisms (Yuan et al. 2009; Xian et al. 2012).

Light is one of the most influential environmental factors; it is used as a source of energy and as a signal to regulate plant growth and development and secondary metabolism (Höft et al. 1996; Cai et al. 2009; Liu et al. 2015; Ajmi et al. 2018). Recently, great progress has been made in understanding light regulation of plant secondary metabolism (e.g. anthocyanin and terpenoid) (Zhou et al. 2015; Jiang et al. 2016). Light also plays an important role in the regulation of alkaloid biosynthesis. Previous studies found that the biosynthesis of camptothecin (CPT) was regulated by light intensity: compared with full light conditions, heavy shading (27% irradiance) increased the CPT content of Camptotheca acuminata leaves by about 40% (Liu et al. 1997). Hu et al. (2016) got similar results whereby C. acuminata grown under 50% irradiance had the highest CPT content, followed by 25 and 75% irradiance and full sunlight. Conversely, light significantly increased the content of vindoline in Catharanthus roseus C20hi cell suspension (0.49–5.51 times that of the controls) (He et al. 2011). These results suggest there are different regulatory mechanisms of light on alkaloid synthesis in different plants. Regarding U. rhynchophylla, it is unclear whether the contents of RIN and IRN are affected by light intensity.

Many studies have shown that the mechanisms underpinning shade effects on plant secondary metabolites may be complex, and related to light intensity and the responses of various photoreceptors and the components of light signal transduction (Hu et al. 2016; Pacín et al. 2016). When plants are under shade, they perceive the light quality and quantity through various photoreceptors (Fraser et al. 2016). This mechanism involves various photoreceptors and early signaling events in response to different light signals (Pacín et al. 2016; Galvão and Fankhauser 2015), including at least four different families of photoreceptors: phytochromes, cryptochromes, phototropins, and UV RESISTANCE LOCUS 8 (UVR8) (Kagawa 2003; Nagatani 2010; Chaves et al. 2011; Jenkins 2014). Phytochrome interaction factors (PIFs) and ELONGATED HYPOCOTYL 5 (HY5) have been shown to play a critical role in regulating the accumulation of alkaloids in response to light (Chang et al. 2018; Liu et al. 2019). Recently, Chang et al. (2018) identified a light-responsive bZIP transcription factor CaLMF in C. acuminata, and overexpression of CaLMF suppressed the expression of CPT biosynthetic genes and reduced the accumulation of CPT in the leaves. In addition, the CrPIF1 of C. roseus is a repressor of the vindoline biosynthesis. CrPIF1 reduces gene expression by inhibiting DAT promoter activity (Liu et al. 2019).

RIN and IRN belong to terpenoid indole alkaloids (TIAs) (Ndagijimana et al. 2013; Liang et al. 2019). Generally, TIAs are derived from the common precursor strictosidine that is coupled to tryptamine and secologanin by strictosidine synthase (STR) (Liu et al. 2007). Tryptamine is derived from the shikimic acid synthesis pathway that starts with chorismate and includes catalysis by a series of enzymes. In this pathway, anthranilate synthase (AS) and tryptophan decarboxylase (TDC) were considered to play a key role in tryptamine biosynthesis (Hughes et al. 2004; Liu et al. 2012; Pan et al. 2016). Secologanin is derived from the secoiridoid pathway that starts with geraniol and ends with the production of secologanin; this process comprises eight enzymes to catalyze oxidation, reduction, glycosylation, and methylation reactions (Irmler et al. 2000; Collu et al. 2001; Asada et al. 2013; Salim et al. 2013; Miettinen et al. 2014). Subsequently, the central precursor strictosidine is hydrolyzed into strictosidine glycoside via the action of strictosidine β-D-glucosidase (SGD), and then strictosidine glycoside enters various metabolic pathways to produce different types of TIAs (Geerlings et al. 2000). Recently, Guo et al. (2014) proposed the late steps of the biosynthesis of RIN and IRN, which may be converted from stemmadenine by oxidation and methyl transfer, but genes involved in these enzymic reactions are still unconfirmed.

In this study, we observed that shade increased the content of RIN and IRN in leaves of U. rhynchophylla. To explore the potential mechanism, the gene expression profiles after 7 and 21 d under shading or light were analyzed by RNA-Seq. Differentially expressed genes (DEGs) involved in RIN and IRN biosynthesis were analyzed and validated by qRT-PCR. In addition, transcription factors (TFs) responsive to light intensity were analyzed and identified, which will help understand the regulatory mechanisms governing the effects of light intensity on RIN and IRN biosynthesis at the transcriptional level.

Materials and methods

Plant materials and shading treatment

The shading experiment was completed at the experimental base (N 28°11′49″, E 112°58′429″) of Guizhou University, Guiyang, China. Two-year-old healthy U. rhynchophylla plants (ground diameter 8.5–8.7 mm; plant height 51.0–53.0 cm) were transplanted into pots (diameter 27.5 cm, height 31.0 cm, one plant per pot), containing 3 kg of mixture of vermiculite: humus: soil (1:2:2, V/V/V). Plants were placed in a greenhouse on March 14, 2019; the growth conditions were: light/dark cycle 16 h:8 h, relative humidity 60 ± 5%, and temperature 25 ±  1 °C. Two months later, the plants were randomly divided into two groups (20 plants in each group). Two light intensity levels were created by placing or not placing a black shade net on top of the steel frame: 100% light intensity (no shade, CK) and 20% light intensity (heavy shade, HS). The average light intensities of CK and HS were about 1500 and 300 μmol m−2 s−1 at noon (Fig. S1). The growth conditions were consistent between the groups except for light intensity. Leaves of the same developmental stage were collected from three independent plants as three biological replicates on days 0, 1, 3, 7, 14, and 21 after treatments commenced. The collected leaves were divided into two subsamples. One subsample was immediately snap-frozen in liquid nitrogen and stored at − 80 °C until analysis; the other subsample was used to determine the content of RIN and IRN after drying and crushing.

Chlorophyll content and photosynthetic parameters

Daily changes in leaf net photosynthetic rate (Pn) was measured on three mature leaves using Li-6400XT (LI-COR, USA), and the data were averaged. Measurements were carried out on cloudless, sunny days from 8:00 to 18:00. Photosynthetic active radiation (PAR) was automatically recorded by the instrument. Three mature leaves from the middle part of the branches were selected, and chlorophyll a, chlorophyll b and carotenoids were measured according to the method described by Li et al. (2000) at the end of the experiment.

Growth parameters of U. rhynchophylla

After the experiment was completed, three plants were selected for determination of height, ground diameter, crown width, and number of leaves. Then, 10 mature leaves from the middle part of the branches were selected, and their length, width and thickness were measured. Each plant was divided into roots, stems and leaves and then rinsed with distilled water, gently blotted by filter paper, weighed, dried to constant weight at 50 °C, and weighed again.

Analysis of RIN and IRN accumulation

The contents of RIN and IRN were analyzed by high performance liquid chromatography (HPLC) using a Waters Alliance 2695 HPLC system (Shimadzu, Kyoto, Japan) equipped with a binary pump and a UV/Vis detector. The collected leaves were dried to constant weight at 50 °C and then ground into powder. Each sample was weighed to 0.1000 g of dried powder and 5 mL of 73% (V/V) methanol (HPLC grade) was added to extract RIN and IRN. Then, the mixture was sonicated in an ultrasonic bath (Ningbo Scientz Biotechnology Co. Ltd) for 50 min, followed by centrifugation at 12,000 × g for 10 min, and the supernatant was filtered through a nitrocellulose filter (0.45 μm). The 10 μL samples were injected for HPLC analysis. Chromatographic separation was performed on an Agilent ZORBAX SB-C18 column (4.6 mm × 250 mm, 5 μm); a mobile phase consisted of methanol and 0.1% ammonia water (V/V = 73:27). Isocratic elution was used. The flow rate was 1 mL min−1, and eluted peaks were detected with a UV detector at 245 nm. The contents of RIN and IRN were calculated based on the standard curves (Table S1).

RNA extraction, cDNA library construction and RNA-seq

Leaves of U. rhynchophylla under shading and control at 7 d (HS1 and CK1, respectively) and 21 d (HS2 and CK2, respectively) were collected for RNA extraction and transcriptome sequencing. Total RNA was extracted using Trizol reagent (Invitrogen, USA). The purity, concentration and integrity of RNA samples were tested using a NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific, USA) and an Agilent 2100 Bioanalyzer to ensure the use of quality samples for transcriptome sequencing. Total RNA extraction, cDNA library construction and transcriptome sequencing were performed by Beijing Biomarker Biotechnology Co., Ltd (Beijing, China). 1 μg RNA per sample was used for RNA sequencing library construction employing a NEBNext®Ultra™ RNA Library Prep Kit according to the manufacturer's instructions. Briefly, mRNA was purified using poly-T oligo-attached magnetic beads; after fragmentation of these mRNAs, the first strand cDNA was synthesized with random six base primers, and then the second strand cDNA was synthesized. The PCR was performed using Phusion High-Fidelity DNA polymerase, universal PCR primers and Index (X) Primer. Finally, PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system. The libraries were sequenced on an Illumina Hiseq 2000 platform to generate paired-end reads.

De Novo transcriptome assembly and functional annotation

Raw reads of fastq format were first processed through the in-house perl scripts, the reads containing adapter, reads containing more than 10% of unknown nucleotides, and low-quality reads were removed from the raw data to obtain clean reads. The clean reads were assembled using Trinity (Grabherr et al. 2011). Subsequently, unigenes were annotated based on the databases NR (NCBI non-redundant protein sequences), Swiss-Prot, GO (Gene Ontology), KOG/COG/eggNOG (Clusters of Orthologous Groups of proteins), and KEGG (Kyoto Encyclopedia of Genes and Genomes) using BLASTx with E-value ≤ 10−5 (Altschul et al. 1997). The predicted amino acid sequences of unigenes were compared with Pfam database using HMMER with E-value ≤ 10−10 to obtain annotation information.

Analysis of differentially expressed genes

To identify DEGs under different light intensities, clean reads were mapped back onto the assembled transcriptome by Bowtie (Langmead et al. 2009). The unigenes expression levels were normalized by Fragments Per Kilobase of transcript per Million fragments mapped (FPKM) and estimated by RSEM (Li and Dewey 2011). DEGs were identified between samples under shading and control at the same sampling time using DESeq2 (Anders and Huber 2010). The false discovery rate (FDR) ≤ 0.01 and |log2 Fold Change|≥ 1 between the two groups were used as thresholds for differential expression. Subsequently, GO enrichment analysis and KEGG pathway enrichment analysis were performed on the differentially expressed genes using topGO and KOBAS, respectively (Young et al. 2010; Mao et al. 2005).

qRT-PCR analysis

Sixteen candidate DEGs and transcription factors potentially involved in RIN and IRN biosynthesis were selected for qRT-PCR validation. The primer sequences are listed in Table S2. 1 μg of total RNA was used for first-strand cDNA synthesis using a PrimeScript™ RT reagent Kit with gDNA Eraser (TaKaRa Dalian, China). Gene expression was measured with a CFX96TM Real-time System (Bio-Rad, Hercules, CA, USA) using the SYBR® Premix Ex Taq™ II (Tli RNase H Plus) (TaKaRa Dalian, China) according to the manufacturers’ instructions. The GAPDH gene and α-tub gene were used as the reference genes. The thermal cycle protocol used for qRT-PCR was: 95 °C for 30 s, then 40 cycles of 95 °C for 5 s, and 60 °C for 30 s. Melting curve analysis was performed by the end of each PCR to confirm the PCR specificity. The relative gene expression was calculated using the 2−ΔΔCt method (Livak and Schmittgen 2001). The results of qRT PCR and DGE are shown as a fold change of gene expression relative to the control sample.

Statistical analyses

Statistical analyses were carried out using the SPSS19.0 software (Chicago, IL, USA). One-way ANOVA and least significant difference (LSD) were used at α = 0.05.

Results

Effect of shading on morphological characteristics, biomass, and RIN and IRN contents of U. rhynchophylla

The daily variation of photosynthetically active radiation (PAR) in different light intensity treatments was characterized first; the results showed that the PAR was significantly higher in the normal light treatment (344–1503 μmol m−2 s−1) compared to the shading treatment (50–296 μmol m−2 s−1) (Fig. S1). The daily variation in photosynthetic parameters of U. rhynchophylla under both conditions was further investigated; the net photosynthetic rate of shade-treated plants decreased compared to plants under normal light conditions (Fig. S1). Chla, Chlb and carotenoid concentrations were significantly higher, and Chla/b significantly lower, in shaded plants compared to plants in normal light conditions (Table S3).

The changes in the growth parameters of U. rhynchophylla under different light intensities were studied after 21 days of shade treatment (Table 1). The results showed that there was no significant difference in canopy width, plant fresh and dry weight, and dry weight of each tissue between shade and normal light conditions. However, shading significantly increased plant height compared to plants under normal light conditions. Conversely, ground diameter and leaf thickness were significantly reduced in shaded plants compared to plants under normal light conditions.

Table 1.

Effect of shade on the growth parameters and biomass of U. rhynchophylla at the end of the experiment

Unshaded plants Shaded plants
Plant height (cm) 79.64 ± 4.59b 87.67 ± 5.94a
Ground diamete r(cm) 11.67 ± 0.66a 9.64 ± 0.55b
Canopy size (cm) 92.30 ± 2.26a 94.50 ± 2.38a
Number of leaves 261.00 ± 22.20a 270.00 ± 27.43a
Leaf length (cm) 11.01 ± 1.36a 11.91 ± 0.68a
Leaf width (cm) 5.27 ± 0.62a 5.44 ± 0.56a
Leaf thickness (μm) 353.00 ± 41.38a 310.00 ± 18.86b
Plant fresh weight (g) 662.98 ± 28.10a 654.05 ± 27.26a
plants dry weight (g) 240.50 ± 11.22a 230.71 ± 9.46a
Roots dry weight (g) 48.52 ± 3.86a 47.71 ± 3.17a
Stem dry weight (g) 93.20 ± 3.91a 87.70 ± 2.43a
Leaves dry weight (g) 98.78 ± 3.58a 95.30 ± 4.20a
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The RIN and IRN contents were determined at six time points. As shown in Fig. 1 and Table S4, on the first and third day of shading, RIN and IRN did not differ significantly from the control. After 7 days of shading, there was a significant increase (P < 0.05) in the contents of RIN (65.7–68.9%) and IRN (55.7–65.2%). Therefore, we concluded that short-term low-light intensity did not alter plant biomass but increased the accumulation of RIN and IRN in U. rhynchophylla leaves.

Fig. 1.

Fig. 1

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RIN (A) and IRN (B) contents in U. rhynchophylla under different light intensity treatments. Significant differences are indicated with one asterisk (P < 0.05). The data are expressed as the mean ± SD

Sequencing and de novo assembly of transcriptome

To obtain a general overview of the transcriptome of U. rhynchophylla under different light intensity treatments, we extracted total RNA from leaves of control and shade-treated plants. Twelve cDNA libraries were constructed and sequenced using Illumina HiSeq 2000 (Table S5). After removing adaptor sequences and low-quality sequences, approximately 341.2 million clean reads were obtained in total. On average, 28.4 million clean reads were obtained per sample. The Q30 ranged from 92.61 to 94.66%, and the average GC content was about 44.60%. Subsequently, clean data from 12 libraries were assembled de novo by the Trinity program to generate 79,817 unigenes with a mean length of 1022.5 bp and the N50 length of 2311 bp (Table 2). Among these unigenes, 36,934 unigenes were longer than 500 bp, accounting for 46.27% of all unigenes. Additionally, 21,821 unigenes were longer than 1000 bp, accounting for 27.34% of all unigenes. This dataset has been deposited at NCBI Short Read Archive (SRA) (accession number: PRJNA691069).

Table 2.

Assembly results of the U. rhynchophylla transcriptome using Trinity software

Unigene length (bp) Number of unigenes Percentage
200–300 24,658 30.89%
300–500 18,225 22.83%
500–1000 15,113 18.93%
1000–2000 9,411 11.79%
2000 +  12,410 15.55%
Total number 79,817
Total length 81,610,810
N50 length 2311
Mean length 1022.47
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Functional annotations and classification of unigenes

After assembly, the unigene's functions were searched against seven public databases, and 36,643 (45.91%) unigenes were functionally annotated (Table 3). Among them, 34,663, 23,217, 13,323, 10,265, 20,131, 23,925, and 22,060 unigenes were annotated in the Nr, Swiss-Prot, KEGG, COG, KOG, GO, and Pfam databases, respectively. Based on the Nr annotation, we determined species homologous to U. rhynchophylla; 54.03% of the unigenes had the highest homology with Coffea canephora, followed by Arabidopsis thaliana, and Olea europaea (Fig. S2).

Table 3.

Functional annotation of U. rhynchophylla unigenes against the public databases

Database Annotated unigenes 300 <  = length < 1000 Length >  = 1000 Percentage (%)
COG 10,265 2268 6110 12.86
GO 23,925 6648 12,157 29.97
KEGG 13,323 3737 6734 16.69
KOG 20,131 5541 10,167 25.22
Pfam 22,060 5612 12,758 27.64
Swissprot 23,217 6451 12,644 29.09
Nr 34,663 10,340 17,019 43.43
All 36,643 11,084 17,116
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The functions of unigenes were predicted via GO database to classify standardized gene functions. 23,925 unigenes were annotated to at least one GO terms, and were divided into three categories and 50 terms (Fig. S3, Table S6). For the “biological process” (BP) category, the term “metabolic process” (12,156) represented the largest cluster, followed by “cellular process” (11,177), “single-organism process” (7641), “biological regulation” (3498), and “response to stimulus” (3133). In the “molecular function” (MF) category, the most enriched terms were “binding” (12,220), “catalytic activity” (11,718), “transporter activity” (1631), “structural molecule activity” (997), and “nucleic acid binding transcription factor activity” (509). As for the “Cellular Component” (CC) category, the enriched terms were “Cell” (10,796), “Cell part” (10,750), “Membrane” (9461), “Organelle” (7794), and “Membrane part” (7381).

In order to further understand the biochemical pathways of unigenes under different light intensities, we mapped unigenes to the KEGG database. 13,323 unigenes were matched to the KEGG database and assigned to 128 KEGG pathways (Table S7). Among them, the largest cluster was “ribosome” (833), followed by “carbon metabolism” (632), “biosynthesis of amino acids” (465), “protein processing in endoplasmic reticulum” (435), and “starch and sucrose metabolism” (331). In addition, 75 and 14 unigenes were mapped to “terpenoid backbone biosynthesis” and “monoterpenoid biosynthesis”, respectively, closely related to the biosynthesis of RIN and IRN.

Analysis of differentially expressed genes

To investigate the effect of shade on U. rhynchophylla gene expression, differential expression analysis was performed between the shade treatment and control at 7 and 21 days. A total of 3959 genes were differentially expressed under shade-treated and the control plants (Table S8). 2391 genes were differentially expressed between CK1 and HS1, of which 1207 were up-regulated and 1184 unigenes were down-regulated. Comparing CK2 and HS2, we observed 2136 differentially expressed genes, of which 1260 and 876 genes were up- and down-regulated, respectively (Fig. 2A). Further comparison of differentially co-expressed genes between 7 and 21 d of shading resulted in the identification of 568 DEGs (Fig. 2B). Among them, 301 and 181 genes were up- and down-regulated, respectively. Considering that the RIN and IRN contents increased under shading, these shared differentially co-expressed genes may play an important role in light-regulated metabolic networks of RIN and IRN.

Fig. 2.

Fig. 2

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Expression patterns of differentially expressed genes. A Number of up- and down-regulated unigenes after 7d (HS1) and 21d (HS2) shading. B Venn diagram of the number of differentially expressed genes in response to shading in U. rhynchophylla

To further analyze the functions of these DEGs, they were mapped to GO terms (Fig. S4) and KEGG pathways (Table S9). In GO analysis, after 7 days of shading, “metabolic process”, “cellular process” and “single-organism process” were the most enriched in the biological process category; the top three in the cellular component category were “cell”, “cell part” and “membrane”, whereas “catalytic activity” and “binding” dominated in the molecular function category (Fig. S4A). The samples shaded for 21 days were compared with control (Figure S4B), and these DEGs were assigned to the relevant functional terms. The results for the biological process and molecular function categories were similar to those of the above comparison after 7 d. However, in the cellular component category, the enriched terms were “membrane” and “membrane part”.

KEGG pathway analysis classified 401 and 300 DEGs in HS1_vs_CK1 and HS2_vs_CK2 comparisons into 104 and 103 KEGG pathways, respectively (Table S9). The top 20 significantly enriched pathways were shown in Fig. 3. The most abundant pathways between CK1 and HS1 included “photosynthesis—antenna proteins” (15 DEGs), “porphyrin and chlorophyll metabolism” (15 DEGs), and “plant hormone signal transduction” (32 DEGs) (Fig. 3A, Table S9A), suggesting that shading affects photosynthesis and hormone signal transduction in U. rhynchophylla. However, different results were observed in the samples shaded for 21 days, in which 36, 27 and 16 unigenes were enriched in “starch and sucrose metabolism”, “plant hormone signal transduction” and “cyanoamino acid metabolism”, respectively (Fig. 3B, Table S9B). In addition, only the “plant hormone signal transduction” pathway was enriched in both groups, and this enrichment declined with duration of the shading treatment.

Fig. 3.

Fig. 3

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Top 20 enriched KEGG pathways. A CK1 vs. HS1, and B CK2 vs. HS2. The Y-axis on the left represents the KEGG pathways, and the X-axis indicates the rich factor. Low q-values are shown in red, and high q-values are depicted in blue

Structural genes involved in RIN and IRN biosynthesis

The schematic diagram of the putative RIN and IRN biosynthesis pathways is shown in Fig. 4A. RIN and IRN are derived from the secoiridoid biosynthesis pathway and shikimate pathway supplying the terpene and indole precursors. The secoiridoid pathway includes four different cytochrome P450 enzymes (geraniol 8-oxidase, G8O; iridoid oxidase, IO; 7-deoxyloganic acid hydroxylase, 7-DLH; secologanin synthase, SLS), two different oxidoreductases (8-hydroxygeraniol oxidoreductase, 8HGO; iridoid synthase, IS), one glucosyltransferase (7-deoxyloganetic acid glucosyltransferase, 7-DLGT) and one methyltransferase (loganic acid methyltransferase, LAMT). Tryptamine is derived from shikimate pathway. In this pathway, the critical roles of AS and TDC have been revealed (Hughes et al. 2004; Pan et al. 2016).

Fig. 4.

Fig. 4

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Expression patterns of unigenes involved in RIN and IRN biosynthesis. A The schematic diagram of the putative RIN and IRN biosynthesis pathways. B Heat map showing the expression profiling of RIN and IRN biosynthesis structural genes. Solid arrows represent one-step reactions; the broken arrow represents multiple reactions. Broken arrows or question marks in red indicate unknown process or enzymes for the reactions. Abbreviations are: GES, geraniol synthase; G8O, geraniol 8-oxidase; 10HGO, 10-hydroxygeraniol dehydrogenase; IS, iridoid synthase; IO, iridoid oxidase; 7-DLGT, 7-deoxyloganetic acid glucosyltransferase; 7-DLH, 7-deoxyloganic acid hydroxylase; LAMT, loganic acid methyltransferase; SLS, secologanin synthase; AS, anthranilate synthase; TDC, tryptophan decarboxylase; STR, strictosidine synthase; SGD, strictosidine β-D-glucosidase

Based on unigenes functional annotation on Swissprot and several other databases, 81 unigenes were annotated as upstream biosynthesis pathway genes of RIN and IRN; they encoded 13 enzyme families including GES, G8O, 8HGO, IS, IO, 7-DLGT, 7-DLH, LAMT, SLS, AS, TDC, STR, and SGD (Table S10). Among them, 11 unigenes including G8O (c49681.graph_c0), IO (c38983.graph_c0), 7-DLGT (c44100.graph_c0), AS (c58994.graph_c1), LAMT (c42611.graph_c0), STR (c36268.graph_c0, c40721.graph_c0, c31592.graph_c0, c43324.graph_c0), and TDC (c19702.graph_c0, c19702.graph_c1) were significantly up-regulated in CK1_vs_HS1 (Fig. 4B). By contrast, 12 unigenes including GES (c54530.graph_c0), G8O (c49681.graph_c0), IO (c38983.graph_c0), 7-DLGT (c44100.graph_c0), 8-HGO (c47303.graph_c0), IS (c39367.graph_c0), LAMT (c42611.graph_c0), SLS (c38601.graph_c1, c38601.graph_c0), STR (c56585.graph_c0, c40721.graph_c0, c47209.graph_c0, c31592.graph_c0, c43324.graph_c0), TDC (c19702.graph_c1), and SGD (c56799.graph_c0) were significantly up-regulated in CK2_vs_HS2 (Fig. 4B). Notably, eight unigenes including G8O (c49681.graph_c0), IO (c38983.graph_c0), 7-DLGT (c44100.graph_c0), LAMT (c42611.graph_c0), TDC (c19702.graph_c1), and STR (c40721.graph_c0, c31592.graph_c0, c43324.graph_c0) were significantly up-regulated in the two comparison groups, and their expression profiles were consistent with the changes in RIN and IRN content during the shading treatment. These genes could be considered as candidate light-responsive genes.

We also analyzed the downstream genes of RIN and IRN biosynthesis, including oxidoreductase, methyltransferase and isomerase (Guo et al. 2014). From the transcriptome data of U. rhynchophylla, 167 unigenes of CYP450, 266 of methyltransferase and 202 of isomerase were annotated (Table S11). DEG analysis showed 40 CYP450s were significantly up- or down-regulated at least in one comparison group, among which four unigenes (c43006.graph_c0, c44141.graph_c1, c50109.graph_c0, c52530.graph_c1) were significantly up-regulated in the two comparison groups (Table S12A). Out of 25 methyltransferase unigenes significantly differentially expressed between the shading treatment and the control, the expression profiles of two unigenes (c37182.graph_c0, c58070.graph_c0) were consistent with RIN and IRN content (Table S12B). The expression of 16 unigenes encoding isomerases had significantly altered during shading, and expression of only one unigene (c38857.graph_c0) matched the changes in RIN and IRN content (Table S12C). The identification of these unigenes provides clues to characterizing the RIN and IRN biosynthesis pathway.

DEGs related to transcription factors

To better explore the mechanism of light-regulated RIN and IRN biosynthesis, it is important to identify the TFs differentially expressed in the two groups of samples. A total of 1065 putative TFs representing 55 TF families were identified when aligning U. rhynchophylla unigenes to the PlantTFDB database (Fig. S5). Among them, 95, 82, 73, 65, and 57 unigenes were annotated to the AP2, bHLH, MYB-related, C2H2, and NAC TF families. However, members of the Alfin-like, S1Fa-like, ULT, VOZ, and zn-clus families had only one unigene. After classifying all TFs, we focused on analyzing the differentially expressed TFs between the control and shade-treated groups. We observed that the expression of 149 TFs was significantly different in different light intensity treatments (Table S13). Among them, 15 TFs were up-regulated and nine were down-regulated between the control and shade treatment groups. The up-regulated TFs were mainly in the bZIP (3), GRAS (3) and C2H2 (2) families, whereas the down-regulated TFs were mainly in the MYB-related (5) and WRKY (2) families. The identification of these TFs provides an opportunity to characterize their role in light-regulated RIN and IRN accumulation.

Expression of genes involved in the perception and transduction of light signals

In the U. rhynchophylla transcriptome data, we annotated eight phytochrome unigenes, six cryptochrom unigenes, 10 phototropin unigenes, and 13 UVR8 unigenes (Table S14). Then, the DEGs between the control and shade-treated groups were analyzed, with one unigene of phytochromes (c54758.graph_c0), three of phototropins (c51401.graph_c2, c47885.graph_c0, c59271.graph_c0), and one of UVR8 (c47984.graph_c0) significantly up- or down-regulated in at least one shading treatment group (Table 4).

Table 4.

Differentially expressed genes associated with light signal perception and transduction

Gene ID CK1_FPKM HS1_FPKM FDR log2FC Up/down CK2_FPKM HS2_FPKM FDR log2FC Up/down
Phytochrome
 c54758.graph_c0 9.09 8.55 0.079508349 0.181743834 Normal 14.1 26.87 1.53E-08 1.03183458 Up
Phototropin
 c51401.graph_c2 7.87 8.88 0.000120423 1.077912745 Up 8.71 6.55 0.379179909 0.337964725 Normal
 c47885.graph_c0 5.42 5.55 0.161758079 0.297768005 Normal 3.81 11.37 3.85E-11 1.581627428 Up
 c59271.graph_c0 1.04 2.75 2.61E-12 1.75621005 Up 1.44 0.77 0.001037304 − 1.133193829 Down
UVR8
 c47984.graph_c0 2.54 0.78 5.10E-07 − 1.324638543 Down 1.5 1 0.251105799 − 0.413479498 Normal
HY5
 c55651.graph_c0 91.66 22.75 2.80E-76 − 1.676322632 Down 61.41 46.47 0.04561751 − 0.272113069 Normal
PIF
 c45661.graph_c1 6.78 11.07 2.26E-22 0.954284341 Normal 10.04 22.08 3.94E-20 1.157339011 Up
 c54619.graph_c0 7.87 6.09 0.3430534 − 0.122027746 Normal 21.27 58.09 7.30E-19 1.532149863 Up
 c49904.graph_c0 9.07 14.96 1.38E-14 0.916788339 Normal 22.99 43.81 3.15E-13 1.018302553 Up
 c44810.graph_c0 1.74 3.56 0.000356603 1.171082161 Up 8.58 6.98 0.687016737 − 0.157383144 Normal
 c49904.graph_c1 5.33 8.13 0.000146728 0.795492985 Normal 10.97 21.55 2.07E-10 1.191524092 Up
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The HY5, belonging to bZIP protein family, is a highly hierarchical regulator of the transcriptional cascades of photomorphogenesis and regulates the expression of nearly one-third of genes in Arabidopsis (Lee et al. 2007). In the transcriptome data in the study presented here, one unigene (c55651.graph_c0) was annotated as HY5 gene that was down-regulated in the two shade-treated groups, but there was significant difference between the shading treatment and control after 7 days (Table 4).

The PIFs belong to the bHLH TF family, which plays an important role in plant growth and development, and also regulates plant secondary metabolism (Shin et al. 2007; Zhang et al. 2019a, b). Thirteen unigenes were annotated as PIFs, of which five unigenes (c45661.graph_c1, c54619.graph_c0, c49904.graph_c0, c44810.graph_c0, c49904.graph_c1) were up-regulated in at least one shading treatment group (Table 4).

Verification of the accuracy of the RNA-Seq data using qRT-PCR

To validate the RNA-seq data, 16 unigenes that were differentially expressed between the shade treatment and the control were subjected to qRT-PCR analysis. These unigenes included one unigene (c19702.graph_c1) belonging to the TDC family, one unigene (c49681.graph_c0) from the G8O family, one unigene (c44100.graph_c0) belonging to the 7-DLGT family, one unigene (c42611.graph_c0) from the LAMT family, one gene (c38983.graph_c0) from the IO family, and three unigenes (c31592.graph_c0, c40721.graph_c0, c43324.graph_c0) belonging to the STR family. Moreover, four unigenes (c44141.graph_c1, c50109.graph_c0, c52530.graph_c1, c43006.graph_c0) belonged to the CYP450 family, two (c55784.graph_c0, c46416.graph_c0) to the MYB TF family, one unigene (c14305.graph_c0) to the C2H2 TF family, and one unigene (c33932.graph_c0) belonged to the WRKY TF family. The expression patterns of the 16 selected genes, detected by qRT-PCR, were similar to those observed in the transcriptomic data in the 7-day shade group (Fig. 5A). In the 21-day shade group, all 16 genes showed the same expression trends obtained by RNA-seq (Fig. 5B). In conclusion, the qRT-PCR results showed that the RNA-Seq data were reliable.

Fig. 5.

Fig. 5

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Real-time PCR results confirmed differentially expressed unigenes identified by RNA-Seq. A HS1 compared to control CK1 and B HS2 compared to control CK2. Data are normalized to GAPDH and α-tub expression and are presented as the mean ± SD (n = 3). *Represents a significant difference (p < 0.05) between the control and shade treatment

Discussion

Light intensity and TIA accumulation

Light is one of the most important environmental factors regulating plant growth and development, and it has also been shown to have important effects on the biosynthesis of secondary metabolites (Cai et al. 2009). In this study, the Chla + b concentration increased signifificantly, while the Chla/b ratio decreased signifificantly under shading conditions. Similar results were observed by Gregoriou et al. (2007). In addition, a signifificant decrease in ground diameter and leaf thickness and signifificant increase of plant height were observed under those conditions. Also, the biomass of U. rhynchophylla was not affected by shading, which might have been due to the short duration of the shading treatment (Ajmi et al. 2018). Research on the effect of light on the content of TIAs has been carried out in some plants (Liu et al. 2015; Yu et al. 2018). However, there is little published information on the relationship between light intensity and accumulation of RIN and IRN in U. rhynchophylla. In the present work, we observed that the content of RIN and IRN in U. rhynchophylla leaves increased after 7 days of shading; the similar observations have been reported in C. acuminata (Hu et al. 2016; Chang et al. 2018). However, light increased the accumulation of TIAs in C. roseus seedlings (Yu et al. 2018). These results imply that there may be multiple mechanisms of light-regulated biosynthesis of TIAs in different plants.

Illumina sequencing of U. rhynchophylla

Traditional Chinese medicine uses U. rhynchophylla to treat for hypertension and central nervous system disorders (Zhang et al. 2015). At present, research on Uncaria mainly focuses on the separation and identification of chemical components and pharmacological efficacy (Guo et al. 2018; Li et al. 2019; Zhang et al. 2019a, b). However, the biosynthesis and regulation of RIN and IRN in U. rhynchophylla have not yet been defined. Therefore, to explain the shade-induced RIN and IRN accumulation in U. rhynchophylla, the transcriptome was analyzed between shade treatments and control. In this study, 12 libraries of U. rhynchophylla leaves from shade treatment and control groups were sequenced, and we obtained 79,817 unigenes with an N50 of 2311 bp, in which 54.09% of the unigenes were not annotated in any databases. This may be due to the lack of genomic information or the genes specific to U. rhynchophylla.

Differential gene expression analysis was performed between the control and shading samples. In this work, DEGs were mainly enriched in KEGG pathways “photosynthesis-antenna proteins”, “plant hormone signal transduction”, “photosynthesis”, “pentose and glucuronate interconversions”, and “starch and sucrose metabolism”. Previous studies on red leaf lettuce have also obtained similar results (Zhang et al. 2018). This suggests that these metabolic pathways may be regulated in response to light. However, the terpenoid skeleton pathway and monoterpenoid pathway related to TIAs biosynthesis were not enriched significantly. The reason may be a lack of sufficient reference data for TIA biosynthesis (Guo et al. 2014).

Genes involved in TIA biosynthesis

Previous studies have shown that shading treatment can increase the expression of CPT biosynthesis genes in C. acuminata seedlings, leading to the accumulation of CPT (Hu et al. 2016). Further studies in C. acuminata reported that four known CPT biosynthesis genes (CaTDC1, CaG8O, CaCYC1, and Ca7DLS) were negatively regulated by light intensity. After 3-day shade treatment, the expression of these genes in leaves increased about 4- to 15-fold compared to the expression under 100% light irradiance (Chang et al. 2018). However, the opposite effect of light induction of TIA genes was observed in C. roseus, with light rapidly activating the expression of key enzyme genes (SLS, STR, D4H, DAT) of the TIA pathway and inducing the accumulation of TIAs (Yu et al. 2018). A recent study also observed that the expression of five vindoline pathway genes, namely T16H2, T3O, T3R, D4H, and DAT, was also induced by light intensity (Liu et al. 2019). Apparently, the mechanisms of light-regulated TIA biosynthesis varied among plants, and one possible explanation was the presence of different types of light-responsive cis-elements in the promoter sequences of the TIA biosynthetic pathway genes, such as TDC (Chang et al. 2018). In the study presented here, we observed all previously reported genes involved in TIA upstream biosynthesis represented in our assembled transcriptome. Twenty-three putative unigenes associated with RIN and IRN biosynthesis were differentially expressed at different durations of shading treatment, and most of these genes were up-regulated. In particular, eight unigenes were up-regulated in after both 7 and 21 days of shading. This partly explained the shade-induced RIN and IRN accumulation in U. rhynchophylla.

Transcription factors involved in TIA biosynthesis

The TFs are widely involved in regulating plant primary and secondary metabolism in response to environmental stimuli and play a key role in coordinating plant growth with environmental changes (Jiang et al. 2016; Liu et al. 2019). Numerous studies have shown that the biosynthesis of TIA was regulated by several TF families such as AP2/ERF (Menke et al. 1999), bHLH (Van Moerkercke et al. 2015), WRKY (Suttipanta et al. 2011), C2H2 zinc fingers (Pauw et al. 2004), MYB-like (Li et al. 2015), and bZIP (Sibéril et al. 2001). In the two shading treatment groups, many TFs were up- or down-regulated; they belonged to TF families WRKY, NAC, MYB-related, bZIP, GRAS, etc. One unigene encoding AP2/ERF TF was up-regulated under shading. Several AP2/ERF family transcription factors (ORCA2/3/4) have been reported to play a key role in regulating TIA biosynthesis (Li et al. 2013; Sun and Peebles 2016; Paul et al. 2017). In C. roseus hairy roots, the overexpression of ORCA2 significantly increased the transcripts levels of many genes (e.g. ASα, TDC, STR, T16H, PRX1, and D4H) in TIA biosynthesis pathway (Li et al. 2013). Interestingly, overexpression of ORCA3 also showed similar results (Van Der Fits and Memelink 2000). In addition, three unigenes encoding bZIP TFs were up-regulated in the shade treatment group. It has been reported that bZIP TFs play an important role in the regulation of TIA biosynthesis (Sibéril et al. 2001). The MYB-related TF family was also involved in the regulation of TIA biosynthesis (Li et al. 2015). In the work presented here, one MYB-related unigene was up-regulated, and five were down-regulated, in the two shade treatment groups.

The WRKY is one of the largest TF families in plants, and is involved in the metabolic regulation, abiotic and biotic stress response and physiological processes (Schluttenhofer and Yuan 2015). In C. roseus hairy roots, the overexpression of CrWRKY1 increased the expression of several key TIA pathway genes (such as TDC, SLS and SGD), but repressed the positive regulators ORCA2, ORCA3 and CrMYC2 (Suttipanta et al. 2011). In the present study, two WRKY TFs were down-regulated in the shade treatment. In summary, shading caused the expression changes in genes of several TF families, suggesting that these TF families may be involved in the regulation of RIN and IRN biosynthesis by light. However, the relationship between these TF families and light signal pathway remains unknown.

HY5 and PIFs are involved in light-induced accumulation of secondary metabolites

The HY5 is a major regulator of seedling development and is involved in nutrient signaling and responses to abiotic (ABA, cold, reactive oxygen species) and biotic stresses (Gangappa and Botto 2016). Furthermore, a lot of evidence show that HY5 is involved in the regulation of plant secondary metabolite synthesis. The HY5 bound directly to the G-box or ACE-box of MYB (such as MYB75/PAP1 and MYB1) to promote their expression and induce anthocyanin synthesis (Shin et al. 2013; Jiang et al. 2016). For Artemisia annua, the yeast one-hybrid and transient expression analysis showed that HY5 bound to the G-box motif in the AaGSW1 promoter, thereby inducing the accumulation of artemisinin (Hao et al. 2019). In C. acuminata, overexpression of CaLMF down-regulated the expression of CPT biosynthetic genes and reduced the accumulation of CPT in leaves (Chang et al. 2018). In the present study, the expression of HY5 was down-regulated in the shade treatment group, which was an opposite change to the content of RIN and IRN under shade conditions. This result implied that HY5 might have a negative regulatory effect on the biosynthesis of RIN and IRN.

The PIFs are core components of regulatory nodes; they integrate a variety of internal and external signals to optimize plant development and are involved in plant-specific processes such as seed germination, hypocotyl negative gravitropism, seedling photomorphogenesis, plant shade avoidance, and leaf senescence (Leivar and Monte 2014; Paik et al. 2017; Jing and Lin 2020). The published study showed that AaPIF3 could activate the promoter of artemisinin biosynthesis genes, including ADS, CYP71AV1, DBR2, and ALDH1, indicating that AaPIF3 had a positive regulatory effect on artemisinin biosynthesis (Zhang et al. 2019a, b). In contrast, CrPIF1 repressed the expression of the CrGATA1 and vindoline pathway genes in C. roseus seedlings in the dark, resulting in reduced vindoline accumulation (Liu et al. 2019). In the present study, the expression of five PIFs was up-regulated in the shading treatment, which was consistent with the changes in RIN and IRN content, suggesting that PIFs may be a transcription factor that positively regulates RIN and IRN biosynthesis.

In fact, HY5 and PIFs did not separately regulate gene expression. In Arabidopsis, HY5 and PIFs directly targeted the common promoter cis-element (G-box) to control the PSY gene expression, forming a dynamic activation-repression transcriptional module in response to light and temperature signals (Toledo-Ortiz et al. 2014). The similar mechanism was also noted in light-regulated MEP pathway genes, where HY5 and PIFs bound directly to the elements of DXS1, DXR and HDR gene promoters and fine-tuned gene expression in response to light (Chenge-Espinosa et al. 2018). However, HY5 and PIFs were not antagonistic to each other in all situations. In Arabidopsis, both PIF3 and HY5 positively regulate anthocyanin biosynthesis by directly binding to different regions of the gene promoter to activate the expression of the same anthocyanin biosynthetic gene (Shin et al. 2007). In the present study, HY5 and PIFs showed the opposite expression patterns in the shade treatment, and their relationship with RIN and IRN biosynthesis still needs further investigation.

Model proposed

Currently, the mechanism of light regulation of RIN and IRN biosynthesis in U. rhynchophylla is unclear. Based on the transcriptome data from this study and the published reports, we propose a model for the involvement of light in RIN and IRN biosynthesis (Fig. 6). In this model, light signals are perceived by photoreceptors through downstream signal transduction pathways to up-regulate the expression of genes related to the RIN and IRN biosynthetic pathways, which ultimately results in the accumulation of these compounds. This model provides a hypothesis for light-regulated RIN and IRN biosynthesis that will be investigated in the future.

Fig. 6.

Fig. 6

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A putative model for the light-regulated RIN and IRN biosynthesis in U. rhynchophylla

Conclusions

In this study, the shade treatment increased accumulation of RIN and IRN in the leaves of U. rhynchophylla. However, its biomass was not affected by shading. Comparative transcriptome analysis revealed that the expression of most unigenes of the upstream biosynthetic pathways of RIN and IRN was up-regulated in the shade treatment, whereas the transcription factors (HY5 and PIFs) involved in the light signaling pathway also showed differential expression with and without shading. This study provides valuable resources for elucidating the regulation of RIN and IRN biosynthesis by light intensity.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOC 32089 KB) (31.3MB, doc)
Supplementary file2 (XLSX 876 KB) (875.9KB, xlsx)
Supplementary file3 (XLSX 59 KB) (59.4KB, xlsx)

Acknowledgements

The authors would like to express their gratitude to EditSprings (https://www.editsprings.cn/) for the expert linguistic services provided.

Funding

This work was supported by the National Key Research and Development Program of China (2016YFC0502604); The Major Special Project of Science and Technology Program in Guizhou (2017–5411-06 and 2018–2797); The Project of High-level Innovative Talents in Guizhou (2015–4031); The Construction Project of Modern Industry Technology system of traditional Chinese Medicinal Materials in Guizhou (GZCYTX-02).

Declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Ajmi A, Vázquez S, Morales F, Chaari A, El-Jendoubi H, Abadía A, Larbi A. Prolonged artificial shade affects morphological, anatomical, biochemical and ecophysiological behavior of young olive trees (cv. Arbosana) Sci Hortic. 2018;241:275–284. [Google Scholar]
  2. Altschul SF, Madden TS, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25(17):3389–3402. doi: 10.1093/nar/25.17.3389. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106. doi: 10.1186/gb-2010-11-10-r106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Asada K, Salim V, Masada-Atsumi S, Edmunds E, Nagatoshi M, Terasaka K, Mizukami H, De Luca V. A 7-deoxyloganetic acid glucosyltransferase contributes a key step in secologanin biosynthesis in madagascar periwinkle. Plant Cell. 2013;25(10):4123–4134. doi: 10.1105/tpc.113.115154. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cai ZQ, Wang WH, Yang J, Cai CT. Growth, photosynthesis and root reserpine concentrations of two Rauvolfia species in response to a light gradient. Ind Crops Prod. 2009;30(2):220–226. [Google Scholar]
  6. Chang CH, Liu ZW, Wang YY, Tang ZH, Yu F. A bZIP transcription factor, CaLMF, mediated light-regulated camptothecin biosynthesis in Camptotheca acuminata. Tree Physiol. 2018;39(3):372–380. doi: 10.1093/treephys/tpy106. [DOI] [PubMed] [Google Scholar]
  7. Chaves I, Pokorny R, Byrdin M, Hoang N, Ritz T, Brettel K, Essen LO, Van Der Horst GTJ, Batschauer A, Ahmad M. The cryptochromes: blue light photoreceptors in plants and animals. Annu Rev Plant Biol. 2011;62:335–364. doi: 10.1146/annurev-arplant-042110-103759. [DOI] [PubMed] [Google Scholar]
  8. Chenge-Espinosa M, Cordoba E, Romero-Guido C, Toledo-Ortiz G, León P. Shedding light on the methylerythritol phosphate (MEP)-pathway: long hypocotyl 5 (HY5)/phytochrome-interacting factors (PIFs) transcription factors modulating key limiting steps. Plant J. 2018;96(4):828–841. doi: 10.1111/tpj.14071. [DOI] [PubMed] [Google Scholar]
  9. Collu G, Unver N, Peltenburg-Looman AMG, van der Heijden R, Verpoorte R, Memelink J. Geraniol 10-hydroxylase1, a cytochrome P450 enzyme involved in terpenoid indole alkaloid biosynthesis. FEBS Lett. 2001;508(2):215–220. doi: 10.1016/s0014-5793(01)03045-9. [DOI] [PubMed] [Google Scholar]
  10. Fraser DP, Hayes S, Franklin KA. Photoreceptor crosstalk in shade avoidance. Curr Opin Plant Biol. 2016;33:1–7. doi: 10.1016/j.pbi.2016.03.008. [DOI] [PubMed] [Google Scholar]
  11. Galvão VC, Fankhauser C. Sensing the light environment in plants: photoreceptors and early signaling steps. Curr Opin Neurobio. 2015;34:46–53. doi: 10.1016/j.conb.2015.01.013. [DOI] [PubMed] [Google Scholar]
  12. Gangappa SN, Botto JF. The multifaceted roles of HY5 in plant growth and development. Mol Plant. 2016;9:1353–1365. doi: 10.1016/j.molp.2016.07.002. [DOI] [PubMed] [Google Scholar]
  13. Geerlings A, Ibanez MML, Memelink J, van der Heijden R, Verpoorte R. Molecular Cloning and analysis of strictosidine β-d-Glucosidase, an enzyme in terpenoid indole alkaloid biosynthesis in Catharanthus roseus. J Biolo Chem. 2000;275(5):3051–3056. doi: 10.1074/jbc.275.5.3051. [DOI] [PubMed] [Google Scholar]
  14. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, Palma FD, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnol. 2011;29:644–652. doi: 10.1038/nbt.1883. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Gregoriou K, Pontikis K, Vemmos S. Effffects of reduced irradiance on leaf morphology, photosynthetic capacity, and fruit yield in olive (Olea europaea L.) Photosynthetica. 2007;45:172–181. doi: 10.1007/s11099-007-0029-x. [DOI] [Google Scholar]
  16. Guo QQ, Ma XJ, Wei SG, Qiu DY, Wilson IW, Wu P, Tang Q, Liu LJ, Dong SK, Zu W. De novo transcriptome sequencing and digital gene expression analysis predict biosynthetic pathway of rhynchophylline and isorhynchophylline from Uncaria rhynchophylla, a non-model plant with potent anti-alzheimer's properties. BMC Genomics. 2014;15(1):676. doi: 10.1186/1471-2164-15-676. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Guo Q, Yang HS, Liu XY, Si XL, Liang H, Tu PF, Zhang QY. New zwitterionic monoterpene indole alkaloids from Uncaria rhynchophylla. Fitoterapia. 2018;127:47–55. doi: 10.1016/j.fitote.2018.01.013. [DOI] [PubMed] [Google Scholar]
  18. Hao XL, Zhong YJ, Nützmann HW, Fu XQ, Yan TX, Shen Q, Chen MH, Ma YA, Zhao JY, Osbourn A, Li L, Tang KX. Light-induced artemisinin biosynthesis is regulated by the bZIP transcription factor AaHY5 in Artemisia annua. Plant Cell Physiol. 2019;60(8):1747–1760. doi: 10.1093/pcp/pcz084. [DOI] [PubMed] [Google Scholar]
  19. He LH, Yang L, Tan RH, Zhao SJ, Hu ZB. Enhancement of vindoline production in suspension culture of the Catharanthus roseus cell line C20hi by light and methyl Jasmonate Elicitation. Anal Sci. 2011;27(12):1243–1248. doi: 10.2116/analsci.27.1243. [DOI] [PubMed] [Google Scholar]
  20. Höft M, Verpoorte R, Beck E. Growth and alkaloid contents in leaves of Tabernaemontana pachysiphon Stapf (Apocynaceae) as influenced by light intensity. Water Nutrient Supply Oecol. 1996;107(2):160–169. doi: 10.1007/BF00327899. [DOI] [PubMed] [Google Scholar]
  21. Hu YY, Yu WW, Song LL, Du XH, Ma XH, Liu Y, Wu JS, Ying YQ. Effects of light on production of camptothecin and expression of key enzyme genes in seedlings of Camptotheca acuminate Decne. Acta Physiol Plant. 2016;38(3):65. [Google Scholar]
  22. Hughes EH, Hong SB, Gibson SI, Shanks JV, San KY. Metabolic engineering of the indole pathway in Catharanthus roseus hairy roots and increased accumulation of tryptamine and serpentine. Metab Eng. 2004;6(4):268–276. doi: 10.1016/j.ymben.2004.03.002. [DOI] [PubMed] [Google Scholar]
  23. Irmler S, Schroder G, St-Pierre B, Crouch NP, Hotze M, Schmidt J, Strack D, Matern U, Schroder J. Indole alkaloid biosynthesis in Catharanthus roseus: new enzyme activities and identification of cytochrome P450 CYP72A1 as secologanin synthase. Plant J. 2000;24(6):797–804. doi: 10.1046/j.1365-313x.2000.00922.x. [DOI] [PubMed] [Google Scholar]
  24. Jenkins GI. Structure and function of the UV-B photoreceptor UVR8. Curr Opin Struct Biol. 2014;29:52–57. doi: 10.1016/j.sbi.2014.09.004. [DOI] [PubMed] [Google Scholar]
  25. Jiang MM, Ren L, Lian HL, Liu Y, Chen HY. Novel insight into the mechanism underlying light-controlled anthocyanin accumulation in eggplant (Solanum melongena L.) Plant Sci. 2016;249:46–58. doi: 10.1016/j.plantsci.2016.04.001. [DOI] [PubMed] [Google Scholar]
  26. Jing Y, Lin RC. Transcriptional regulatory network of the light signaling pathways. New Phytol. 2020;227(3):683–697. doi: 10.1111/nph.16602. [DOI] [PubMed] [Google Scholar]
  27. Kagawa T. The phototropin family as photoreceptors for blue light-induced chloroplast relocation. J Plant Res. 2003;116(1):75–80. doi: 10.1007/s10265-002-0072-4. [DOI] [PubMed] [Google Scholar]
  28. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):R25. doi: 10.1186/gb-2009-10-3-r25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lee J, He K, Stolc V, Lee H, Figueroa P, Gao Y, Tongprasit W, Zhao H, Lee I, Deng XW. Analysis of transcription factor HY5 genomic binding sites revealed its hierarchical role in light regulation of development. Plant Cell. 2007;19(3):731–749. doi: 10.1105/tpc.106.047688. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Leivar P, Monte E. PIFs: systems integrators in plant development. Plant Cell. 2014;26(1):56–78. doi: 10.1105/tpc.113.120857. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinfo. 2011;12:323. doi: 10.1186/1471-2105-12-323. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Li CY, Leopold AL, Sander GW, Shanks JV, Zhao L, Gibson SI. The ORCA2 transcription factor plays a key role in regulation of the terpenoid indole alkaloid pathway. BMC Plant Biol. 2013;13(1):155. doi: 10.1186/1471-2229-13-155. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Li CY, Leopold AL, Sander GW, Shanks JV, Zhao L, Gibson SI. CrBPF1 overexpression alters transcript levels of terpenoid indole alkaloid biosynthetic and regulatory genes. Front Plant Sci. 2015;6:818. doi: 10.3389/fpls.2015.00818. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Li HS, Sun Q, Zhao SJ, Zhang WH (2000) Principles and techniques of plant physiological and biochemical experiments. Higher Education Press, pp134–137.
  35. Liang JH, Luan ZL, Tian XG, Zhao WY, Wang YL, Sun CP, Huo XK, Deng S, Zhang BJ, Zhang ZJ, Ma X. Uncarialins A-I, Monoterpenoid Indole alkaloids from Uncaria rhynchophylla as natural agonists of the 5-HT1A receptor. J Nat Prod. 2019;82(12):3302–3310. doi: 10.1021/acs.jnatprod.9b00532. [DOI] [PubMed] [Google Scholar]
  36. Liu DH, Jin HB, Chen YH, Cui LJ, Ren WW, Gong YF, Tang KX. Terpenoid Indole alkaloids biosynthesis and metabolic engineering in Catharanthus roseus. J Integr Plant Biol. 2007;49(7):961–974. [Google Scholar]
  37. Liu WH, Chen R, Chen M, Zhang HX, Peng MF, Yang CX, Ming XJ, Lan XZ, Liao ZH. Tryptophan decarboxylase plays an important role in ajmalicine biosynthesis in Rauvolfia verticillata. Planta. 2012;236(1):239–250. doi: 10.1007/s00425-012-1608-z. [DOI] [PubMed] [Google Scholar]
  38. Liu YL, Patra B, Pattanaik S, Wang Y, Yuan L. GATA and phytochrome interacting factor transcription factors regulate light-induced vindoline biosynthesis in Catharanthus roseus. Plant Physiol. 2019;180(3):1336–1350. doi: 10.1104/pp.19.00489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Liu Y, Song LL, Yu WW, Hu YY, Ma XH, Wu JS, Ying YQ. Light quality modifies camptothecin production and gene expression of biosynthesis in Camptotheca acuminata Decne seedlings. Ind Crops Prod. 2015;66:137–143. [Google Scholar]
  40. Liu ZJ, Carpenter SB, Constantin RJ. Camptothecin production in Camptotheca acurninata seedlings in response to shading and flooding. Can J Bot. 1997;75:368–373. [Google Scholar]
  41. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCt method. Methods. 2001;25(4):402–408. doi: 10.1006/meth.2001.1262. [DOI] [PubMed] [Google Scholar]
  42. Mao XZ, Cai T, Olyarchuk JG, Wei L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005;21(19):3787–3793. doi: 10.1093/bioinformatics/bti430. [DOI] [PubMed] [Google Scholar]
  43. Menke FLH, Champion A, Kijne JW, Memelink J. A novel jasmonate- and elicitor-responsive element in the periwinkle secondary metabolite biosynthetic gene Str interacts with a jasmonate- and elicitor-inducible AP2-domain transcription factor, ORCA2. EMBO J. 1999;18(16):4455–4463. doi: 10.1093/emboj/18.16.4455. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Miettinen K, Dong L, Navrot N, Schneider T, Burlat V, Pollier J, Woittiez L, van der Krol S, Lugan R, Ilc T, Verpoorte R, Oksman-Caldentey K, Martinoia E, Bouwmeester H, Goossens A, Memelink J, Werck-Reichhart D. The seco-iridoid pathway from Catharanthus roseus. Nature Comm. 2014;5(1):3606–3616. doi: 10.1038/ncomms4606. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Nagatani A. Phytochrome: structural basis for its functions. Curr Opin Plant Biol. 2010;13:565–570. doi: 10.1016/j.pbi.2010.07.002. [DOI] [PubMed] [Google Scholar]
  46. Ndagijimana A, Wang XM, Pan GX, Zhang F, Feng H, Olaleye O. A review on indole alkaloids isolated from Uncaria rhynchophylla and their pharmacological studies. Fitoterapia. 2013;86:35–47. doi: 10.1016/j.fitote.2013.01.018. [DOI] [PubMed] [Google Scholar]
  47. Pacín M, Semmoloni M, Legris M, Finlayson SA, Casal JJ. Convergence of CONSTITUTIVE PHOTOMORPHOGENESIS 1 and PHYTOCHROME INTERACTING FACTOR signalling during shade avoidance. New Phytol. 2016;211(3):967–979. doi: 10.1111/nph.13965. [DOI] [PubMed] [Google Scholar]
  48. Paik I, Kathare PK, Kim JI, Huq E. Expanding roles of PIFs in signal integration from multiple processes. Mol Plant. 2017;10(8):1035–1046. doi: 10.1016/j.molp.2017.07.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Pan QF, Mustafa NR, Tang KX, Choi YH, Verpoorte R. Monoterpenoid indole alkaloids biosynthesis and its regulation in Catharanthus roseus: a literature review from genes to metabolites. Phytochem Rev. 2016;15(2):221–250. [Google Scholar]
  50. Paul P, Singh SK, Patra B, Sui XY, Pattanaik S, Yuan L. A differentially regulated AP2/ERF transcription factor gene cluster acts downstream of a MAP kinase cascade to modulate terpenoid indole alkaloid biosynthesis in Catharanthus roseus. New Phytol. 2017;213(3):1107–1123. doi: 10.1111/nph.14252. [DOI] [PubMed] [Google Scholar]
  51. Pauw B, Hilliou FAO, Martin VS, Chatel G, de Wolf CJF, Champion A, Pré M, van Duijn KJW, van der Fits L, Memelink J. Zinc finger proteins act as transcriptional repressors of alkaloid biosynthesis genes in Catharanthus roseus. J Biol Chem. 2004;279(51):52940–52948. doi: 10.1074/jbc.M404391200. [DOI] [PubMed] [Google Scholar]
  52. Salim V, Yu F, Altarejos J, De Luca V. Virus-induced gene silencing identifies Catharanthus roseus 7-deoxyloganic acid-7-hydroxylase, a step in iridoid and monoterpene indole alkaloid biosynthesis. Plant J. 2013;76(5):754–765. doi: 10.1111/tpj.12330. [DOI] [PubMed] [Google Scholar]
  53. Schluttenhofer C, Yuan L. Regulation of specialized metabolism by WRKY transcription factors. Plant Physiol. 2015;167(2):295–306. doi: 10.1104/pp.114.251769. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Shin DH, Choi M, Kim K, Bang G, Cho M, Choi S, Choi G, Park Y. HY5 regulates anthocyanin biosynthesis by inducing the transcriptional activation of the MYB75/PAP1 transcription factor in Arabidopsis. FEBS Lett. 2013;587(10):1543–1547. doi: 10.1016/j.febslet.2013.03.037. [DOI] [PubMed] [Google Scholar]
  55. Shin J, Park E, Choi G. PIF3 regulates anthocyanin biosynthesis in an HY5-dependent manner with both factors directly binding anthocyanin biosynthetic gene promoters in Arabidopsis. Plant J. 2007;49(6):981–994. doi: 10.1111/j.1365-313X.2006.03021.x. [DOI] [PubMed] [Google Scholar]
  56. Sibéril Y, Benhamron S, Memelink J, Giglioli-Guivarc'H N, Thiersault M, Boisson B, Doireau P, Gantet P. Catharanthus roseus G-box binding factors 1 and 2 act as repressors of strictosidine synthase gene expression in cell cultures. Plant Mol Biol. 2001;45(4):477–488. doi: 10.1023/a:1010650906695. [DOI] [PubMed] [Google Scholar]
  57. Sun JY, Peebles CAM. Engineering overexpression of ORCA3 and strictosidine glucosidase in Catharanthus roseus hairy roots increases alkaloid production. Protoplasma. 2016;253(5):1255–1264. doi: 10.1007/s00709-015-0881-7. [DOI] [PubMed] [Google Scholar]
  58. Suttipanta N, Pattanaik S, Kulshrestha M, Patra B, Singh SK, Yuan L. The transcription factor CrWRKY1 positively regulates the Terpenoid Indole alkaloid biosynthesis in Catharanthus roseus. Plant Physiol. 2011;157(4):2081–2093. doi: 10.1104/pp.111.181834. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Toledo-Ortiz G, Johansson H, Lee KP, Bou-Torrent J, Stewart K, Steel G, Rodriguez-Concepcion M, Halliday KJ. The HY5-PIF regulatory module coordinates light and temperature control of photosynthetic gene transcription. PLoS Genetics. 2014;10(6):e1004416. doi: 10.1371/journal.pgen.1004416. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Van Der Fits L, Memelink J. ORCA3, a jasmonate-responsive transcriptional regulator of plant primary and secondary metabolism. Science. 2000;289:295–297. doi: 10.1126/science.289.5477.295. [DOI] [PubMed] [Google Scholar]
  61. Van Moerkercke A, Steensma P, Schweizer F, Pollier J, Gariboldi I, Payne R, Bossche V, Miettinen K, Espoz J, Purnama PC, Kellner F, Seppänen-Laakso OC, SE, Rischer H, Memelink J, Goossens A, The bHLH transcription factor BIS1 controls the iridoid branch of the monoterpenoid indole alkaloid pathway in Catharanthus roseus. PNAS. 2015;112(26):8130–8135. doi: 10.1073/pnas.1504951112. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Wang X, Zheng M, Liu J, Huang ZF, Bai YD, Ren ZY, Wang ZW, Tian YL, Qiao Z, Liu WY, Feng F. Differences of first-pass effect in the liver and intestine contribute to the stereoselective pharmacokinetics of rhynchophylline and isorhynchophylline epimers in rats. J Ethnopharmacol. 2017;209:175–183. doi: 10.1016/j.jep.2017.07.039. [DOI] [PubMed] [Google Scholar]
  63. Xian YF, Lin ZX, Mao QQ, Hu Z, Zhao M, Che CT, Ip SP. Bioassay-guided isolation of neuroprotective compounds from Uncaria rhynchophylla against beta-amyloid-induced neurotoxicity. Evid Based Complementary Altern Med. 2012;2012:1–8. doi: 10.1155/2012/802625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Yu BF, Liu Y, Pan YJ, Liu J, Wang HZ, Tang ZH. Light enhanced the biosynthesis of terpenoid indole alkaloids to meet the opening of cotyledons in process of photomorphogenesis of Catharanthus roseus. Plant Growth Regul. 2018;84(3):617–626. [Google Scholar]
  65. Yuan D, Ma B, Yang JY, Xie YY, Wang L, Zhang LJ, Kano Y, Wu CF. Anti-inflammatory effects of rhynchophylline and isorhynchophylline in mouse N9 microglial cells and the molecular mechanism. Int Immunopharmacol. 2009;9(13–14):1549–1554. doi: 10.1016/j.intimp.2009.09.010. [DOI] [PubMed] [Google Scholar]
  66. Young MD, Wakefield MJ, Smyth JK, Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11:R14. doi: 10.1186/gb-2010-11-2-r14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Zhang CY, Wu X, Xian YF, Zhu L, Lin G, Lin ZX. Evidence on integrating pharmacokinetics to find truly therapeutic agent for alzheimer's disease: comparative pharmacokinetics and disposition kinetics profiles of stereoisomers Isorhynchophylline and Rhynchophylline in rats. Evid Based Complementary Altern Med. 2019;2019:4016323. doi: 10.1155/2019/4016323. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Zhang QZ, Wu NY, Jian DQ, Jiang RQ, Yang CX, Lan XZ, Chen M, Zhang FY, Liao ZH. Overexpression of AaPIF3 promotes artemisinin production in Artemisia annua. Ind Crops Prod. 2019;138:111476. [Google Scholar]
  69. Zhang Q, Zhao JJ, Xu J, Feng F, Qu W. Medicinal uses, phytochemistry and pharmacology of the genus Uncaria. J Ethnopharmacol. 2015;173:48–80. doi: 10.1016/j.jep.2015.06.011. [DOI] [PubMed] [Google Scholar]
  70. Zhang YZ, Xu SZ, Cheng YW, Peng ZF, Han JM. Transcriptome profiling of anthocyanin-related genes reveals effects of light intensity on anthocyanin biosynthesis in red leaf lettuce. Peer J. 2018;6:e4607. doi: 10.7717/peerj.4607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Zhou F, Sun TH, Zhao L, Pan XW, Lu S. The bZIP transcription factor HY5 interacts with the promoter of the monoterpene synthase gene QH6 in modulating its rhythmic expression. Front Plant Sci. 2015;6:304. doi: 10.3389/fpls.2015.00304. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Zhou JY, Zhou SW. Antihypertensive and neuroprotective activities of rhynchophylline: the role of rhynchophylline in neurotransmission and ion channel activity. J Ethnopharmacol. 2010;132(1):15–27. doi: 10.1016/j.jep.2010.08.041. [DOI] [PubMed] [Google Scholar]

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