Regulation of growth and flavonoids formation of tea plant (Camellia

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Regulation of growth and flavonoids formation of tea plant (Camellia sinensis) by blue and green light Chao Zheng, Jian-Qiang Ma, Chun-Lei Ma, Si-Yan Shen, Yu-Fei Liu, and Liang Chen J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b07050 • Publication Date (Web): 05 Feb 2019 Downloaded from http://pubs.acs.org on February 6, 2019

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Journal of Agricultural and Food Chemistry

Regulation of growth and flavonoids formation of tea plant (Camellia sinensis) by blue and green light Chao Zheng, Jian-Qiang Ma, Chun-Lei Ma, Si-Yan Shen, Yu-Fei Liu, Liang Chen* Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, National Center for Tea Improvement, Tea Research Institute of the Chinese Academy of Agricultural Sciences, Hangzhou, China * Correspondence: Liang Chen, [email protected] Tel: +86 571 86652835, Fax: +86 571 86653866

Chao Zheng: [email protected]; Jian-Qiang Ma: [email protected]; Chun-Lei Ma: [email protected]; Si-Yan Shen: [email protected]; Yu-Fei Liu: [email protected].

1 ACS Paragon Plus Environment


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ABSTRACT

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The eﬀects of blue (BL) and green light (GL) treatment during the dark period were

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examined in Camellia sinensis as a first step to understanding the spectral effects of

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artificial BL and GL on plant secondary metabolism and light signaling interactions. BL

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could induce the expression of CRY2/3, SPAs, HY5, and R2R3-MYBs to promote the

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accumulation of anthocyanins and catechins in tea plants. GL, on the other hand, could

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stimulate the accumulation of several functional substances (e.g., procyanidin B2/B3 and

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L-ascorbate) and temper these BL responses via down-regulation of CRY2/3 and PHOT2.

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Furthermore, the molecular events that triggered by BL and GL signals were partly

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overlapped with abiotic/biotic stress responses. We indicate the possibility of a targeted

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use of BL and GL to regulate the amount of functional metabolites to enhance tea quality

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and taste, and to potentially trigger defense mechanisms of tea plants.

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KEYWORDS: Camellia sinensis, light quality, abiotic and biotic stress, widely targeted

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metabolomics, weighted gene co-expression network


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INTRODUCTION

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Horticulture plants are used for food, fiber, biofuel, medicine, and other products to sustain

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and enhance human life.1-3 Tea plant (Camellia sinensis (L.) O. Kuntze), an evergreen

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woody crop, contains various secondary metabolites (e.g., flavonoids, caffeine, and

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theanine) with potential beneficial effects on human health. Its fresh leaves are processed

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to prepare tea, the most popular non-alcoholic beverage. Being sessile in nature, they need

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to develop plastic response mechanisms to the ever-changing light environment. Shading,

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climatic variation, and daily/seasonal fluctuation of light not only change its quantity

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(intensity) but also its quality (spectral composition). Although both light quality (LQ) and

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quantity are important for plant life, the former is a vital signaling component that

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orchestrates various plant growth and developmental processes such as flowering induction,

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circadian rhythms, phototropism, stem elongation, and seed germination.4 Plants utilize

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diverse sets of photoreceptors to perceive the light of different wavelengths. The

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phytochromes (PHYA-PHYE) mainly respond to far-red (FR) and red (RL) light;

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Ultraviolet-B RESISTANCE 8 (UVR8) is the receptor that responds to UV-B light;

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Phototropins (PHOT1 and PHOT2) and cryptochromes (CRY1, CRY2, and CRY3) are

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blue light (BL) and UV-A receptors.5 To cope with low light stress, providing supplemental

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light-emitting diode (LED) lights at night has been proposed to be an effective method to

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improve plant growth and yield with lower energy cost.6 In addition, LED lights give the

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option of not only precisely controlling light quantity but also quality. However, when

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replacing the broad-spectrum white light with narrow waveband LED lights, an

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understanding of wavelength-dependent plant responses is particularly important to

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enhance or at least maintain plant performance.



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Light is one of the most influential environment cues that affect plant metabolite

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production. Biosynthesis of various secondary metabolites (SMs) such as carotenoids,

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flavonoids, caffeic acid, L-ascorbate, and chicory acid, can be promoted by stimulating

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with a specific monochromatic or polychromatic light.7 In C. sinensis, most studies focus

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on the effects of shading (i.e., light intensity) on the physiology and secondary

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metabolism.8-10 Fu et al., 2015 was the first to investigate the effects of single-wavelength

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BL (470 nm) and RL (660 nm) on the regulation of formation of volatile compounds. They

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found that BL and RL could stimulate the expression of several volatile biosynthesis-

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related genes, e.g., 9/13-lipoxygenases (LOX), phenylalanine ammonialyase (PAL), and

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terpene synthases (TPS), which lead to the accumulation of volatile terpenes,

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phenylpropanoids/benzenoids, and fatty acid derivatives in preharvest tea leaves.11 Many

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SMs are pivotal components utilized during periods of biotic and abiotic stress, as well as

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characteristic constituents to specific colors, tastes, and odors of plants.12-13 For instance,

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anthocyanins are needed for a complete cold acclimation response and could greatly affect

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the main shade of color in the tea infusion and infused leaf.13-14 In Arabidopsis, light

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signaling and low temperature were integrated by HY5, which can induce the expression

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of key enzymes genes (e.g., CHS, CHI, and FLS) in the anthocyanin biosynthetic pathway

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during cold acclimation response.14 Whereas, the crucial relationships between LQ,

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secondary metabolism, and stress tolerance in tea plants remain unearthed.

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By now, a considerable amount of information was obtained on the role of BL and RL on

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plant growth and metabolism. Less studied are the green light (GL) response mechanisms

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and a systematic investigation of BL-GL reversible responses.15 Previously, GL has been

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reported not only to optimize stomatal aperture but also to fine-tune resource-use efficiency


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at canopy level.15-16 These studies indicate that GL, if the right intensity and wavelength of

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light are applied, may significantly improve the yield and quality of crops cultivated in a

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closed growth system, whilst revealing the potential role of GL will improve the

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supplemental LQ in fluctuating light environments such as the field or horticulture facilities.

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Although the nature of GL sensing receptor remains under investigation, it is not surprising

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that GL illumination could result in the inactivation of BL-mediated CRYs response.17 As

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the flavin chromophore of CRYs are photoreduced to a semiquinone form upon excitation

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by BL, which enables CRYs to additionally absorb GL region.18 For example, GL has been

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observed to reverse BL-mediated anthocyanin accumulation and hypocotyl elongation

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inhibition in Arabidopsis.17 In Lolium rigidum, however, the BL-mediated dormancy

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maintenance cannot be reversed by GL.19 The responses to different monochromatic lights

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could be unrelated, neutral, agonistic or antagonistic. The polychromatic light responses

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could be an integration of such responses, which can be more complicated than linearly

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extrapolating those monochromatic responses. Thus, additional work is required if we wish

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to elucidate the full complement of LQ responses by comparing data on monochromatic

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lights with data on corresponding polychromatic lights.

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Taking advantage of RNA-Seq technology and widely targeted metabolomics strategy,

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we investigated the global metabolome and transcriptome of tea plants grown under

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different LQs. By clustering differentially expressed genes (DEGs) from different LQ

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treatments to predefined expression modes, we further analyzed the transcriptional

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response behaviors of tea plants response to individual BL and GL as well as their

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combination. Furthermore, the spectral effects of different LQs on secondary metabolism

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of tea plants were also investigated. Finally, we integrated the previously published RNA-



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seq data to elucidate the potential signaling interactions between LQ and diverse

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environmental factors.

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MATERIALS AND METHODS

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Plant materials and light treatments

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Camellia sinensis (L.) O. Kuntze ‘Zhonghuang 3’ (ZH3) is a newly discovered light-

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sensitive yellow foliar mutant of high made tea quality in China’s Zhejiang province, which

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contains normal polyphenol, caffeine, water extract and a significantly higher content of

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free amino acids. Its bright leaf color and enhanced levels of free amino acids enable this

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yellow foliar mutant to possess a higher economic value than the common green leaf

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cultivars. Thus, we selected this excellent tea germplasm as plant material in the present

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study. Two-year-old tea plants were culture-grown under a 12 h photoperiod with 400 μmol

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m-2 s-1 white LED light irradiation in a growth chamber for 7 d and then subjected to a low-

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light condition (12 h photoperiod with 100 μmol m-2 s-1; white light, WL) for 2 d

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(acclimation) before LQ treatments (Figure 1A). The temperature and humidity in the

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growth chamber were set to 25/20℃ (day/night) and 75%, respectively. The light source

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was on the top of the culture frame, with 30 cm distance from the plants. For LQ treatments,

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tea plants were exposed to low-light (12 h; 100 μmol m-2 s-1; white LED light) during the

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daytime, and provided with 4 h (300 μmol m-2 s-1) supplementary BL (peak at 460 nm),

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GL (peak at 520 nm) or their combination (BG, 150 μmol m-2 s-1 BL + 150 μmol m-2 s-1

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GL) during the middle of dark period for 12 d. The tea plants grown under the low-light

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condition without nighttime supplemental LED lights were used as a control (CK) (Figure


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1A). The photosynthetic rate of third leaves (i.e., mature green leaves with normal

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chlorophyll contents) for each treatment group (five replicates) was measured before

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sampling using a portable photosynthesis system (Li-6400; Li-Cor, Lincoln, NE, USA).

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Leaf tissues (comprised two top leaves and a bud) from 96 individuals at the same

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developmental stage were collected for transcriptomics (four treatments * three biological

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replications * three individuals for each replicate) and metabolomics (four treatments *

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three biological replications * five individuals for each replicate) studies.

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RNA-Seq and data processing

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The total RNA was isolated using the RNeasy plant mini kit (Tiangen Bio, Beijing, China).

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A minimum of 1.5 μg of total RNA per sample was sent to the Novogene (Novogene,

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Beijing, China), where library preparation and sequencing were conducted. The cDNA

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libraries were sequenced on an Illumina HiSeq 4000 platform (Illumina, San Diego, CA,

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USA) to generate 150 bp paired-end reads. The raw reads of the current study have been

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submitted to the BIGD (BIG Data Center, http://bigd.big.ac.cn/) under accession number

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PRJCA001034. The published RNA-Seq data used in our study were downloaded from the

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NCBI SRA database (http://www.ncbi.nlm.nih.gov/sra) under the accession number

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PRJNA347510 and PRJNA306068. The first experiment profiled the transcriptome of tea

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leaves subjected to cold (CT) and drought (DT), as well as a combination of cold and

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drought stress (CD).20 The second experiment surveyed the blister blight (BB) interaction

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induced transcriptomic responses with resistant and susceptible tea genotypes at four

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different stages.21 All datasets were uniformly processed using the same bioinformatics

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pipeline. First, adapters and low-quality reads were trimmed and filtered using



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Trimmomatic (v0.36).22 Trinity (v2.5.1) was used to assemble the high-quality reads from

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three datasets into transcripts independently.23 De novo assemblies were used as inputs to

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Lace (v1.00) to construct a superTranscript.24 The superTranscripts generated from three

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datasets were then combined into a non-redundant reference transcriptome using the

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EvidentialGene pipeline.25 Transcript expression quantification (TMM normalization

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method) and differential gene expression (adjusted P-value < 0.05) analysis were achieved

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using the Salmon program (v0.9.0)26 and DESeq2 R package (v1.10.1),27 respectively.

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Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO)

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enrichment analysis of the differentially expressed genes (DEGs) was implemented by

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using the KOBAS software (v2.0)28 and the GOseq R packages (v1.32.0),29 respectively.

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Gene Network Construction and Visualization

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Weighted gene co-expression network analysis (WGCNA) was performed using the

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WGCNA R package (v1.63).30 A total of 106,004 genes (i.e., the top 75% most varying

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transcripts selected by a robust co-variation estimator relative median absolute deviation

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(MAD)) were used as input to construct the weighted network. Network construction and

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module detection were implemented by 'blockwiseModules' function with default settings,

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except that 'soft thresholding power' is 7; 'mergeCutHeight' is 0.25; and 'minModuleSize'

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is 30. The module eigengene values were calculated to define intra-modular connectivity

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and gene significance, as well as to test the association with each treatment. The module

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networks were visualized using Cytoscape (v3.4.0).31


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Quantitative real-time PCR (qRT-PCR) validation for DEGs

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qRT-PCR was performed using SYBR Premix Ex Taq II kit (Takara) and reactions were

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run on a LightCycler 480 Real-Time PCR instrument (Roche Applied Science) with the

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following parameters: 95°C for 30 s, 40 cycles at 95°C for 5 s, 60°C for 30 s. Biological

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triplicate samples were used and GAPDH was used as endogenous control. CT values

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obtained through qRT-PCR were analyzed using the 2−ΔΔCT method to calculate relative

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fold change values.32 Primers used are shown in Table S1.

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Metabolite profiling

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The freeze-dried leaf sample was crushed using a mixer mill (MM 400, Retsch) for 1.5 min

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at 30 Hz before extraction, 100 mg dried powder was extracted with 1.0 ml pure methanol

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spiked with 0.1 mg/L lidocaine (internal standard). The sample extracts were then injected

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into the LC-ESI-MS/MS system (HPLC, Shim-pack UFLC SHIMADZU CBM20A system;

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MS, Applied Biosystems 4000 Q-TRAP). Quantification of metabolites was carried out by

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using a large-scale multiple reaction monitoring (MRM) mode.33 Of the 671 metabolites

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detected in tea leaves, 263 were putatively annotated and 408 were identified by using

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authentic standards. These metabolites included nucleic acids and their derivatives, amino

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acids and their derivatives, fatty acids, and flavonoids. To describe co-variation patterns

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among different LQ treatments in a more systematic manner, we constructed a

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metabolomic co-variance network based on Pearson correlation coefficient (PCC > 0.90)

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using the complete dataset of metabolic features. Biochemical substrate-product



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relationship and MAD scores were mapped onto this network to evaluate the varying

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degrees of SMs existing among biochemically related metabolites.

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RESULTS

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Impact of different light qualities on phenotype and photosynthesis of the tea plant

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The yellowish new shoots and enhanced levels of free amino acids enable ZH3 to possess

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a higher economic value than the common green leaf cultivars. After 12 d LQ treatments,

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comparatively similar phenotypes were observed among BL, GL, and BG (Figure 1B and

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S1). The new shoots of tea plants provided with supplemental lights exhibited the chlorina

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phenotype while maintaining normal growth status (Figure 1B and S1). In contrast, a

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wilting phenotype with reduced leaf area was observed in the new shoots of CK (Figure

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1B and S1). Although the new shoots of ZH3 turned green in CK, it displays a lower

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photosynthetic capacity when light intensity was over 400 μmol m-2 s-1 (Figure 1C). Our

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results showed that additional nighttime LED light has a positive effect on the growth and

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induction of yellowish new shoots of ZH3 under low-light conditions.

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Optimizing transcriptome assemblies by combining multiple assemblies

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To reveal the molecular events of tea plants grown under different LQs, RNA-Seq libraries

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for BL, GL, BG, and CK were prepared, and then paired-end sequenced, each with three

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biological replicates. After trimming adaptor sequences and filtering low-quality reads,

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clean data ranging from 6.51 to 8.28 Gb were generated for each sample. A total of 573.4

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million high-quality reads were subject to de novo assembly using Trinity software and

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produced 496,537 transcripts, and 214,068 unigenes with an N50 of 1,440 bp and 1,010


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bp, respectively (Table S2). In order to optimize transcriptome assemblies for C. sinensis

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leaf and construct a common reference for WGCNA analysis, we additionally analyzed

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two recently published RNA-Seq datasets. By Lace and EvidentialGene pipeline, we

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successfully recovered more complete genes with a longer N50 (1,728) and mean length

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(986) while maintaining the assembly quality (90.7% of the complete BUSCOs) even for

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more complex transcriptome datasets consisting of three cultivars (Table S2).

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Identification and clustering analysis of DEGs under different light qualities

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To investigate the molecular differences of tea plants grown under diverse LQ conditions,

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the DESeq2 R package was used to determine DEGs from CK and each LQ treatment.27

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There was a similar number of DEGs in BL (3,223) and GL (3,063), while the DEGs in

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BG (2,548) was far fewer (Figure 2A). By calculating the cumulative log-fold changes of

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top 1000 BL- and GL-responding genes in BG, respectively. BL (847) were found to

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possess a higher impact on tea plants when illuminated simultaneously with GL (568). We

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also identified a great number of GL-unique responsive genes (1,525, 47.3%), which were

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not modulated by BL or BG. Furthermore, only 783 genes (13.4%) were commonly

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regulated by all the three LQ treatments, and only 1,789 of genes (30.6%) that activated by

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either BL or GL were also responding to BG. As shown in Venn diagrams, most of the

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genes (3,960, 67.7%) were up-regulated after providing with additional LED lights (Figure

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2B, C). Among the 3,522 genes that are up-regulated by either BL or GL, only 1,211

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(34.4%) are also induced by BG (Figure 2B). Similarly, among the 1,576 genes that are

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down-regulated by BL or GL, only 568 (36.0%) are also repressed by BG (Figure 2C).



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Higher plant PHOTs and CRYs control how plants modulate growth and development in

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response to BL changes.5 Although GL-specific sensor has not yet been identified, GL

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could affect plant processes via CRY-dependent pathways.15 In the current study, BL

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elevated the expression level of CRY2 and PHOT2, but GL decreased the expression level

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of PHOT2 (Figure 2D). Both BL and BG repressed the expression level of PHOT1 and

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induce the expression level of CRY3. PIF3 that acts downstream to CRYs was significantly

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repressed by BL and BG, while slightly induction was observed in GL. Constitutively

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photomorphogenic 1 (COP1)/Suppressor of phyA-105 (SPA) complex is a well-

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characterized negative regulator of photomorphogenesis that functions as an E3 ubiquitin

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ligase to target activators (e.g., HY5, HFR1, and MYBs) of the light response for

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degradation.34 SPAs were significantly induced by BL, while all LQ treatments increased

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the expression level of COP1. Other important modulators of light signal coordination,

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such as HY5 and several R2R3-MYBs (e.g., MYB12, MYB44, C1, and TT2) were either

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significantly repressed in GL or induced in BL and BG. In addition, COP10, encode

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another negative regulator of photomorphogenesis, were found to be repressed by BL

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(Figure 2D).35 Gene expression pattern of several key light-responsive regulators (e.g., HY5,

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COP1, CRY2, PHOT2, DREB1A, and PIF3) were further validated by qRT-PCR analysis

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(Figure S2).

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The responses of a given gene to BL and GL could be neutral, agonistic, antagonistic or

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unrelated. Therefore, simply adding together two light responses is seldom the true

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response, and the required BG response could be unique or a combination of such responses.

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To examine these responses, we clustered the DEGs from BL, GL, and BG to 20 predefined

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expression modes (EP1-20, Expression pattern 1-20) as described by our previous study


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(Figure 3A).20 Interestingly, half (50%) of the DEGs shown a “canceled” (genes response

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to either BL or GL returned to control levels in BG) modes, followed by “combinatorial”

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(20%; similar transcriptional response in BL and GL but a different response to BG),

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“independent” (16%; response to only BL or GL and a similar response to BG), “similar”

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(13%; similar responses to BL, GL, and BG), and “prioritized” (0%; opposing responses

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to the BL and GL, and one LQ response prioritized in BG). Notably, the expressing patterns

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of 70% genes in BG, which responded in the “canceled”, “combinatorial” and “prioritized”

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modes, cannot be inferred from the BL or GL studies alone. The accuracy of profiles and

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assignments was verified by qRT-PCR (Figure S2).

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The BG-specific DEGs (EP1, “combination” mode) were mainly involved in biotic and

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abiotic stress response (response to virus, bacterium, cold, water deprivation, hydrogen

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peroxide, and phytoalexin biosynthetic process, e.g., ZAT10, RBCS1A, CRPK1, TIL, VTC2,

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FBS1, WRKY33, MPK1, PTI5, RAV1, and PR1B1), hormone signaling (response to

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abscisic acid (ABA), jasmonate (JA), cytokinin, and salicylic acid (SA), e.g., WAK2,

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GRXC9, GATA22, and MYC2), as well as growth regulation processes (regulation of cell

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size, gene expression, macromolecule, flavonoid and nucleobase-containing compound

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biosynthetic process, e.g., NAC036, ASF1B, SPT16, MYB3, WRKY41, and TPX2) (Figure

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3B and Table S3).

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The GL-specific induced DEGs (EP5, “canceled” mode) were primary implicated in

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signaling (phosphorylation, e.g., CEPR1/2, MAPKKK18, and PPCK1; ion homeostasis and

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transport, e.g., CAT1, NHX2, and CAX3), developmental processes (cellular

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macromolecular complex assembly, protein metabolic and secondary cell wall biogenesis,

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e.g., NAC073, HD1, and CEPR1; response to ethylene (ET), cytokinin, and auxin, e.g.,



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PTI6, ERF5, and SAUR36), regulation of shade avoidance (e.g., BBX24/STO, HAT4, BIM2,

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and PIF3), control of water loss (response to ABA, osmotic stress, e.g., PYL8/9, SDIR1,

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and PLD1), and biotic stress response (response to bacterium, e.g., CAD, OCP3, NRP1,

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and SDF2) (Figure 3C and Table S3).

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The BL-specific induced DEGs (EP7, “canceled” mode) were mainly involved in

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photomorphogenesis (response to radiation, photoperiodism, blue, red or far-red light, e.g.,

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CRY2, PHOT2, ADO1, SPA1/2/3/4, CCA1, and LHY), chloroplast development

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(chloroplast organization, plastid fission, thylakoid membrane organization; e.g., atpI,

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SGRL, MSL2, and PMI2), phosphorylation (e.g., PEPR1, MPK16, and CPK11),

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polysaccharide (e.g., G6PD1, TPS7, and BAM3), and nitrate metabolic process (e.g., GLN1

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and NRT1.2/1.7) (Figure 3D and Table S3).

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Unsurprisingly, providing supplemental BL and GL either alone or together elicited a

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"similar" (EP19) set of genes that involved in light response (response to blue light, red or

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far-red light, and light intensity, e.g., GI, HOP3, HY5 and COP1), ROS and hormone

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signaling (response to hydrogen peroxide, cell redox homeostasis, response to SA and JA,

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e.g., LOX2.1, GI, CAT3, GA2OX1/8, SQE3), photosynthesis (photosynthesis, light

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harvesting in photosystem I/II, chloroplast organization, e.g., FTSH1/2, PAO, NYC1, PPH,

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LHCA3/A4/B5, and CAB13/37), secondary metabolism (phenylpropanoid biosynthetic

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process, e.g., UFGT, CYP75B2, DFR, and ANR) and response to starvation and nutrient

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(e.g., BAM1/3/9, UGT73D1, ZIP4, SULTR1, and STP5). In addition, chlorophyll

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degradation related genes, (e.g., FTSH1/2, PAO, NYC1, and PPH) and carotenoid

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biosynthesis related genes (e.g., CRTISO and PDS) were observed to be up-regulated by


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all LQ treatments, which may lead to the chlorina phenotype of ZH3 (Figure 3E and Table

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S3).

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Gene co-expression network analysis

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Another goal of this study was to investigate and functionally describe the potential

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signaling interactions of different LQs with other environmental cues in tea plants. By

283

WGCNA analysis, we identified 25 distinct co-expression modules shown by the

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dendrogram (Figure 4A, B). Of particular interest is the identification of a BL-responsive

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module (M7, antiquewhite2, 706 genes) and a GL-responsive module (M17, orangered;

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150 genes) that were also significantly (P-value < 0.05) induced by CT and BB,

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respectively (Figure 4B, C, D).

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The Gene Ontology (GO) enrichment analysis of M7 also reflected the associations

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between two independent abiotic environmental factors, BL and CT (photosynthesis,

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response to radiation, and response to temperature stimulus) (Figure 5A). The presence of

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some prior reported BL- and CT-responsive regulators such as HOS1, CBF3/DREB1A,

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PIF3, and PHOT2 clearly indicates this module in response to BL and CT (Figure 5B and

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Table S4).36-39 Other highly connected genes inside the module, such as VTE1, ANL2, and

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ANN5, have also been functionally linked to both light and cold stimulus responses (Figure

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5B and Table S4).40-41

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GO enrichment analysis for M17 showed significantly enriched terms associated with

297

phenylpropanoid biosynthetic, organic acid and anion transport, carbohydrate and lignan

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metabolic, xylem and cell wall development (Figure 5C). Some highly connected genes,

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such as Light-dependent short hypocotyls-like protein (LSH4) and Glutamine dumper 3



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(GDU3) in this module have been functionally associated with the responses to light and

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pathogen infection (Figure 5D and Table S4).42 This module included 15 and seven

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annotated TFs and protein kinases (PKs), respectively. Some of these TFs with higher

303

intramodular connectivity has been involved in defense and developmental processes,

304

which are regulated by phytohormones, such as gibberellin (GA), ABA, JA, and SA

305

(Figure 5D and Table S4).39,

306

like/Pelle kinases (RLK/Pelles) superfamily, including LRR (e.g., NIK2, BRL2, PXC1,

307

and TDR) and RLCK (e.g., At5g18500, and PIX7) subfamilies, and most of them in the

308

M17 have also been implicated in defense functions.44

309

Metabolites co-variance network analysis

310

To explore the potential effect of different LQs on the secondary metabolism of tea plant

311

under the low-light condition, we employed a widely targeted metabolomics strategy to

312

quantify their metabolites.33 Among the 671 metabolic features determined in the tea leaves

313

under different LQs, 289 metabolites showed a co-variance pattern (PCC > 0.90) and 54

314

of these metabolites had observed relative higher MAD score > 0.1 (Figure 6A and Table

315

S5). We then examined the metabolite classes of these 54 metabolites and found that most

316

of them belonged to flavonoids, including anthocyanins, flavones, flavonols, flavanones,

317

catechins, and proanthocyanidins. Within the flavonoid biosynthesis pathway, most of the

318

key enzymatic genes, including 4CL, CHS, PAL, C4H, CHI, F3H, F3 ′ H, F3 ′ ,5 ′ H, ANS,

319

ANR, FLS, DFR, LAR, FGS, LDOX, and UFGT, were significantly induced after supplying

320

BL (Figure 6B). When GL was simultaneously illuminated with BL, however, the

43

All the PKs in the M17 were belonging to Receptor-


Page 17 of 40


321

expression level of several key enzymatic genes (e.g., F3H, F3′,5′H, CHS, and CHI) among

322

the pathway decreased. On the other hand, phenylalanine exhibited a relatively low

323

variation level and decreased with all LQ treatments. In clear contrast, gradual increases in

324

variations and accumulation levels were observed for the downstream metabolites of the

325

pathway. Highest MAD scores were seen for the catechins and procyanidins located most

326

downstream steps in the pathway. In contrast to phenylalanine, the production level of

327

anthocyanins (cyanidin 3,5-O-diglucoside), procyanidins (procyanidin B2/B3) and

328

catechins (catechin (C), gallocatechin (GC), epigallocatechin (EGC), epicatechin gallate

329

(ECG), epigallate catechin gallate (EGCG), and gallocatechin-gallocatechin (GC-GC))

330

levels were increased with LQ treatments, and most of them displayed a higher

331

accumulation level in BL than GL/BG (Figure 6B). In addition, the accumulation levels of

332

some important functional substances, such as L-ascorbate and SA were observed to be

333

significantly induced by GL (P-value < 0.01), while several benzoic acids and their

334

derivatives (e.g., 2,5-dihydroxy benzoic acid O-hexside and gallic acid O-hexoside were

335

significantly induced by all LQ treatments (Figure S3).

336

DISCUSSION

337

This study was designed to investigate the potential of a targeted use of BL and GL to

338

shape plant growth and secondary metabolism under the low-light condition, and we also

339

discuss the potential signaling interactions between LQ and other environmental stress

340

responses. We initially compared the transcriptomic profiles of tea leaves under BL and

341

GL with BG (Figure 2). Subsequently, we investigated the transcriptional response

342

behaviors of BG by clustering DEGs from the BL, GL, and BG to predefined expression



Page 18 of 40

343

modes (Figure 3A). We revealed that supplemented with diverse LQs provokes altogether

344

different transcriptome responses in tea plants. Only 11.4% (783) of DEGs were

345

overlapped in all LQ treatments, and only 13% of DEGs shared “similar” response mode

346

(Figure 2A and Figure 3A). Consistent with previous studies, GL tends to temper the

347

effects of BL in tea plants.17, 45-46 Only 30.6% (1,789) of genes that were activated by either

348

BL or GL were also responsive to BG, and half (50%) of all the DEGs which were induced

349

by BL or GL were “canceled” when radiating with BG (Figure 2A and Figure 3A). Notably,

350

the “combinatorial”, “prioritized”, and “canceled” modes comprise 70% of the total DEGs,

351

whose expression patterns cannot be speculated from BL or GL studies alone (Figure 3A).

352

This indicated that tea plant responses to polychromatic light are orchestrated by complex

353

signaling pathway cross-talk, which cannot be inferred from corresponding

354

monochromatic light studies.

355

Being photosynthetic organisms, plants utilize light energy for photosynthesis and percept

356

it as a signal to adjust their growth and development. In this study, supplemental nighttime

357

BL, GL, and BG can effectively improve tea plant growth and photosynthetic capacity

358

under low-light condition (Figure 1). The "similar" responses elicited by different LQ

359

treatments were mainly involved in light stimulus response (response to blue light, red or

360

far-red light, and light intensity) and may trigger ROS and hormone signaling (response to

361

hydrogen peroxide, cell redox homeostasis, response to SA and JA) to fine-tuning

362

photosynthesis (photosynthesis, light harvesting in photosystem I/II, chloroplast

363

organization), secondary metabolism (phenylpropanoid biosynthetic process), and

364

improving plant leaf nutrient status (response to starvation and nutrient) under low-light

365

condition (Figure 3E). Moreover, supplementary LED lighting stimulated the expression


Page 19 of 40


366

of chlorophyll degradation (e.g., FTSH1/2, PAO, NYC1, and PPH) and carotenoid

367

biosynthesis related genes (e.g., CRTISO and PDS), which may lead to the chlorina

368

phenotype of ZH3 (Table S3). However, the new shoot of ZH3 could revert to green under

369

shade or low-light conditions (Figure 1A). Insufficient light may hamper plant growth and

370

development, and thus, the increased chlorophyll content may be a shade tolerance strategy

371

employed by ZH3 to improve photosynthesis under low-light conditions. Excess light, on

372

the other hand, beyond the photosynthetic capacity might cause cell death and oxidative

373

damage to the newly emerged shoots. We speculate that it is a common strategy employed

374

by light-sensitive albino tea plant mutants, such as ‘Baijiguan’ and ‘Huangjinya’, to

375

tolerate and survive under a wide range of light regimes.47-48

376

A shaded environment is enriched with GL, and up to 80% of all the GL is thought to be

377

transmitted through or scattered by plant chloroplast.15 These properties of GL might lead

378

to a misconception that plants do not make use of the GL. However, GL of high intensity

379

(300 μmol m-2 s-1) did not limit photosynthesis capacity but actively regulates tea plant

380

growth under low-light condition (Figure 1). Moreover, GL was proposed to acts as a vital

381

signal for short-term dynamic and long-term developmental acclimation to the

382

environment and regulates many crucial processes (e.g., stomata movement and pathogen

383

resistance).46 In our study, GL may function as a shade signal to fine-tune signalling

384

(phosphorylation, ion homeostasis and transport), control water loss (response to abscisic

385

acid, osmotic stress), and permit a dynamic and developmental acclimation (cellular

386

macromolecular complex assembly, protein metabolic and secondary cell wall biogenesis)

387

to low light (regulation of shade avoidance) and potential biotic stress (response to

388

bacterium) (Figure 3C). In addition, supplementary GL could significantly elevate the level



Page 20 of 40

389

of several functional substances, such as SA, L-ascorbate, procyanidin B2/B3, and benzoic

390

acid derivatives (Figure 6, S2). These SMs are commonly known in the context of plant

391

defense and stress responses. For example, procyanidins have been identified as a feeding

392

deterrent for herbivorous insects.49 Benzoic acid and their derivatives are known as

393

widespread and vital mediators of plant responses to abiotic and biotic stress.49 SA is the

394

predominant phytohormone regulating responses to pathogens.50 In a similar study, the

395

increase of SA level by GL exposure during the dark period has been identified as a CRY2-

396

dependent response.51 If the GL illumination is effective for disease or pest control, it is

397

attractive in greenhouse or plant factories as an economically feasible and environmentally

398

friendly strategy to reduce the usage of agricultural chemicals. Hence, we further tested the

399

potential signaling interaction of GL with biotic stresses by WGCNA, and we identified a

400

gene co-expression module (M17) that showed a significant association with BB and with

401

GL (Figure 4B, D). These overlapped co-expression genes were primarily implicated in

402

several important plant defense processes, such as phenylpropanoid biosynthetic, organic

403

acid and anion transport, carbohydrate and lignan metabolic, xylem and cell wall

404

development. (Figure 5C). Intrigued by such precise regulation of plant defense responses

405

triggered by GL signal, we investigate the TFs and PKs with a high intramodular

406

connectivity to reveal the underlying regulatory mechanisms under these conditions

407

(Figure 5D and Table S4). Most of these TFs (e.g., DAG1 and WRKY39) were involved

408

in defense and phytohormones signaling (e.g., GA, ABA, and SA), which coordinate

409

various developmental processes and immune responses.39, 43, 52 RLK/Pelles are a group of

410

highly conserved signaling components that involved in biotic stress perception and

411

development regulation.44 All the PKs in the M17 were belonging to RLK/Pelles (e.g.,


Page 21 of 40


412

NIK2, BRL2, PXC1, TDR, TDR, At5g18500, and PIX7) (Table S4). Most of these

413

RLK/Pelles can be rapidly induced in Arabidopsis after infection by pathogen infection or

414

treatment with SA, which may represent a specific adaptation mechanism to detect and

415

respond to both GL stimuli and defense signals.44 Collectively, our results revealed that

416

high-intensity GL not only improves photosynthesis but contributes to the accumulation of

417

several functional substances (e.g., SA, procyanidin B2/B3, and L-ascorbate) under low-

418

light conditions, and that CRY2/3-dependent and SA-mediated defense responses may be

419

partly involved in the effect of GL on plants.

420

In field conditions, both the absolute and the relative amounts of BL to other LQs vary

421

widely, which could carry out abundant environmental information to the plant.17, 19, 53 In

422

the current study, high-intensity BL triggered a more profound effect on

423

photomorphogenesis (response to radiation, photoperiodism, blue, red or far-red light),

424

chloroplast development (chloroplast organization, plastid fission, thylakoid membrane

425

organization), phosphorylation, polysaccharide, and nitrate metabolic process (Figure 3D),

426

which may release tea plants from the threat of low-light conditions (Figure 1). BL has

427

long been known to promote the accumulation of anthocyanin in a fluence-rate dependent

428

manner.53 In our study, most of the key enzymatic genes involved in flavonoid biosynthesis

429

pathway were significantly induced and resulted in a higher accumulation level of

430

anthocyanins (cyanidin 3,5-O-diglucoside) and catechins (C, GC, EGC, ECG, and EGCG)

431

in BL (Figure 6B). When GL is simultaneously delivered with BL, however, the expression

432

level of several key structural genes (e.g., F3H, F3 ′ ,5 ′ H, CHS, and CHI) among the

433

flavonoid biosynthesis pathway decreased. Accordingly, the accumulation levels of



Page 22 of 40

434

anthocyanin and catechins in GL and BG are lower than BL treatment alone (Figure 6B).

435

This revealed a GL paradox-as intensity of GL increases, the magnitude of the BL-driven

436

response decreases. We then closely examined this response and indicated that it is a BL

437

photoreceptors-dependent light response. The expression level of PHOT2 was induced by

438

BL, while it was observed to be repressed by GL (Figure 2D). In a previous report, only

439

PHOT2 was identified as the photoreceptor that contributes to the anthocyanin biosynthesis

440

in strawberry fruits.38 Thus, PHOT2 may play a specific role in sensing BL, and mediating

441

anthocyanin biosynthesis under high-intensity BL in tea plants. However, both BL and BG

442

repressed the transcriptional levels of PHOT1 (Figure 2D). PHOT1 is mainly involved in

443

photo-movement responses such as chloroplast relocation and phototropism.5 This allowed

444

us to speculate that CRYs may act antagonistically to PHOT1 at high light intensity, and

445

thus the BL sensing system can lower its responsivity to light when photomovement

446

responses are less important to plant growth and development. CRYs play a pivotal role in

447

regulating plant development and photomorphogenesis.5 It has been demonstrated that

448

CRYs regulate gene expression in response to BL via suppressing the activity of E3

449

ubiquitin ligase COP1.54 Moreover, the CRY2-COP1 interaction can be further enhanced

450

by BL-dependent CRY2-SPA1 interaction.54 COP1 acts as a negative regulator of

451

photomorphogenesis that mediates degradation of various TFs, such as HY5 and MYBs

452

involved in light signaling.55 In addition, these light-dependent TFs have also been known

453

to positively regulate enzymatic genes required for the production of benzenoids,

454

flavonoids, and phenylpropanoids.56-57 In the current study, COP1 was observed to be

455

induced by all LQ treatments, which might result in the suppression of flavonoids

456

biosynthesis pathway (Figure 2D). Recently, however, COP1 has been observed to reverse


Page 23 of 40


457

its repressive role and promotes photomorphogenesis under photomorphogenic UV-B

458

light.58 Thus, COP1 may participate in BL induced flavonoids biosynthesis in a different

459

way, however, the mechanism by which COP1 is functionally switched is remained to be

460

elucidated. Furthermore, the suppressing activity of COP1 might be blocked by the BL-

461

induced CRY2 and SPA1, as well as the BL/BG induced CRY3 (Figure 2D). Moreover,

462

BL down-regulated another negative regulator of photomorphogenesis, COP10, which has

463

been implicated in COP1-mediated HY5 degradation (Figure 2D).35 Other important

464

modulators of light signal coordination, such as HY5 and several R2R3-MYBs (MYB12,

465

MYB44, C1, and TT2), were found to be either significantly repressed by GL or induced

466

by BL/BG (Figure 2D). Together, BL-triggered CRY2/3-COP1-SPA1 interaction allows

467

photomorphogenesis promoting TFs, such as HY5 and R2R3-MYBs to combine with the

468

downstream flavonoids biosynthesis genes (e.g., CHI, CHS, and FLS). In addition, GL

469

could inactivate the CRY2/3- and PHOT2-mediated BL responses, such as anthocyanins

470

and catechins biosynthesis. HY5 have also been reported to mediate the activation of ~10%

471

of all cold-responsive genes in Arabidopsis, including those implicated in anthocyanin

472

biosynthesis, ensuring the complete activation of cold acclimation process. By WGCNA

473

analysis, we identified a set of genes (M7; e.g., HOS1, CBF3/DREB1A, PIF3, PHOT2,

474

VTE1, ANL2, and ANN5) that were highly co-expressed in response to both CT and BL,

475

which indicate a potential integration of CT and BL signals (Figure 4B, D, Figure 5A, B

476

and Table S4). The CBF cold-response pathway is highly conserved among plants and has

477

a pivotal role in plant freezing resistance. The proposed model involves CBFs induction by

478

MYB superfamily TFs CCA1 and LHY during the daytime.59 In our study, these two

479

central clock components CCA1 and LHY were observed to be induced by BL exclusively



Page 24 of 40

480

but not in BG, suggesting that GL might antagonize the BL-mediate activation of CBF

481

pathway (Figure 2D). Jiang et al. reported that PIF3 functions as a negative regulator of

482

Arabidopsis cold tolerance by down-regulating the expression of CBF genes.60 In the

483

current study, BL and BG significantly repressed the expression of PIF3, which may result

484

in the relieve of CBF3 repression (Figure 2D). PIF3 that act downstream of CRYs also

485

regulate the circadian,39 and thus potentially play a role in the BL-dependent control of

486

circadian and the CBF cold-response pathway at basal growth temperatures.

487

The content change of SMs regulated by BL and GL also contributes greatly to the

488

specific taste, infusion color of made tea, which are critical aspects of tea quality. The main

489

shade of color in the tea infusion and infused leaf is primarily determined by the

490

anthocyanin, carotenoid, and chlorophyll content, as well as the content of water-soluble

491

flavonols (e.g., kaempferol, myricitrin, and rutin).13 A delicious cup of tea infusion is

492

primarily determined by the ingenious balance between various taste sensations, such as

493

bitterness, astringency, sourness, umami, and sweetness. Among these, the bitterness and

494

astringency of tea infusion were largely determined by the contents of catechins (e.g., EC,

495

EGC and EGCG) and other phenolic compounds.13 Moreover, supplemental LED lights

496

may promote the chlorophyll catabolism process in ZH3 and therefore increase the amino

497

acids content in chlorotic leaves, which may further improve the umami taste of tea

498

infusion and achieve a higher economic value. Thus, it is possible to target using LEDs to

499

enhance tea quality and taste.

500

We mimic the low light scenario that may occur in the field condition (e.g., shading,

501

climatic variation, daily/seasonal fluctuation of light) and horticulture facilities (e.g.,

502

greenhouse and vertical indoor farming). Our systematic approach utilized here made it


Page 25 of 40


503

possible to resolve the complex and highly interconnected signaling pathways between BL

504

and GL responses. It is also possible to improve tea quality by modulating the LQ-

505

dependent secondary metabolic pathways. The results obtained in this study were the

506

consequences of low-intensity WL during the daytime and high-intensity supplemental

507

BL/GL/BG during the nighttime, which may provide a better reference for production

508

practices and help improve the quality of supplemental lighting used in closed growth

509

systems. In addition, light in the natural shade environment is characterized by reduced

510

ratios of BL/GL and RL/FR instead of the presence of single GL spectrum.61 Thus, our

511

data were comparable with previous LQ studies, and the systematic analysis of the LQ and

512

stress response profiles can be productively mined by other researchers. However, the LQ

513

combination strategies should be carefully evaluated when selecting a nighttime LED light

514

source because the effect of LQ treatments on plant growth and secondary metabolites

515

accumulation varies with tea cultivars and plant development stages, even under the same

516

light modulation strategies and cultivation conditions.

517

ABBREVIATIONS USED

518

ZH3, ‘Zhonghuang3’; CK, control; WL, white light; RL, red light; GL, green light; BL,

519

blue light; BG, blue and green light combination; LED , light-emitting diode; LQ, light

520

quality; TFs, transcription factors; PKs, protein kinases; SMs, secondary metabolites;

521

DEGs, differentially expressed genes; BB, blister blight; CT, cold treatment; DT, drought

522

treatment; CD, cold and drought stress combination; GO, Gene Ontology; MAD, Median

523

absolute deviation; qPCR, quantitative real-time PCR; WGCNA, weighted gene co-

524

expression network analysis; PCC, pearson correlation coefficient; GO, Gene Ontology;



Page 26 of 40

525

KEGG, Kyoto Encyclopedia of Genes and Genomes; BUSCO , benchmarking universal

526

single-copy ortholog; MRM , multiple reaction monitoring; C, catechin; GC, gallocatechin;

527

EGC, epigallocatechin; ECG, epicatechin gallate; EGCG, epigallate catechin gallate; GC-

528

GC, gallocatechin-gallocatechin; JA, jasmonate; ET, ethylene; ABA, abscisic acid; GA,

529

gibberellin; SA, salicylic acid.

530

Funding

531

This work was supported by the Ministry of Agriculture of China through the Earmarked

532

Fund for China Agriculture Research System (CARS-019), and the Chinese Academy of

533

Agricultural Sciences through the Agricultural Science and Technology Innovation

534

Program (CAAS-ASTIP-2017-TRICAAS) to Liang Chen.

535

Supporting Information

536

Figure S1. The phenotype of new shoots of control (CK) and plants supplying with blue

537

light (BL) and green light (GL) either alone or together (BG) for 12 days.

538

Figure S2. qRT-PCR validation of 12 transcripts and their transcriptional response profiles.

539

Figure S3. Relative intensity of metabolites under different light quality conditions. Mean

540

expression values of metabolite intensities with their standard error bars from three

541

biological replicates are represented. The asterisks indicate significant differences between

542

different samples ("*" means P < 0.05; "**" means P < 0.01).

543

Table S1. Primers used for the qPCR assay.

544

Table S2. Quality assessment of assemblies.

545

Table S3. A list of genes in EP1, EP5, EP7, and EP19.

546

Table S4. A list of genes in module 7 and 17.


Page 27 of 40

547


Table S5. A list of top 54 most variant metabolites.

548 549

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721 722

Figure captions

723

Figure 1. Effects of different light qualities on tea plant growth and photosynthetic

724

capacity. (A) Sketch map of light quality treatments. (B) The phenotypes and (C)

725

photosynthetic rate of control (CK) and plants supplying with blue light (BL) and green

726

light (GL) either alone or together (BG) for 12 days. Error bars represent standard error, n

727

= 5.


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728

Figure 2. Differential transcriptome responses of tea plants under different light quality

729

conditions. (A) The histogram showing the number of common and specific DEGs under

730

BL, GL, and BG (left), and the cumulative log-fold changes of 1000 most significantly BL-

731

and GL-responding genes in BG (right), respectively. Venn diagram of genes (B) up-

732

regulated or (C) down-regulated by each light quality treatment. The numbers of common

733

and specific DEGs were shown in the overlapping and non-overlapping regions,

734

respectively. The total numbers of up- and down-regulated DEGs were indicated in

735

parentheses. (D) Heat map representation of the expression patterns of light signaling

736

regulators. Color indicates fold change of DEGs under BL, GL, and BG, as shown in the

737

top.

738

Figure 3. Transcriptional response modes and GO enrichment analysis of DEGs. (A) The

739

dotted line in the boxes represents gene expression with no change compared with the

740

control. The color and value in the right boxes represent the percentage of DEGs in

741

particular expression pattern (red is higher). Combinatorial: similar transcriptional

742

response in BL and GL but a different response to BG; canceled: genes response to either

743

BL or GL returned to control levels in BG; prioritized: opposing responses to the BL and

744

GL and one light quality response prioritized in BG; independent: response to only BL or

745

GL and a similar response to BG; similar: similar responses to BL, GL, and BG. (B-E) In

746

the word clouds, the size of the words is proportional to -log10 (P-value) within one word

747

cloud. The absolute enrichment strength of GO terms (words) is color-coded in grayscale;

748

EP 1-20 (Expression pattern 1-20).

749

Figure 4. Signaling interactions between light qualities and stress treatments. (A)

750

Hierarchical clustering dendrogram of the average network adjacency for the identification



Page 36 of 40

751

of coexpression modules. The major tree branches constitute 25 modules labeled by

752

different colors. (B) Module-treatment association. Each row corresponds to a module. The

753

number of genes in each module is indicated on the left. Color indicates the correlation

754

coefficient of a specific module and the treatment, as shown in the right. Eigengene

755

expression profile for the (C) M7 and (D) M17 in different treatments. The first principal

756

component indicates the value of the module eigengene; the horizontal axis labels indicate

757

different treatments.

758

Figure 5. GO enrichment and network analysis for module 7 and 17. GO enrichment

759

analysis for (A) M7 and (C) M17. The color of the dots in the scatterplot represents the

760

range of the log10 (P-value). The correlation network of (B) M7 and (D) M17. Genes with

761

a higher degree are indicated by red. Categories of the transcription factor (TF), protein

762

kinase (PK), and other genes depicted with different signs.

763

Figure 6. Effect of different light qualities on secondary metabolism in tea plants. (A) Co-

764

variance network. Nodes are colored according to median absolute distance (MAD) scores

765

across samples. Edge line color reflects co-variance between metabolites. Gray, Pearson

766

correlation coefficient (PCC > 0.90); Red, PCC > 0.90 and biochemical substrate-product

767

relationship. (B) Flavonoid biosynthetic pathway. Heat maps on the left and right show

768

fold change of the genes and metabolites involved in flavonoid biosynthetic pathway,

769

respectively. The numbers in the brackets following each gene name indicate the number

770

of corresponding genes identified in transcriptome. The color in the ellipses represents the

771

gene was regulated under particular light quality treatment (blue indicates BL; green

772

indicates GL; cyan indicates BG).


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Figure graphics Figure 1

Figure 2



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Figure 3

Figure 4


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Figure 5

Figure 6



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Graphic for table of contents


Regulation of growth and flavonoids formation of tea plant (Camellia

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