Anthocyanins, water-soluble pigment compounds belonging to the flavonoid class, are widely distributed in plants, which facilitate pollination, seed dispersal and stress resistance. They are also important contributors to the organoleptic qualities of colored fruits, vegetables, and flowers. Additinoally, anthocyanins have shown multiple biological activities and exhibit antioxidant, anticarcinogenic, antimicrobial, and antiviral properties [1
]. For these reasons, interest among plant breeders, the food industry, and consumers in developing anthocyanin-rich foods has intensified.
Anthocyanins are structurally composed of an anthocyanidin aglycone bound to one or more sugar moieties. There are about 17 anthocyanidins found in nature, whereas only six of them, namely, pelargonidin (Pg), cyanidin (Cy), delphinidin (Dp), peonidin (Pn), petunidin (Pt), and malvidin (Mv), occur most frequently in plants [3
]. Anthocyanins are the end-products of a distinct branch that exists in the late stage of the flavonoid biosynthetic pathway, mainly involved in DFR (dihydroflavonol 4-reductase), leucoanthocyanidin oxidase (LDOX), ANS (anthocyanidin synthase), and UFGT (UDP-glucose: flavonoid 3-O
-glucosyltransferase) biosynthetic enzymes [5
]. It has been reported that most of the anthocyanin pathway enzymes are encoded by small gene families, and usually, one or two members of each gene play a crucial role [6
]. The expression of these structural genes relies on the transcriptional activity of MBW ternary complex, which consists of R2R3-MYB and bHLH (MYC-like basic helix–loop–helix) transcription factors, together with WD40-repeat proteins. In vegetative tissues, anthocyanin biosynthesis could be modulated by different MBW complexes involving PRODUCTION OF ANTHOCYANIN PIGMENT1 (PAP1)/MYB75 and PAP2/MYB90, in combination with TRANSPARENT TESTA8 (TT8)/bHLH042, ENHANCER OF GLABRA3 (EGL3)/bHLH002, GLABRA3 (GL3)/bHLH001, and TRANSPARENT TESTA GLABRA1 (TTG1)/WD40 protein [7
]. R2R3-MYBs are considered as key regulators of anthocyanin biosynthesis and have been well characterized in model plants and fruit trees, such as Arabidopsis [9
], petunia [10
], strawberry [11
], apple [12
], grape [13
], and lychee [14
]. MYB R3 repeat (with a conserved motif (D/E)LX2(R-K)X3LX6LX3R) is necessary for interaction with the N-terminal MYB-interacting region (MIR) of the bHLH. Both MYBs and bHLH have the capability of DNA binding, but the target gene specificity of the MBW complex seems to be more conferred by the MYB protein, while WD40 proteins rather seem to be a docking platform, as they can interact with interact with diverse proteins [15
]. The WRKY transcription factors (TTG2/PH3) have been shown to cooperate with the MBW complex, highlighting the importance of transcriptional regulation in the control of flavonoid biosynthesis [16
]. More recently, WRKY41 was demonstrated to repress anthocyanin accumulation by controlling the expression of regulatory and structural genes involved in anthocyanin biosynthesis in Arabidopsis thaliana
and Brassica napus
Light is one of the most important environmental factors for plant growth and development. Plants rely on it as their source of energy and have evolved mechanisms to perceive light signals, including light intensity, specific wavelengths, photoperiod, and direction. Shading and bagging experiments in various fruit species, such as lychee [19
], grapevine [20
], apple [21
], and pear [22
], have demonstrated that light exposure is required to stimulate anthocyanin accumulation and fruit coloration through up-regulation of anthocyanin biosynthetic genes. It has been generally documented that a longer photoperiod can increase the content of anthocyanins and other flavonoids [23
]; however, inconsistent results have also been reported in some plants. The contents of quercetin and kaempferol were higher at 12 h day lengths under different temperature compared to that at 24 h day lengths [25
]. Higher plants can sense specific light wavelengths (also known as light quality or light spectrum) spanning from ultraviolet-B (UV-B) to far-red wavelengths. Arrays of photoreceptors, including UV RESISTANCE LOCUS 8 (UVR8) induced by UV-B, cryptochromes (CRY1, CRY2, CRY3), and phototropins (PHOT1, PHOT2) absorbing ultraviolet-A (UV-A)/blue light, and phytochromes (PHYA-E) responding to red/far-red light, have been reviewed [26
]. Photoreceptors regulate photomorphogenic development by suppressing the RING-finger type ubiquitin E3 ligase CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1) activity, which is directly associated with SUPPRESSOR OF PHYA (SPA) and other COP1 cofactors [27
]. ELONGATED HYPOCOTYL 5 (HY5) is a direct target of COP1 and has been linked to the activation of transcription factors and structural genes in the flavonoid pathway in response to light [28
]. In addition, some PHYTOCHROME INTERACTING FACTORs (PIFs) family members were found to be able to interact with phytochromes and participate in anthocyanin biosynthesis by binding the promoters of related genes [31
Strawberry (Fragaria × ananassa) is popular due to its unique flavor, attractive appearance, and nutritional value, and known as a functional dietary food rich in folate, vitamin C, anthocyanins and other bioactive compounds. Particularly, anthocyanins are natural colorants with health-promoting properties, which have received much attention. Light is one of the most important factors that affects anthocyanin accumulation. However, uneven coloration and defective quality as a result of inadequate anthocyanins often happen in strawberry cultivation with poor light conditions. Thus, supplemental light is necessary. Red and blue light have been generally considered to have the strongest effects on plant growth and metabolism. In this paper, we explored the effect of blue and red light on the anthocyanin accumulation and differentially expressed genes in strawberry, expecting to have a better understanding of the role of light quality in anthocyanin biosynthesis and provide scientific and theoretical basis for strawberry cultivation.
The genetic background of the plant is the main determinant of anthocyanin biosynthesis, whereas the external environment, including biotic and abiotic factors, can cause quantitative and qualitative changes in the composition of these compounds [33
]. The light quality plays an important role for anthocyanin accumulation, independent of photoperiod and light intensity [26
]. LEDs are characterized by a narrow light-emitting spectrum, enabling the focus of the light exposed to plants using only the required wavelength [35
]. This method is more efficient in converting electric power to light power, and it also enables the irradiation of plants at a close distance for a long time because LEDs are cold light illuminators [36
]. Currently, blue and red LEDs in biologically-active visible light regions have been widely introduced to regulate vegetable and fruit quality [37
], but they have been less applied to fruit in vivo. Strawberry plants have a small size, and they do not require a very high light intensity (100–300 µmol·m−2
]. Therefore, it is possible and valuable to investigate the influence of light quality on strawberry fruit coloration using LEDs with single-peak blue and red light in artificial climate chambers where other environmental factors can be controlled.
In our study, the results showed that blue and red light treatment resulted in significantly higher levels of total anthocyanin (TA), and the highest content was achieved in blue light-treated fruit (‘Toyonaka’), followed by red light treatment, which was consistent with responses observed in grape and bilberry fruit [41
]. Differences in the anthocyanin profile (consisting of Pg3G and Pg3MG) were detected in each treated group. In general, the main anthocyanin in strawberry (‘Toyonaka’) was Pg3G, like other cultivars [43
], accounting for 89.84%, 83.60%, and 82.41% in BL, RL, and WL treatments, respectively. This indicated that increased total anthocyanins in strawberry fruits in response to light quality mainly depended on Pg3G production; the secondary anthocyanin (Pg3MG) showed a distinct increase at a quantitative level under RL and BL treatment, but accounted for a smaller proportion of total anthocyanins than in plants under the control treatment (WL). Researchers have found that light quality affects anthocyanin biosynthesis differently [45
]. It is generally documented that short wavelengths in the range of blue and UV light seem to be the prominent wavelengths impacting the increase in anthocyanin content [26
]. Nevertheless, evidence suggesting that light with long wavelengths can increase the intensity of the red coloration also exists [47
]. In strawberry, blue light can induce different cultivar anthocyanin accumulation [50
], whereas red and yellow selective plastic films can increase the temperature and play a positive role in anthocyanin biosynthesis [49
]. Therefore, optimization of anthocyanin concentration using light quality should take species, cultivars, and microenvironment variation into consideration.
Plants utilize multiple photoreceptors to perceive different wavelengths, which then trigger a series of signal transduction events, and finally lead to physiological responses [19
]. In the present study, transcriptome analysis was conducted to further understand the relationship between strawberry pigmentation and monochromatic visible light (red and blue) at the transcriptional level. We found that four types of photoreceptors, including cryptochromes (CRY1
, and CRY3
) and phototropins (PHOT1
), were down-regulated in fruit treated with blue light. Kadomura-Ishikawa (2013) demonstrated that expression patterns of photoreceptor genes decrease gradually during fruit development from the small green to red stages in strawberry, with the exception of PHOT2
], so the reduction in photoreceptor transcription levels could be considered a sign of full fruit coloration. Consistently, anthocyanin biosynthesis is typically associated with blue light through CRYs [54
]. However, the regulation of anthocyanin synthesis via CRYs requires the activity of PHYs for full expression [56
]. CRYs also need interplay with UVR8 to mediate target gene expression under natural environmental conditions [59
]. Thus, other types of light apart from blue light could also significantly affect anthocyanin synthesis in plants. In this study, red light induced the anthocyanin accumulation and expression levels of PHYs
and other photoreceptors. Moreover, the expression level of HY5
, a positive photomorphogenic regulator, was also significantly up-regulated by red light.
In light-inducible anthocyanin biosynthesis, MYBs seem to play a pivotal role in structural gene expression and anthocyanin accumulation [61
]. Lilium regale LrMYB15
transcription ceased completely when plants were kept in shaded conditions, and the colors of the flower buds faded, indicating that transcription of this gene is under the control of light [61
]. Potato StMYBA1
requires light to activate anthocyanin biosynthesis in transgenic tobacco [62
]. These light-sensitive MYBs have also been identified in many fruits, such as grape, apple, pear, lyhee, and strawberry [14
], and are usually activated by HY5 [28
]. In strawberry, FaMYB10
has a role as a signal transduction mediator from light perception to anthocyanin synthesis [66
], and it was also identified in our DEGs (Gene ID: 101307024). Most of the MYBs involved in anthocyanin biosynthesis interact with bHLHs and WD40s to form the MBW regulatory complex. However, the role of bHLH and WD40 partners in light-regulated anthocyanin biosynthesis is not yet clear. In addition, some experiments have noted that WRKYs are also involved in the regulation of this pathway [68
]. We showed that MYB
, and WRKY
expression patterns were similar to photoreceptors under different light quality treatments. Noticeably, most of these regulators had a low transcription abundance in fruit treated with blue light, which resulted in a decrease in the expression level of numerous structural genes. However, the highest anthocyanin content was detected in blue light treatment. Possibly, these genes decreased at this stage that anthocyanin concentration reached saturation, suggesting that blue light could promote the rapid accumulation of anthocyanin in strawberry fruit. In red and white light treatment, light signal perception and transduction components were dynamic to keep the regulatory factors and structural genes of anthocyanin biosynthesis at a high expression level. Moreover, red light not only elevated the anthocyanin contents, it might also contribute to the synthesis of proanthocyanidins by inducing the LAR
. Hence, these results also indicated that the light is an essential environmental factor for anthocyanin biosynthesis before anthocyanin concentration reaches a plateau in fruit.
4. Materials and Methods
4.1. Plant Materials
‘Toyonaka’ (Fragaria × ananassa) seedlings were grown in 15 cm × 13 cm pots filled with a 2:2:1 (v/v/v) mixture of nutrient soil, garden soil, and perlite and subjected to routine management from September 2014 in the greenhouse of Sichuan Agricultural University. Subsequently, on the seventh day after flowering, potted seedlings of uniform size were randomly divided into three groups, transferred into assigned growth chambers and maintained on a photoperiod of 8 h dark at 16 °C and 16 h light at 25 °C at 75% relative humidity. White (control), red (730 nm), and blue (450 nm) light-emitting diodes (LEDs) were placed at the top of the chambers to irradiate strawberry seedlings at 100 μmol·m−2·s−1 until fruits were harvested. Fruit samples from three biological replicates (at least three fruits per replicate) for each treatment were collected on the 25th day after flowering and then stored at −80 °C after immediately freezing in liquid nitrogen.
4.2. Anthocyanin and Proanthocyanidin Determination
Approximately 1.0 g of frozen samples was ground to a fine powder in liquid nitrogen, then soaked in 5 mL of methanol containing 1% (v/v) hydrochloric acid overnight at 4 °C. After centrifugation at 5000× g for 20 min, the supernatant was transferred into a brown volumetric flask. Then, the residue was re-homogenized twice using extraction buffer. Finally, the supernatants were combined and brought to a final volume of 10 mL. One milliliter of the extract was passed through a 0.45 μm membrane filter before HPLC analysis. Determination of anthocyanins was performed on an Agilent 1260 HPLC system (Agilent Technologies, Palo Alto, CA, USA) equipped with variable wavelength detectors (VWD) and a ZORBAX SB-C18 column (150 mm × 4.6 mm, 5 μm). Mobile phases consisting of ultra-pure water (A), acetonitrile (B), and formic acid (C) were used to carry out a linear gradient elution. The chromatographic conditions were as follows: 0 min, 100% A; 13 min, 78% A + 20% B + 2% C; 20 min, 58% A + 40% B + 2% C; and 25 min, 100% A. The flow rate was 1 mL·min−1; the injection volume was 10 μL; and the C18 column was maintained at 30 °C. Anthocyanins were detected at 520 nm by VWD.
Proanthocyanidin content was determined using an improved DMAC (4-dimethylaminocinnamaldehyde) method that has been described previously [70
]. A 0.5–1.0 g sample of strawberry powder was added into 20 mL extraction solution, which was a mixture of acetone, deionized water, and acetic acid (150:49:1 v
), placed on a shaker for 1 h and subsequently centrifuged at 10,000× g
for 20 min at 12 °C. The supernatant was collected for analysis at 640 nm in a 96-well microplate reader (Thermo Fisher Scientific, Waltham, MA, USA).
Standards were purchased from Sigma (St. Louis, MO, USA), and all samples were prepared in triplicate.
4.3. RNA Extraction, cDNA Library Preparation and Illumina Sequencing
Total RNA was isolated from each sample using the improved CTAB (cetyltrimethylammonium bromide) method [71
]. The quality and quantity of the total RNA were analyzed by electrophoresis on a 1% agarose gel and using a NanoPhotometer®
spectrophotometer (Implen, Westlake Village, CA, USA) and the RNA Nano 6000 Assay Kit on a Bioanalyzer 2100 system (Agilent Technologies, Palo Alto, CA, USA).
cDNA libraries were obtained from white, red, and blue light-treated strawberries in two biological replicates (W251, W252, R251, R252, B251, B252). A total amount of 3 µg RNA per sample was used as input material. Sequencing libraries were generated using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, Ipswich, MA, USA). Briefly, mRNA was purified from total RNA by Oligo(dT)-attached magnetic beads and sheared randomly using fragmentation buffer. Subsequently, the fragment templates were used to synthesize first strand cDNA by adding random hexamer primers and M-MuLV Reverse Transcriptase (RNase H−) followed by the generation of the second-strand cDNA using dNTPs, buffer, DNA polymerase I, and RNase H. Then, the double-stranded cDNA was purified with AMPure XP beads and sequentially modified by end-repairing, poly-A tail-adding and Illumina adapter-ligating before selecting for fragment size with AMPure XP beads. Finally, the cDNA libraries were PCR-amplified and assessed using a Qubit 2.0 Flurometer (Life Technologies, Carlsbad, CA, USA), a Bioanalyzer system (Agilent Technologies, Palo Alto, CA, USA) and Q-PCR methods. Transcriptome sequencing was performed on the Illumina HiSeq 2500 platform (Illumina, San Diego, CA, USA), and 125/150 bp paired-end raw reads were generated.
4.4. RNA-Seq Data Preprocessing Reads Mapping
Raw data (raw reads) in fastq format were first processed with in-house Perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing poly-N (ratio of “N” accounted for more than 10%) and low-quality reads (bases of Qphred ≤ 20, Q20, which accounted for more than 50%) from the raw data. At the same time, the Q20, Q30, and GC contents of the clean data were calculated. All downstream analyses were based on clean data with high quality. Reference-based strategy to assemble a transcriptome is the most straightforward method, which requires a high-quality reference genome. However, the whole-genome sequence of Fragaria
has not been published. Fragaria vesca
is the most plausible progenitor of Fragaria
and the availability of its genome offers the possibility of mapping the transcriptomic data of Fragaria
to a reference genome, which contributes greatly to advances in molecular genetic analysis and identification of genes related to agriculturally-important traits in Fragaria
]. Hence, clean reads were mapped to the Fragaria vesca
reference genome (https://www.rosaceae.org/organism/Fragaria/vesca
]. Reference genome and gene model annotation files were downloaded directly from the genome website. An index of the reference genome was built using Bowtie v2.2.3, and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12 with the default constraint of two mismatches.
4.5. Differentially-Expressed Gene (DEG) Identification and Functional Annotation
RNA-Seq gene expression levels were normalized by calculating FPKM (fragments per kilobase of transcript sequence per million base pairs sequenced) [75
]. Differential expression analysis was performed using the DESeq R package v1.10.1 after the Pearson correlation between samples was analyzed [76
]. DESeq provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting p
-values were adjusted using Benjamini and Hochberg’s approach (1995) applied in multiple hypothesis testing for controlling the false discovery rate (FDR) [77
]. Genes with an adjusted p
< 0.05 found by DESeq were assigned as differentially expressed. Then, DEGs were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis implemented by the Goseq R package and KOBAS software, respectively, for functional annotation, and corrected p
-values less than 0.05 were considered significantly enriched. Heatmaps were generated using the among-gene normalized FPKM values as an indicator of gene expression values. Before drawing the diagram, average FPKM was obtained between two replicates, and the log 10 transformed (FPKM+1) were used for drawing the map with the Pheatmap R package, and the relative expression level was represented by colors ranging from low (blue) to high (red) for each gene across the entire dataset.
4.6. Quantitative Real-Time PCR (qRT-PCR) Analysis
qRT-PCR was used to validate the gene expression patterns obtained by RNA-Seq on the CFX96 real-time PCR system (Bio-Rad, Hercules, CA, USA). cDNA for each sample was generated using the PrimeScript™ RT reagent Kit with gDNA Eraser (Takara Shuzo, Kyoto, Japan), according to the manufacturer’s instructions. Gene-specific primers used for verification of DEGs were listed in Table S3
. All PCR reactions contained 0.4 μL of each primer (0.4 μM), 5 μL SYBR Premix (Takara Shuzo, Kyoto, Japan), 1 μL cDNA template, and 3.2 μL of RNase-free water in a final volume of 10 μL. The reaction protocol was set with three-step cycling conditions: 95 °C for 3 min, followed by 40 cycles of 95 °C for 10 s, 60 °C for 30 s and 72 °C for 15 s. A melting curve analysis was inserted after the final cycle, ramping from 65 °C to 95 °C (increment 0.5 °C/5 s). Relative fold changes in gene expression were calculated by the 2−ΔΔCT
method, and the FaActin
gene (GenBank: LC017712.1) was selected as the internal control to normalize the raw data.