Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Transcriptome Analysis Reveals that Red and Blue Light Regulate Growth and Phytohormone Metabolism in Norway Spruce [Picea abies (L.) Karst.]

  • Fangqun OuYang,

    Affiliations State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy Forestry, Beijing, 100091, PR China, National Engineering laboratory for Forest Tree Breeding, Key Laboratory for Genetics and Breeding of Forest Trees and Ornamental Plant of Ministry of Education, College of Biological Science and Technology, Beijing Forestry University, Beijing, 100083, PR China

  • Jian-Feng Mao,

    Affiliation National Engineering laboratory for Forest Tree Breeding, Key Laboratory for Genetics and Breeding of Forest Trees and Ornamental Plant of Ministry of Education, College of Biological Science and Technology, Beijing Forestry University, Beijing, 100083, PR China

  • Junhui Wang ,

    wangjh808@sina.com (JW); liyue@bjfu.edu.cn (YL)

    Affiliation State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy Forestry, Beijing, 100091, PR China

  • Shougong Zhang,

    Affiliation State Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy Forestry, Beijing, 100091, PR China

  • Yue Li

    wangjh808@sina.com (JW); liyue@bjfu.edu.cn (YL)

    Affiliation National Engineering laboratory for Forest Tree Breeding, Key Laboratory for Genetics and Breeding of Forest Trees and Ornamental Plant of Ministry of Education, College of Biological Science and Technology, Beijing Forestry University, Beijing, 100083, PR China

Transcriptome Analysis Reveals that Red and Blue Light Regulate Growth and Phytohormone Metabolism in Norway Spruce [Picea abies (L.) Karst.]

  • Fangqun OuYang, 
  • Jian-Feng Mao, 
  • Junhui Wang, 
  • Shougong Zhang, 
  • Yue Li
PLOS
x

Abstract

The mechanisms by which different light spectra regulate plant shoot elongation vary, and phytohormones respond differently to such spectrum-associated regulatory effects. Light supplementation can effectively control seedling growth in Norway spruce. However, knowledge of the effective spectrum for promoting growth and phytohormone metabolism in this species is lacking. In this study, 3-year-old Norway spruce clones were illuminated for 12 h after sunset under blue or red light-emitting diode (LED) light for 90 d, and stem increments and other growth traits were determined. Endogenous hormone levels and transcriptome differences in the current needles were assessed to identify genes related to the red and blue light regulatory responses. The results showed that the stem increment and gibberellin (GA) levels of the seedlings illuminated by red light were 8.6% and 29.0% higher, respectively, than those of the seedlings illuminated by blue light. The indoleacetic acid (IAA) level of the seedlings illuminated by red light was 54.6% lower than that of the seedlings illuminated by blue light, and there were no significant differences in abscisic acid (ABA) or zeatin riboside [ZR] between the two groups of seedlings. The transcriptome results revealed 58,736,166 and 60,555,192 clean reads for the blue-light- and red-light-illuminated samples, respectively. Illumina sequencing revealed 21,923 unigenes, and 2744 (approximately 93.8%) out of 2926 differentially expressed genes (DEGs) were found to be upregulated under blue light. The main KEGG classifications of the DEGs were metabolic pathway (29%), biosynthesis of secondary metabolites (20.49%) and hormone signal transduction (8.39%). With regard to hormone signal transduction, AUXIN-RESISTANT1 (AUX1), AUX/IAA genes, auxin-inducible genes, and early auxin-responsive genes [(auxin response factor (ARF) and small auxin-up RNA (SAUR)] were all upregulated under blue light compared with red light, which might have yielded the higher IAA level. DELLA and phytochrome-interacting factor 3 (PIF3), involved in negative GA signaling, were also upregulated under blue light, which may be related to the lower GA level. Light quality also affects endogenous hormones by influencing secondary metabolism. Blue light promoted phenylpropanoid biosynthesis, phenylalanine metabolism, flavonoid biosynthesis and flavone and flavonol biosynthesis, accompanied by upregulation of most of the genes in their pathways. In conclusion, red light may promote stem growth by regulating biosynthesis of GAs, and blue light may promote flavonoid, lignin, phenylpropanoid and some hormones (such as jasmonic acid) which were related to plant defense in Norway spruce, which might reduce the primary metabolites available for plant growth.

Introduction

Light quality [13] has important effects on plant growth and development, especially for plants in high-latitude areas [4], and different light spectra have different effects on plant growth [5]. Studies to date of the effects of light quality have mainly concentrated on model plants [6, 7], algae [8, 9], and vegetables [1012]. By contrast, there are few studies of the effects of light quality on woody plants. Thus, it is of great importance to increase the current understanding of the growth response of woody plants to light quality.

The spectra of sunlight that affect plant photosynthesis primarily include red and blue light. Blue light, which has a shorter wavelength and higher energy than red light, has been found to promote hydraulic conductivity in Betula pendula [13]. However, blue light does not have a significant effect on hypocotyl extension in Scots pine (Pinus sylvestris L.), a species in which stem extension is regulated by far-red light [14]. Mølmann et al. (2006) [15] have found that red and far-red light can maintain the growth of Norway spruce and that a southern population is more sensitive to red light, lacking a complete bud set, even at a low level of radiation (0.1 Wm-2). However, blue light induces bud set in seedlings. Furthermore, the effects of light quality vary among different varieties or species of plants. The different mechanisms by which light quality regulates plant growth and development include the selective activation of all types of light receptors, such as the activation of phytochrome by red and far-red light, cryptochrome and phototropin by blue light, and UVB receptor by ultraviolet light [3, 16].

Plant growth is also affected by interactions between endogenous hormone levels and light quality [17]. In the light regulation process, the hormone level in a plant affects its light responsiveness. Exogenous hormones can stimulate the light-mediated regulation of plant growth, functioning as second messengers in light signal transduction processes [18]. In turn, light regulates a variety of hormone pathways. PHYA affects the hybrid aspen gibberellin (GA) and indoleacetic acid (IAA) metabolic pathways [19], and key light signaling components, such as phytochrome-interacting factor 3 (PIF3), PIF4 and HY5, can connect light and plant hormone signaling in the regulation of seedling photomorphogenesis [17]. The plant hormones associated with light-mediated plant growth regulation largely include GAs [6, 20, 21], auxins [22, 23], cytokinins [20] and abscisic acid (ABA) [24], of which the growth-promoting phytohormones GAs and auxin play the main roles. Light quality also affects endogenous hormone regulation of plant growth and development by influencing secondary metabolism; for example, blue light promotes flavonoid accumulation [25], which affects auxin polar transport [26].

Light supplementation can effectively control seedling growth in Norway spruce. However, knowledge of the effective spectrum for promoting growth and phytohormone metabolism in this tree is still lacking. The completion of the P. abies genome [27] and the rapid development of high-throughput sequencing have facilitated gene expression studies in Norway spruce using RNA sequencing (RNA-seq) analysis. In the present study, 3-year-old P. abies clones were illuminated for 12 h after sunset under red or blue LED light, and stem increment and other growth trait determinations, phytohormone level measurements and RNA-seq analysis were performed to achieve the following aims: (1) to understand the effects of these two types of light qualities on Norway spruce growth; (2) to analyze the relationship between light quality and plant hormones in Norway spruce; and to identify differentially expressed genes (DEGs) under red and blue light. This study was conducted to provide a basis for elucidating the genetic mechanisms by which different light qualities regulate seedling growth and phytohormone levels.

Materials and Methods

Experimental design and growth conditions

P. abies clones (3 years old) were grown in a container (10 x 10 cm) under greenhouse conditions and received natural light during the day and illumination by blue-light (B, 460 nm) or red-light (R, 660 nm) LED lamps for 12 h at night (power of 90 W) from May 10 to August 10, 2013. Each LED lamp was 90 cm long and was installed above five clones. Each row included five clones arranged with 10 cm spacing. Light intensity (50 μmol.m-2.s-1) was measured using a spectrum radiator (OL750) at the National Institute of Metrology, People’s Republic of China. Five clones were present in each plot, with three plot replications per light quality treatment. Shading cloth was used between the plots during the lighting period and was removed during the day.

The clones were tended consistently for all experimental treatments. From June until September, the average temperature in the nursery was 20~26°C, with an average humidity of 50~65%. The clones were watered regularly and fertilized twice per month using a foliar nutrient with 5 kg/m2 4/1000 monopotassium phosphate (the main ingredient was KH2PO4) and 0.002 kg/kg phosham [the main ingredient was (NH4)2HPO4], calcium phosphate [Ca3(PO4)2], and carbamide (H2NCONH2).

Measurements of seedling traits

We determined the stem height, ground diameter, and length of the current shoots for all clones in August 2013 after 90 days of illumination. The leaf area and leaf weight were measured for 30 needles from 6 clones per LED treatment. The specific leaf weight (SLW) was calculated as follows: leaf weight/leaf area.

Determination of plant hormones

In August 2013, after 90 days of blue or red light treatment, current needles were harvested from three randomly selected Norway spruce clones and stored at -80°C until analysis for the following phytohormones: GAs, IAA, ABA, and ZR. The samples were ground in an ice-cold mortar, extracted with 10 mL 80% methanol (v/v) containing 1 mmol-1 butylated hydroxytoluene (BHT), and then stored at 4°C for 4 h. Next, they were centrifuged at 3500 rpm for 8 min at 4°C. The precipitation was extracted with the same extraction solution for 1 h at 4°C and then centrifuged again under the same conditions. The two combined supernatants were passed through Chromosep C18 columns (C18 Sep-Park Cartridge, Waters Corp., Milford, MA) and dried under N2. The residues were then dissolved in 2 mL phosphate-buffered saline (PBS) for analysis of GAs, IAA, ABA, and ZR using an enzyme-linked immunosorbent assay (ELISA). Mouse monoclonal antigens and antibodies against IAA, GAs, ZR and ABA and IgG-horseradish peroxidase used in ELISA were obtained from the Research Institute of China Agricultural University (Beijing, China). Microtiter plates (96-well) were coated with 100 μL of coating buffer (1.5 g L-1 Na2CO3, 2.93 g L-1 NaHCO3, and 0.02 g L-1 NaN3, pH 9.6) containing 0.25μg mL-1 of antigens against the hormones and were incubated for 4 h at 37°C for ZR, GAs, and ABA and overnight at 4°C for IAA. Then, the plates were washed four times with PBS + Tween 20 (0.1% [v/v]) buffer (pH 7.4), coated with 50 L-1 of either grain extracts or hormone standards and 50 μL of 20μg mL-1 antibodies and incubated for 3 h at 28°C for ZR, GAs, and ABA and overnight at 4°C for IAA. After washing again as above, 100 μL of IgG-horseradish peroxidase substrate was added and incubated for 1 h at 30°C. A color development solution containing 1.5 mg mL-1 0-phenylenediamine and 0.008% (v/v) H2O2 was added to each well of the plate, after the wells were washed five times with the above mentioned PBS + Tween 20 buffer. An ELISA reader (model EL310, Bio-TEK, Winooski, VT) was used to detect the color development in each well at optical density A490, after the reaction progress was stopped by adding 50 μL of 2 mol.L-1 H2SO4 per well. The ZR, IAA, GAs, and ABA concentrations were calculated according to Weiler et al. (1981)[28].

RNA-seq analysis

RNA extraction, cDNA library preparation, and sequencing.

Total RNA was extracted from 50 to 100 mg of needles using TRIZOL reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The samples were subjected to residual DNA removal by DNase I digestion for 30 min at 37°C (Takara, Dalian, China). Then, a NanoDrop ND-1000 spectrophotometer (LabTech, Holliston, MA, USA) was used to measure the absorbance of the purified RNA at 260 and 280 nm (A260/A280) to determine the quality and quantity. The average RNA integrity number (RIN) of the samples was 8.9 using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Next, mRNA was purified from 6 μg of total RNA (an equal-ratio mixture of RNA from three randomly selected blue- and red-light-treated P. abies needles) using oligo (dT) magnetic beads to remove the rRNA. A fragmentation buffer was added to produce short mRNA fragments (approximately 200 bp long). First-strand cDNA was synthesized using random hexamer primers with mRNA fragments as templates. Second-strand cDNA was synthesized by adding buffer, dNTPs, RNase H, and DNA polymerase I. The double-stranded cDNA was purified using a QiaQuick PCR Extraction Kit and washed with EB buffer for end repair and single nucleotide A (adenine) addition. In the end, sequencing adaptors were ligated to the fragments. The required fragments were purified using agarose gel electrophoresis and enriched by PCR amplification. The library products were prepared for sequencing analysis using an Illumina HiSeq 2000 (Illumina, San Diego, CA, USA).

Sequence read mapping and assembly.

Clean reads were generated by filtering raw reads, removing low-quality tags (reads with unknown nucleotides, “N”), removing empty reads (no read sequence between the adaptors), and removing reads with only one copy number (that may have resulted from sequencing errors). Reference genome and gene model annotation files were downloaded from the Norway spruce genome website at http://congenie.org/eplant. The remaining clean reads were aligned to the reference genome and sequences using SOAPaligner/soap2, permitting up to two base mismatches. The alignment data were used to calculate the distribution of reads for the reference genes and to perform coverage analysis.

Quantification and differential expression analysis of transcripts.

The reads per kilobase transcriptome per million mapped reads (RPKM) method [29] was used to calculate the gene expression level following the formula: RPKM = 106C/(NL/103). When calculating the expression of gene A, C represents the reads uniquely aligned to gene A, N is the total number of reads uniquely aligned to all genes, and L is the number of bases in gene A. We used “FDR ≤ 0.001 [7] and the absolute value of Log2Ratio ≥ 1” as thresholds to determine the significance of the gene expression differences, where FDR is the false discovery rate. More stringent criteria, including smaller FDRs and larger fold changes, can be used to identify DEGs.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differentially expressed transcripts.

GO and KEGG enrichment analyses were performed to assess the DEGs. GO terms with corrected P-values of less than 0.05 were considered to be significantly enriched in the DEG transcripts. For KEGG analysis, we used a Q-value of less than or equal to 0.05 as the threshold to demonstrate significant enrichment of the gene sets.

Quantitative real-time PCR (qRT-PCR) validation

The DEGs with three biological replicates were validated using qRT-PCR. In all cases, the primers designed spanned exon-exon boundaries. Actin AAF03692 (TGAGCTCCCTGATGGGCAGGTGA/TGGATACCAGCAGCTTCCATCCCAAT) [30] was used as a reference control. The reaction was performed using a 26SYBR Green Master Mix (TianGen) and a CFX96 Real-Time System (Bio-Rad, USA) under the following conditions: denaturation at 95°C for 3 min followed by 40 cycles of amplification (95°C for 30 s, 60°C for 30 s, and 72°C for 30 s). Relative expression was calculated using the delta-delta-Ct method. The primer sequences can be found in S1 Table.

Results

Effects on seedling traits

There were significant differences in stem height, ground diameter, leaf area, leaf dry weight, and SLW between the two light quality treatments (P-value < 0.1). Multiple comparisons of the data showed that the average values under the red light treatment were higher than those under the blue light treatment, except for SLW (Fig 1A1E). The average stem increment, ground diameter, leaf area, and leaf dry weight of the clones illuminated by red light were 8.6%, 13.27%, 22.72%, and 47.32% higher, respectively, than those of the seedlings illuminated by blue light, whereas the average SLW was 11.44% lower than that in the seedlings illuminated by blue light.

thumbnail
Fig 1. Multiple comparisons of growth traits and phytohormone average levels for red light and blue light treatments.

https://doi.org/10.1371/journal.pone.0127896.g001

Effects on phytohormones

ZR and ABA were not affected by light quality, whereas it had significant effects on GAs and IAA (P-value < 0.1). The average GA level of the seedlings illuminated by red light (6.14 ng/100 g) was 29.0% higher than that of those illuminated by blue light (4.6 ng/100 g). Conversely, the IAA level (76.22 ng/100 g) was 54.6% lower compared with the seedlings illuminated by blue light (117.8 ng/100 g) (Fig 1H1K).

RNA-seq analysis

The focus of this study was to identify candidate genes for investigating light quality (red light and blue light) responses based on DEG patterns in Norway spruce clones grown under red and blue light. Therefore, we examined the changes in gene expression under red light using the expression levels under blue light as a reference, and vice versa. Using this approach, the genes enhanced under red light were found to be suppressed under blue light, and vice versa.

Illumina sequencing and mapping of the reference genome and genes

In this study, 58,736,166 and 60,555,192 clean reads were generated for each sample illuminated by red or blue LED lamps, which were used for further analysis (Table 1). Approximately 71% of the reads in each sample were uniquely mapped to the Norway spruce genome, and 36% of the total reads were assigned to Norway spruce genes (Table 1). A total of 20,817 and 21,414 genes (short reads mapped to the reference genome) were detected in each library, accounting for more than 78% of the 26,437 genes in the P. abies reference genome database (Nystedt et al., 2013). Overall, 21,923 unique genes were expressed between the two libraries (S2 Table), with a mapping coverage of 82.93%, which strongly supported the RNA-seq results. The mean coverage of all genes was greater than 78%, and the highest coverage achieved was 100.00% (Fig 2A and 2B).

thumbnail
Fig 2. Mean coverages of all genes in the samples treated with red light (A) and blue light (B) and the upregulated and downregulated DEGs in the sample treated with blue light compared with that treated with red light (C).

https://doi.org/10.1371/journal.pone.0127896.g002

thumbnail
Table 1. Mapping of RNA-seq library reads in Picea abies under red light and blue light to the Picea abies reference genome and genes.

https://doi.org/10.1371/journal.pone.0127896.t001

DESeq analysis

In total, 20,308 uniform genes from the two libraries were analyzed using DESeq (version 2.14) to determine the DEGs in each sample (FDR < 0.001), fold change ≥ 2). Ultimately, 2,926 DEGs were identified, among which 2,744 were upregulated and 182 were downregulated in the sample under blue light compared with that under red light (Fig 2C; S3 Table). Approximately 893 genes were upregulated by ≥ 2-fold, and 30 genes were downregulated by ≥ 2-fold.

GO and KEGG pathways

GO terms were assigned to the mapped genes, and enrichment analysis of these terms showed that “metabolic process”, “cell and cell part”, and “catalytic activity” were predominant in the cellular component, molecular function, and biological process categories, respectively (Fig 3). Morphogenesis (“anatomical structure morphogenesis”, “post-embryonic morphogenesis”, “post-embryonic organ morphogenesis”, and “floral organ morphogenesis”), signaling pathway (“transmembrane receptor protein tyrosine kinase signaling pathway”, “enzyme-linked receptor protein signaling pathway”, and “cell surface receptor signaling pathway”), and growth regulation (“regulation of cell size”, “cell division”, “regulation of meristem growth”, and “regulation of meristem development”) were also significantly enriched in the biological process category (S4 Table).

To identify the biological pathways that are active in Norway spruce under red light and blue light, we mapped the 2926 DEGs to the reference canonical pathways in the KEGG database. In total, 1669 DEGs were assigned to 111 KEGG pathways. Some of the genes assigned to primary metabolic process terms were associated with the following KEGG pathways: metabolic pathways (29%), biosynthesis of secondary metabolites (20.49%), plant hormone signal transduction (8.39%), phenylpropanoid biosynthesis (6.65%), flavonoid biosynthesis (4.67%), and starch and sucrose metabolism (4.49%) (Fig 4; S4 Table). These annotations increase the current understanding of the regulatory functions of light quality on specific processes, functions, and pathways in conifers.

There were 484 and 342 genes assigned to metabolic pathways and biosynthesis of secondary metabolites, respectively. Of these, only 33 and 36 genes were downregulated under blue light. Their heatmaps according to gene expression level [log10(RPKM)] are displayed in Fig 5. The KEGG pathway maps contained 39 metabolic pathway maps and 25 biosynthesis of secondary metabolites pathway maps. The significantly prominent pathways in the present study were phenylpropanoid biosynthesis, flavonoid biosynthesis, flavone and flavonol biosynthesis, starch and sucrose metabolism, phenylalanine metabolism and glycerophospholipid metabolism, which are presented in Table 2. The pathways revealed extensive blue-light-associated upregulation genes compared with those under red light treatment, specifically, 77.55%~98.21% upregulated (Fig 5, Table 2).

thumbnail
Fig 5. Heatmap of genes from metabolic pathways and biosynthesis of secondary metabolites.

https://doi.org/10.1371/journal.pone.0127896.g005

thumbnail
Table 2. Significantly enriched pathways of differentially expression unigenes.

https://doi.org/10.1371/journal.pone.0127896.t002

By examining plant hormone signal transduction (Fig 6; S4 Table), we found that the AUXIN-RESISTANT1 (AUX1), AUX/IAA, auxin-inducible genes, auxin response factor (ARF) and small auxin-up RNA (SAUR) genes were also upregulated under blue light, whereas the GH3 gene was downregulated (Fig 6). GRAS genes (S2 Table), GIBBERELLIN INSENSITIVE DWARF1 (GID1) and DELLA genes were upregulated under blue light. CRE1, B-ARR, A-ARR and AHP3 (S2 Table) genes were also upregulated under blue light, whereas AHP1 and AHP5 (S2 Table) genes were downregulated. Only the protein phosphatase 2C (PP2C) gene, which is involved in ABA signal transduction, was upregulated in the samples grown under red light (Fig 6). In the pathway of ethylene (ET) signal transduction, CTR1 and EBF1/2 were upregulated under blue light, whereas ERF1/2 was downregulated. In the pathway of brassinosteroid (BR) signal transduction, BKI1, BZR1/2, TCH4 and CYCD3 were upregulated under blue light. Twenty BAK1 genes were upregulated and 6 genes were downregulated in the samples grown under blue light; 16 BRI1 genes were upregulated and 4 genes were downregulated in the samples grown under blue light. In the jasmonic acid (JA) signal transduction pathway, JAZ was upregulated, whereas 13 MYC2 genes were upregulated and 1 gene was downregulated under blue light.

Several DEG-encoding enzymes involved in the circadian rhythm in plants, plant hormone signal transduction, carotenoid biosynthesis, carbon fixation in photosynthetic organisms, oxidative phosphorylation, and the pentose phosphate pathway were identified (Table 3). With regard to the circadian rhythm in plants, PIF3 was upregulated by blue light, whereas constans (CO), chalcone synthase (CHS), and amyloid precursor proteins (APRs) 3, 5, and 7 were upregulated by red light. For plant hormone signal transduction, AUX1, AUX1/IAA, ARF, SAUR, GID1, and DELLA were upregulated by blue light, whereas GH3 (Table 3) and CONSTANS-LIKE 7 (COL7; MA_91504g0010, S2 Table) were upregulated by red light. Enzymes involved in carotenoid biosynthesis, carbon fixation in photosynthetic organisms, oxidative phosphorylation, and the pentose phosphate pathway were upregulated by blue light.

qRT-PCR analysis

Total RNA from the same two samples used for RNA-seq analysis was used as a template for qRT-PCR (Fig 7). For the majority of genes, the transcript fold changes determined by qRT-PCR were similar to those estimated from the RNA-seq data, supporting the RNA-seq results for P. abies.

Discussion

The stem increment, ground diameter, leaf area, and leaf dry weight parameters of Norway spruce illuminated by red light were all higher compared with the samples illuminated by blue light, and these findings were coupled with a significantly higher GAs level and a lower IAA level. These changes may be related to DEG gene expression mainly associated with plant hormone signal transduction, metabolic pathways and biosynthesis of secondary metabolites. The DEG classifications revealed extensive blue-light-associated upregulation in Norway spruce.

Light-induced developmental and metabolic patterns in green plants are thought to be mediated primarily by changes in the expression of light-regulated genes [31], including those encoding photosynthetic components and enzymes [9]. In the present study, several genes involved in the response to red light or blue light were found to be differentially expressed; for example, MA_16729g0010, MA_41041g0010, and MA_10432538g0010 were upregulated under red light (S3 Table). Carotenoids absorb mainly blue-violet wavelengths and were upregulated under blue light (Table 2). These results show that blue/red light modulates plant growth and development by altering the expression of corresponding genes. Indeed, light quality influences plant growth by regulating specific photoreceptors [3, 32, 33], and photoreceptor gene expression was found to be affected by light quality in our study. However, significant differential expression between the two light qualities was not found, which is in accordance with previous reports of Arabidopsis seedlings [31] and Saccharina japonica (Phaeophyceae) [9]. The gene expression profiles of Arabidopsis seedlings grown under white light, red light, and blue light are very similar for most genes [31], and a large proportion of DEGs identified in S. japonica under blue light are also induced by red light [9]. These results indicate that light-regulated gene expression in Norway spruce is not a unique response to blue light or red light and that different light qualities are transduced to regulate the same metabolic patterns. Cryptochromes are both blue and red light receptors, suggesting that plant photoreceptors cooperate to control development and physiology [7]. In Physcomitrella patens, phototropins not only mediate blue light-induced chloroplast movement but also exhibit a function in chloroplast movement in response to red light, which it does not absorb [34].

GAs play a central role in promoting stem growth. GAs promote skotomorphogenesis and repress photomorphogenesis in contrast with light signals [17], accelerating stem elongation [35]. Arabidopsis thaliana mutants lacking endogenous GAs have shorter stems and smaller leaves [36]. In the present study, the GA concentrations were significantly increased under red light compared with blue light (Fig 1H), which might have been the reason for the greater height increase of the plants grown under red light in this study. In addition, the GID1, DELLA, and GRAS genes were upregulated under blue light (Fig 6, S2 Table). The GA-GID1 (GA receptor) complex can trigger the rapid degradation of DELLA proteins [37], a subfamily of GRAS genes belonging to a plant-specific transcription factor family, which includes GIBBERELLIC ACID INSENSITIVE (GAI), REPRESSOR OF GAI (RGA) and SCARECROW (SCR) [38]. As transcription factors, DELLA proteins in the nucleus play an important role in regulating sensitivity to GAs because they are involved in negative GA signaling [39]. Poplar has a decreased sensitivity to GAs because the levels of DELLA inhibitors (coding GA-INSENSITIVE) in apical buds increase rapidly when they are transferred to short-day conditions [40]. Olsen (2010) has proposed that the expression of PIFs increases under short-day conditions, which may stimulate the expression of DELLA inhibitors, leading to decreases in GA sensitivity and bud set [4]. PIFs are important factors linking light and plant hormone signaling and regulating seedling photomorphogenesis [41], and they can activate GAI and RGA expression [39]. PIF3 and DELLA inhibitors were found to be upregulated by blue light in this study (Table 2), which is similar to a study of poplar indicating that PIF3-LIKE1 and PIF4 transcription increases following transfer to short-day conditions [42]. These results demonstrate that the mechanisms by which GAs control growth in Norway spruce (Fig 6) may involve the GA-GID1-DELLA signaling module of angiosperms [37], which is also in accordance with a model proposed by Olsen in which GAs control growth [4].

In addition to GAs, auxin has been suggested to be involved in growth cessation, cold acclimation, and dormancy induction [43]. Auxin also plays an important role in photomorphogenesis [44, 45]. Light signaling and the auxin pathway have been clearly demonstrated to be intertwined, and a series of AUX/IAA proteins are phosphorylated by phytochrome A [46]. In the present study, the IAA levels were significantly increased in the plants illuminated under blue light compared with those illuminated under red light (Fig 1G). In addition, the AUX/IAA, auxin-inducible, and early auxin-responsive genes (ARF and SAUR) were upregulated under blue light (S3 Table, Table 2, Fig 5). These results indicate that blue light promoted and red light suppressed auxin metabolism by regulating the expression of related genes. Reddy and Finlayson have also demonstrated that the red light receptor phytochrome B promotes branching in Arabidopsis by suppressing auxin signaling [23]. We found that COL7 was upregulated under red light (S4 Table). COL7 is a critical factor linking photoreceptor and auxin levels and enhances the branching number and downregulates the IAA level under high red:far-red light [22]. COL7 also promotes the mRNA expression of SUPERROOT 2 (SUR2), which suppresses auxin biosynthesis, in association with photo-excited phyB [22].

The roles of ABA and GAs in plant growth and development are antagonistic. ABA represses growth in contrast with GAs. Low red:far-red light quality suppresses bud outgrowth but not that of the topmost bud, which is notably associated with ABA, as shown by DEG analysis [47]. By contrast, the ABA level was not significantly affected by the two light qualities assessed in this study. In ABA signal transduction, only PP2C genes, which have been demonstrated to function as negative regulators of ABA signaling [48], were upregulated in the samples grown under blue light (Fig 6). Cytokinins are well known to control cell division in plant growth and development [49], promoting axillary bud outgrowth [50]. With regard to cytokinin signal transduction, AHP3 was found to be upregulated under blue light; however, AHP1 and AHP5 were downregulated (Fig 6), which might have caused the lack of a significant difference in the ZR level between the two light qualities. It has been demonstrated that the five Arabidopsis AHP genes are ubiquitously expressed and unaffected by cytokinin [51]. AHP1, AHP2 and AHP5 overexpression has been found to have no effect on cytokinin primary response gene expression [52]. In addition to IAA, GAs, cytokinins and ABA, the signal transduction pathways of other hormones (ET, BR, JA) were also influenced by red light and blue light (Fig 6). ET, BR and JA all play an important role in the regulation of hypocotyl elongation of Arabidopsis seedlings in response to light [5355]. Ethylene suppress hypocotyl elongation in darkness while promoting it in light [53]. Serine/threonine-protein kinase (CTR1) and EBF1/2, which were repressors in the ethylene signaling pathway, were all upregulated under blue light, whereas an ethylene response transcription factor (ERF1/2) was downregulated under blue light (Fig 6). ERF1 mediates an ethylene activated growth-inhibition pathway that operates effectively in the dark and minimally under strong light conditions in Arabidopsis [53]. JAZ and most of the MYC2 genes were upregulated under blue light in the pathway of JA signal transduction (Fig 6). JAZs are repressors of transcription factors that are positive regulators of JA responses. However, MYC2 acts as a repressor of blue light-mediated photomorphogenic growth in Arabidopsis [54]. Both auxin and brassinosteroid (BR) play an important role in regulating the enhanced hypocotyl elongation of Arabidopsis seedlings in response to blue light depletion [55]. BRI1 is a receptor-like kinase in the BR signaling pathway, which then triggers downstream signaling components. In the present study, most of the BRI1 genes were upregulated in the samples under blue light (Fig 6). BR-regulated plant growth usually depends on an intact auxin signaling pathway [56].

The light spectrum is an important environmental factor that regulates plant growth and development and also influences the secondary metabolism, which acts as de defense compounds [57]. In the present study, blue light promoted phenylpropanoid biosynthesis and phenylalanine metabolism with 90.99% and 98.21% of the genes upregulated, respectively (Table 2). Phenylalanine ammonia-lyase (PAL) is a key enzyme in the phenylpropanoid pathway. The PAL gene is upregulated under blue light (MA_44561g0010, S2 Table), which is consistent with the findings in lettuce (Lactuca sativa L.) [58]. Lignins and flavonols are derived from multiple branches of the phenylpropanoid biosynthesis pathways. In the present study, blue light promoted dirigent gene families, which were related to lignin biosynthesis and conifer defense [59] (S3 Table, Fig 7). Chalcone synthase (CHS), the first enzyme in flavonoid biosynthesis, is only expressed under blue light (MA_84838g0010, S2 Table). In addition, more than 77% genes are upregulated under blue light in flavonoid biosynthesis and flavone and flavonol biosynthesis (Table 2). Blue light facilitates the accumulation of flavonoids in Arabidopsis ([60]), lettuce [58] and Saccharina japonica (Laminariales, Phaeophyceae) [25], which might reduce the primary metabolites for plant growth. There are interaction effects between plant hormones and second metabolism [61]. Flavonoids act as negative regulators of auxin transport in vivo in Arabidopsis [26]. Auxin transport is elevated in the absence of endogenous flavonoids [26]. However, blue light promoted flavonoid biosynthesis of clones with a higher IAA level in the present study, which may be correlation with other hormones. Ethylene may reportedly be involved in regulating light-induced phenylpropanoid accumulation in the tea plant [62].

The qRT-PCR quantification of transcript abundance for eight hormone- and secondary-metabolism-associated genes in the samples under blue and red light for 90 days were similar to those estimated from the RNA-seq, which indicated that the high reliability results had an certain reference value. The time course of apical bud formation in white spruce (Picea glauca) [35] showed that endogenous hormone content and related gene expression level were stable during 70 days under short-day treatment. Possibly, the gene expression level-associated hormone and second metabolism of Norway spruce under long-day treatment for 90 days were also stable. However, this finding requires further verification. A time-course expression analysis of candidate genes involved in plant hormone signal transduction and secondary metabolism under different light treatment should be conducted in the future to determine whether phytohormones are directly or indirectly affected by light quality, as well as their effects on other pathways.

In conclusion, light quality regulates Norway spruce seedling growth and development by mainly affecting the metabolic pathway, biosynthesis of secondary metabolites and plant hormone signal transduction by altering the expression of corresponding genes identified by RNA-seq. Blue light promotes IAA accumulation and second metabolism biosynthesis, and red light promotes GA accumulation in Norway spruce.

Supporting Information

S2 Table. 21,923 unique genes expressed between the two libraries.

https://doi.org/10.1371/journal.pone.0127896.s002

(XLS)

S3 Table. 2,926 DEGs identified between the two libraries.

https://doi.org/10.1371/journal.pone.0127896.s003

(XLS)

S4 Table. GO classification (P-values of less than 0.05) and KEGG pathway (Q-values of less than or equal to 0.05) assignments of DEGs.

https://doi.org/10.1371/journal.pone.0127896.s004

(XLS)

Acknowledgments

This study was supported by a grant from Twelfth Five-Year Plan for Science & Technology Support of China (2012BAD01B01). We give our thanks to Yinan Liu and Yanli Wei for their help in genes heatmap plotting.

Author Contributions

Conceived and designed the experiments: JW SZ. Performed the experiments: FOY JFM. Analyzed the data: FOY JFM. Contributed reagents/materials/analysis tools: JW SZ YL. Wrote the paper: FOY JW YL. Plotted the results: FOY.

References

  1. 1. Mortensen LM, Sandvik M. Light quality and growth of Norway spruce [Picea abies (L.)]. New forests. 1988;2(4):281–7.
  2. 2. Gebauer R, Volařík D, Urban J, Børja I, Nagy NE, Eldhuset TD, et al. Effects of different light conditions on the xylem structure of Norway spruce needles. Trees. 2012;26(4):1079–89.
  3. 3. Chen M, Chory J, Fankhauser C. Light signal transduction in higher plants. Annual Review of Genetics. 2004;38:87–117. pmid:15568973
  4. 4. Olsen JE. Light and temperature sensing and signaling in induction of bud dormancy in woody plants. Plant molecular biology. 2010;73(1–2):37–47. pmid:20490894
  5. 5. Cosgrove DJ. Rapid suppression of growth by blue light occurrence, time course, and general characteristics. Plant Physiology. 1981;67(3):584–90. pmid:16661718
  6. 6. LeonidV K, LindaJ W, Allison H. Interactions between plant hormones and light quality signaling in regulating the shoot growth of Arabidopsis thaliana seedlings. Botany. 2012;90:237–46.
  7. 7. Sellaro R, Hoecker U, Yanovsky M, Chory J, Casal JJ. Synergism of Red and Blue Light in the Control of Arabidopsis Gene Expression and Development. Current Biology. 2009;19(14):1216–20. pmid:19559617
  8. 8. Beel B, Prager K, Spexard M, Sasso S, Weiss D, Müller N, et al. A flavin binding cryptochrome photoreceptor responds to both blue and red light in Chlamydomonas reinhardtii. The Plant Cell Online. 2012;24(7):2992–3008. pmid:22773746
  9. 9. Wang W-J, Wang F-J, Sun X-T, Liu F-L, Liang Z-R. Comparison of transcriptome under red and blue light culture of Saccharina japonica (Phaeophyceae). Planta. 2013;237(4):1123–33. pmid:23277166
  10. 10. Aksenova NP, Konstantinova TN, Sergeeva LI, Macháčková I, Golyanovskaya SA. Morphogenesis of potato plants in vitro. I. Effect of light quality and hormones. Journal of Plant Growth Regulation. 1994;13(3):143–6.
  11. 11. Yu SM, Ramkumar G, Lee Y. Light quality influences the virulence and physiological responses of Colletotrichum acutatum causing anthracnose in pepper plants. Journal of applied microbiology. 2013;115(2):509–16. pmid:23663215
  12. 12. Lu N, Maruo T, Johkan M, Hohjo M, Tsukagoshi S, Ito Y, et al. Effects of supplemental lighting with light-emitting diodes (LEDs) on tomato yield and quality of single-truss tomato plants grown at high planting density. Environmental Control in Biology. 2012;50(1):63–74.
  13. 13. Sellin A, Sack L, Ounapuu E, Karusion A. Impact of light quality on leaf and shoot hydraulic properties: a case study in silver birch (Betula pendula). Plant, cell & environment. 2011;34(7):1079–87.
  14. 14. Fernbach E, Mohr H. Coaction of blue/ultraviolet-A light and light absorbed by phytochrome in controlling growth of pine (Pinus sylestris L.) seedlings. Planta. 1990;180(2):212–6. pmid:24201947
  15. 15. Mølmann JA, Junttila O, Johnsen O, Olsen JE. Effects of red, far-red and blue light in maintaining growth in latitudinal populations of Norway spruce (Picea abies). Plant, cell & environment. 2006;29:166–72.
  16. 16. Quail PH. Photosensory perception and signalling in plant cells: new paradigms? Current Opinion in Cell Biology. 2002;14:180–8. pmid:11891117
  17. 17. Lau OS, Deng XW. Plant hormone signaling lightens up: integrators of light and hormones. Current opinion in plant biology. 2010;13(5):571–7. pmid:20739215
  18. 18. Gaba V, Black M. The control of cell growth by light. Photomorphogenesis: Springer; 1983. p. 358–400.
  19. 19. Olsen J, Junttila O, Nilsen J, Eriksson M, Martinussen I, Olsson O, et al. Ectopic expression of oat phytochrome A in Hybrid aspen changes critical daylength for growth and prevents cold acclimatization. Plant Journal. 1997;12:1339–50.
  20. 20. Kurepin LV, Emery RN, Pharis RP, Reid DM. The interaction of light quality and irradiance with gibberellins, cytokinins and auxin in regulating growth of Helianthus annuus hypocotyls. Plant, cell & environment. 2007;30(2):147–55.
  21. 21. Pierik R, Keuskamp DH, Sasidharan R, Djakovic-Petrovic T, de Wit M, Voesenek LA. Light quality controls shoot elongation through regulation of multiple hormones. Plant Signaling & Behavior. 2009;4(8):755–6.
  22. 22. Zhang Z, Ji R, Li H, Zhao T, Liu J, Lin C, et al. CONSTANS-LIKE 7 (COL7) is Involved in Phytochrome B (phyB) Mediated Light-Quality Regulation of Auxin Homeostasis. Molecular Plant. 2014:ssu058. pmid:24908267
  23. 23. Reddy SK, Finlayson SA. Phytochrome B promotes branching in Arabidopsis by suppressing auxin signaling. Plant physiology. 2014;164(3):1542–50. pmid:24492336
  24. 24. Gubler F, Hughes T, Waterhouse P, Jacobsen J. Regulation of dormancy in barley by blue light and after-ripening: effects on abscisic acid and gibberellin metabolism. Plant Physiology. 2008;147(2):886–96. pmid:18408047
  25. 25. Deng Y, Yao J, Wang X, Guo H, Duan D. Transcriptome sequencing and comparative analysis of Saccharina japonica (Laminariales, Phaeophyceae) under blue light induction. PLoS One. 2012;7(6):e39704. pmid:22761876
  26. 26. Brown DE, Rashotte AM, Murphy AS, Normanly J, Tague BW, Peer WA, et al. Flavonoids act as negative regulators of auxin transport in vivo in Arabidopsis. Plant physiology. 2001;126(2):524–35. pmid:11402184
  27. 27. Nystedt B, Street NR, Wetterbom A, Zuccolo A, Lin Y-C, Scofield DG, et al. The Norway spruce genome sequence and conifer genome evolution. Nature. 2013;497(7451):579–84. pmid:23698360
  28. 28. Weiler E, Jourdan P, Conrad W. Levels of indole-3-acetic acid in intact and decapitated coleoptiles as determined by a specific and highly sensitive solid-phase enzyme immunoassay. Planta. 1981;153(6):561–71. pmid:24275876
  29. 29. Marioni JC, Mason CE, Mane SM. RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays. Genome research, 2008, 18(9): 1509–1517. pmid:18550803
  30. 30. Yakovlev Ia, Fossdal C-G, Johnsen Ø, Junttila O, Skrøppa T. Analysis of gene expression during bud burst initiation in Norway spruce via ESTs from subtracted cDNA libraries. Tree Genetics & Genomes. 2006;2:39–52.
  31. 31. Ma L, Li J, Qu L, Hager J, Chen Z, Zhao H, et al. Light control of Arabidopsis development entails coordinated regulation of genome expression and cellular pathways. The Plant Cell Online. 2001;13(12):2589–607. pmid:11752374
  32. 32. Kircher S, Gil P, Kozma-Bognár L, Fejes E, Speth V, Husselstein-Muller T, et al. Nucleocytoplasmic partitioning of the plant photoreceptors phytochrome A, B, C, D, and E is regulated differentially by light and exhibits a diurnal rhythm. The Plant Cell Online. 2002;14(7):1541–55. pmid:12119373
  33. 33. Fankhauser C, Chory J. Light control of plant development. Annual review of cell and developmental biology. 1997;13(1):203–29.
  34. 34. Kasahara M, Kagawa T, Sato Y, Kiyosue T, Wada M. Phototropins mediate blue and red light-induced chloroplast movements in Physcomitrella patens. Plant physiology. 2004;135(3):1388–97. pmid:15247376
  35. 35. El Kayal W, Allen CCG, Ju CJT, Adams E, King-Jones S, Zaharia LI, et al. Molecular events of apical bud formation in white spruce, Picea glauca. Plant Cell and Environment. 2011;34(3):480–500. pmid:21118421
  36. 36. Kurepin LV, Walton LJ, Hayward A, Emery RN, Pharis RP, Reid DM. Interactions between plant hormones and light quality signaling in regulating the shoot growth of Arabidopsis thaliana seedlings. Botany. 2012;90(3):237–46.
  37. 37. Sun T. Gibberellin-GID1-DELLA: a pivotal regulatory module for plant growth and development. Plant Physiology. 2010;154(2):567–570. pmid:20921186
  38. 38. Lee M-H, Kim B, Song S-K, Heo J-O, Yu N-I, Lee SA, et al. Large-scale analysis of the GRAS gene family in Arabidopsis thaliana. Plant molecular biology. 2008;67(6):659–70. pmid:18500650
  39. 39. Castillon A, Shen H, Huq E. Phytochrome interacting factors:Central players in phytochrome-mediated light signaling networks. Trends of Plant Science. 2007;12:514–21. pmid:17933576
  40. 40. Junttila O, Jensen E. Gibberellins and photoperiodic control of shoot elongation in Salix. Plant physiology. 1988;74::371–6.
  41. 41. Lucas M, Prat S. PIFs get BRright: Phytochrome Interacting Factors as integrators of light and hormonal signals. New Phytologist. 2014;202(4):1126–41. pmid:24571056
  42. 42. Ruttink T, Arend M, Morreel K, Storme V, Rombauts S, Fromm J, et al. A molecular timetable for apical bud formation and dormancy induction in poplar. The Plant Cell Online. 2007;19(8):2370–90. pmid:17693531
  43. 43. Li C, Junttila O, Ernstsen A, Heino P, Palva ET. Photoperiodic control of growth, cold acclimation and dormancy development in silver birch (Betula pendula) ecotypes. Physiologia Plantarum. 2003;117(2):206–12.
  44. 44. Behringer F, Davoes P. Indole-3-acetic acid levels after phytochrome-mediated changes in stem-elongation rate of dark-and light-grown Pisum seedlings. Planta. 1992;188:85–92. pmid:24178203
  45. 45. Olsen JE, Junttila O, Moritz T. Long-day induced bud break in Salix pentandra is associated with transiently elevated levels of GA1 and gradual increase in indole-3-acetic acid. Plant and cell physiology. 1997;38(5):536–40.
  46. 46. Colón-Carmona A, Chen DL, Yeh K-C, Abel S. Aux/IAA proteins are phosphorylated by phytochrome in vitro. Plant Physiology. 2000;124(4):1728–38. pmid:11115889
  47. 47. Reddy SK, Holalu SV, Casal JJ, Finlayson SA. Abscisic acid regulates axillary bud outgrowth responses to the ratio of red to far-red light. Plant physiology. 2013;163(2):1047–58. pmid:23929720
  48. 48. Seo J-K, Kwon S-J, Cho WK, Choi H-S, Kim K-H. Type 2C protein phosphatase is a key regulator of antiviral extreme resistance limiting virus spread. Scientific reports. 2014;4.
  49. 49. Horvath DP, Anderson JV, Chao WS, Foley ME. Knowing when to grow: signals regulating bud dormancy. Trends in plant science. 2003;8(11):534–40. pmid:14607098
  50. 50. Cline MG. The role of hormones in apical dominance. New approaches to an old problem in plant development. Physiologia plantarum. 1994;90(1):230–7.
  51. 51. Tanaka Y, Suzuki T, Yamashino T, Mizuno T. Comparative studies of the AHP histidine-containing phosphotransmitters implicated in His-to-Asp phosphorelay in Arabidopsis thaliana. Bioscience, biotechnology, and biochemistry. 2004;68(2):462–5. pmid:14981318
  52. 52. Yamada H, Suzuki T, Terada K, Takei K, Ishikawa K, Miwa K, et al. The Arabidopsis AHK4 histidine kinase is a cytokinin-binding receptor that transduces cytokinin signals across the membrane. Plant and Cell Physiology. 2001;42(9):1017–23. pmid:11577198
  53. 53. Zhong S, Shi H, Xue C, Wang L, Xi Y, Li J, et al. A molecular framework of light-controlled phytohormone action in Arabidopsis. Current Biology. 2012;22(16):1530–5. pmid:22818915
  54. 54. Yadav V, Mallappa C, Gangappa SN, Bhatia S, Chattopadhyay S. A basic helix-loop-helix transcription factor in Arabidopsis, MYC2, acts as a repressor of blue light—mediated photomorphogenic growth. The Plant Cell Online. 2005;17(7):1953–66. pmid:15923349
  55. 55. Keuskamp DH, Sasidharan R, Vos I, Peeters AJ, Voesenek LA, Pierik R. Blue-light-mediated shade avoidance requires combined auxin and brassinosteroid action in Arabidopsis seedlings. The Plant Journal. 2011;67(2):208–17. pmid:21457374
  56. 56. Zhou X-Y, Song L, Xue H-W. Brassinosteroids regulate the differential growth of Arabidopsis hypocotyls through auxin signaling components IAA19 and ARF7. Molecular plant. 2013;6(3):887–904. pmid:23125315
  57. 57. Awad MA, Wagenmakers PS, de Jager A. Effects of light on flavonoid and chlorogenic acid levels in the skin of ‘Jonagold’apples. Scientia Horticulturae. 2001;88(4):289–98.
  58. 58. Son K H, Oh M M. Leaf shape, growth, and antioxidant phenolic compounds of two lettuce cultivars grown under various combinations of blue and red light-emitting diodes. HortScience. 2013; 48(8): 988–995.
  59. 59. Ralph S, Park J-Y, Bohlmann J, Mansfield SD. Dirigent proteins in conifer defense: gene discovery, phylogeny, and differential wound-and insect-induced expression of a family of DIR and DIR-like genes in spruce (Picea spp.). Plant molecular biology. 2006;60(1):21–40. pmid:16463097
  60. 60. Jenkins GI, Long JC, Wade HK, Shenton MR, Bibikova TN. UV and blue light signalling: pathways regulating chalcone synthase gene expression in Arabidopsis. New Phytologist. 2001;151(1):121–31.
  61. 61. Cheong YH, Chang H-S, Gupta R, Wang X, Zhu T, Luan S. Transcriptional profiling reveals novel interactions between wounding, pathogen, abiotic stress, and hormonal responses in Arabidopsis. Plant Physiology. 2002;129(2):661–77. pmid:12068110
  62. 62. Wang Y, Gao L, Wang Z, Liu Y, Sun M, Yang D, et al. Light-induced expression of genes involved in phenylpropanoid biosynthetic pathways in callus of tea (Camellia sinensis (L.) O. Kuntze). Scientia Horticulturae. 2012;133:72–83.