Transcriptome analysis of shade avoidance and shade tolerance in conifers
Gymnosperms respond differently to light intensity and R:FR; although some aspects of shade response appear conserved, yet underlying mechanisms seem to be diverse in gymnosperms as compared to angiosperms.
Shade avoidance syndrome (SAS) is well-characterized in the shade intolerant model species Arabidopsis thaliana whereas much less is known about shade tolerance response (STR), yet regulation of SAS and STR with reference to conifers remains poorly understood. We conducted a comparative study of two conifer species with contrasting responses to shade, Scots pine (shade-intolerant) and Norway spruce (shade-tolerant), with the aim to understand mechanisms behind SAS and STR in conifers. Pine and spruce seedlings were grown under controlled light and shade conditions, and hypocotyl and seedling elongation following different light treatments were determined in both species as indicators of shade responses. Red to far-red light ratio (R:FR) was shown to trigger the shade response in Norway spruce. In Scots pine, we observed an interaction between R:FR and light intensity. RNA sequencing (RNA-Seq) data revealed that SAS and STR responses included changes in expression of genes involved primarily in hormone signalling and pigment biosynthesis. From the RNA-Seq analysis, we propose that although some aspects of shade response appear to be conserved in angiosperms and gymnosperms, yet the underlying mechanisms may be different in gymnosperms that warrants further research.
KeywordsGymnosperms Light intensity Norway spruce Phytochrome B Pigment synthesis R:FR ratio RNA sequencing Scots pine Seedling morphology
Arabidopsis thaliana ethylene responsive element binding factors
Early light-induced protein 2
Light-harvesting chlorophyll-binding protein complex
Red to far-red ratio
Lower (root) to upper (hypocotyl + cotyledon) growth ratio
Shade avoidance syndrome
Shade tolerance response
Hypocotyl + root
Plants have developed sophisticated mechanisms to sense and respond to light duration, intensity and quality. Multiple wavelengths of the light spectrum are of biological significance in addition to the photosynthetically active radiation (PAR) (400–700 nm). The red (R, 660 nm) to far-red (FR, 730 nm) ratio (R:FR) is an indicator of the degree of shade with low values activating both shade avoidance and tolerance responses (Ballare et al. 1987; Gommers et al. 2013). In a fully light exposed area at midday, the R:FR ratio was reported to be 1.2 (Warrington et al. 1989; Smith 1994), whereas under vegetative shade the R light is largely absorbed by the chlorophyll and other leaf pigments while the FR is transmitted or reflected, resulting in a decrease in R:FR ratio to 0.2–0.8 (Ballare et al. 1987). Similarly, a decrease in R:FR ratio occurs during the twilight hours largely due to the longer path length of the light through the ozone layer which absorbs in the red–green region of the spectrum that results in a relative increase in blue and FR light (Attridge 1990).
Shade is perceived by the plants as decrease in the R:FR ratio, where there is higher FR than R. The study by Fernbach and Mohr (1990) on the Scots pine hypocotyl growth reported the absence of high irradiance response (HIR) (i.e., a lack of hypocotyl growth inhibition under FR), whereas presence of HIR under FR is a common feature in the angiosperms. Thus gymnosperms respond to light quality in a different way as compared to angiosperms. In gymnosperms as well as in angiosperms, the extent of vegetative response to shade differs between species depending on their level of tolerance to shade (Hoddinott and Scott 1996; Humbert et al. 2007). Shade tolerance is a function of the capacity of a particular species to efficiently modify its morphology to adapt and respond to low light intensities and low R:FR ratio, in addition to change the carbon allocation from photosynthetic activity to elongation (Valladares and Niinemets 2008; Giertych et al. 2015). Comparative studies of species with different levels of shade tolerance have been proven as an optimal experimental set up to study the mechanisms governing response to shade in both angiosperms (Sefcik et al. 2006) and gymnosperms (Peer et al. 1999).
A significant amount of research has been devoted to study the eco-physiological consequences of exposure to shade in angiosperms (Valladares and Niinemets 2008) and conifers (Warrington et al. 1989; Hoddinott and Scott 1996). In A. thaliana, the shade avoidance syndrome (SAS) is well-characterized and primarily involves the phytochromes, PhyA and PhyB, and the downstream genes required for the integration between the light and hormone signalling pathways (Yang and Li 2017). Shade reduces phyB activity, which increases the mRNA levels of basic helix–loop–helix (bHLH) transcription factors such as phytochrome interacting factors (PIF) (Lorrain et al. 2008). PIFs regulate a large number of genes encoding metabolic enzymes and genes in the signalling pathways of the phytohormones (Ballare and Pierik 2017). The shade tolerance response (STR) has so far attracted less attention (Gommers et al. 2013). Recently, a RNA sequencing comparative study between two Geranium species from different native light environments revealed that STR and SAS share a common phytochrome-mediated mechanism with contrasting patterns of gene expression for the control of immunity and shoot elongation (Gommers et al. 2017). Genes involved in the SAS/STR in conifers remain unexplored, therefore we performed the whole-genome expression study using RNA sequencing (RNA-Seq) to get an overview of the biological pathways and molecular mechanisms that regulate SAS/STR and also to suggest potential candidates involved in the mechanism.
In this study, we aimed to advance our knowledge on the following: (1) Scots pine and Norway spruce as a model system for shade response studies, (2) the effect of R:FR and light intensity on the response to shade in seedlings and (3) the mechanism governing the SAS and the STR in conifers. To address this, seeds from Scots pine and Norway spruce were grown under constant light with contrasting R:FR (SUN-like 1.2 and SHADE-like 0.2) and light intensities. Hypocotyl (HYP), root (ROOT) and cotyledon (COT) lengths were determined in fully developed seedlings under the different light regimes, and the seedlings were analysed for whole genome expression using RNA-Seq.
Materials and methods
Scots pine and Norway spruce seeds were collected from 70 unrelated trees from a Swedish natural population in Kaunisvaara (67°N 5′N). To ensure low consanguinity and to capture a representation of the population diversity, trees were collected at a distance of minimum 50 meters from each other. Cones were dried with warm air to force release the seeds. Sound seeds were separated from the empty seeds by flotation. The percentage of germination was obtained by germinating soaked seeds on paper discs on a warm bench with controlled humidity and temperature. The percentage of germination was of 98% on a batch of 200 seeds (5 seeds per tree).
Seed germination and light treatment
R:FR 0.2 (36 µmol m−2 s−1)
R (6 µmol m−2 s−1):FR (30 µmol m−2 s−1)
R:FR 1.2 (65 µmol m−2 s−1)
R (35 µmol m−2 s−1):FR (30 µmol m−2 s−1)
R:FR = 0.2 (65 µmol m−2 s−1)
R (11 µmol m−2 s−1):FR (54 µmol m−2 s−1)
R:FR 1.2 (20 µmol m−2 s−1)
R (11 µmol m−2 s−1):FR (9 µmol m−2 s−1)
Absence of light
Length of hypocotyl (HYP), root (ROOT) and cotyledon (COT), the lower (root) to upper (hypocotyl + cotyledon) growth ratio (ROOT_HYPCOT) and hypocotyl + root (TOTAL_LENGTH) were scored at the mm precision for each seedling at the seedling developmental stage where hypocotyl was fully developed (Ranade and García-Gil 2013).
Three biological replicates were prepared for each of the light treatments—A (SHADE), B (SUN) and DARK (control), for RNA extraction for Scots pine and Norway spruce. The biological replicates were prepared by pooling three seedlings per sample to reduce variation between replicates and to increase the statistical power of the analysis (i.e. increased sensitivity to detect genes that are differentially expressed between conditions).
Total RNA was isolated using Spectrum Plant Total RNA Kit (Sigma) following the manufacturer’s instructions. The mRNA concentration and quality was determined using NanoDrop-2000 spectrophotometer (Thermo Fisher Scientific Inc.) and Bioanalyzer 2100 (Agilent Technologies Inc.), respectively. RNA library preparation and subsequent sequencing were performed at SciLifeLab (Stockholm, Sweden). Strand-specific RNA libraries for sequencing were prepared with TruSeq Stranded mRNA Sample prep kit of 96 dual indexes (Illumina) according to the manufacturer’s instructions except for the following changes: the protocols were automated in Agilent NGS workstation (Agilent Technologies) using purification steps as described in Lundin et al. (2010) and Borgstrom et al. (2011). Clonal clusters were generated using cBot (Illumina) and sequenced on HiSeq 2500 (Illumina) according to manufacturer’s instructions. Bcl to Fastq conversion was performed with bcl2Fastq v1.8.3 from the CASAVA software suite. The quality scale was Sanger/phred33/Illumina 1.8 + . The obtained data was deposited to the ENA and is accessible under the accession number RJEB19683.
Pre-processing of RNA-Seq data and differential expression analyses
The data pre-processing was performed as described here: http://www.epigenesys.eu/en/protocols/bio-informatics/1283-guidelines-for-rna-seq-data-analysis. Briefly, the quality of the raw sequence data was assessed using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Residual ribosomal RNA (rRNA) contamination was assessed and filtered using SortMeRNA (v2.1; (Kopylova et al. 2012); settings –log –paired_in –fastx–sam –num_alignments 1) using the rRNA sequences provided with SortMeRNA (rfam-5s-database-id98.fasta, rfam-5.8s-database-id98.fasta, silva-arc-16s-database-id95.fasta, silva-bac-16s-database-id85.fasta, silva-euk-18s-database-id95.fasta, silva-arc-23s-database-id98.fasta, silva-bac-23s-database-id98.fasta and silva-euk-28s-database-id98.fasta). Data was then filtered to remove adapters and trimmed for quality using Trimmomatic (v0.32; (Bolger et al. 2014); settings TruSeq 3-PE-2.fa:2:30:10 SLIDINGWINDOW:5:20 MINLEN:50). After both filtering steps, FastQC was run again to ensure that no technical artefacts were introduced. Filtered reads were aligned to v1.0 of the P. abies genome (retrieved from the PopGenIE resource; Sundell et al. 2015) using STAR (v2.4.0f1; Dobin et al. 2013); non- default settings: –outSAMstrandField intronMotif –readFilesCommand zcat –outSAMmapqUnique 254 –quantMode TranscriptomeSAM –outFilterMultimapNmax 100 –outReadsUnmapped Fastx –chimSegmentMin 1 –outSAMtype BAM SortedByCoordinate –outWigType bedGraph –alignIntronMax 11000). The annotations obtained from the P. abies v1.0 GFF file contain only one transcript per gene-model, and as such, did not need to be modified to generate ‘synthetic’ gene models. This GFF file and the STAR read alignments were used as input to the HTSeq (Anders et al. 2015) htseq-count python utility to calculate exon-based read count values. The htseq-count utility takes only uniquely mapping reads into account. The Scots pine samples were processed similarly, but aligned to the v1.01 of the P. taeda genome (Zimin et al. 2014) and its annotation retrieved from http://pinegenome.org/pinerefseq/. The biological relevance of the data—e.g. biological replicates similarity—was assessed by Principal Component Analysis (PCA) and other visualisations (e.g. heatmaps), using custom R scripts.
Seedling morphology traits
Seedling morphology data were converted into percentage of change with respect to DARK (100%). Analysis of variance (ANOVA) was applied to estimate the significance of the light treatment effect. Principal Component Analysis (PCA), ANOVA and Duncan post hoc tests were conducted using R software (R Development Core Team 2015).
Differential expression analysis
Genes involved in shade avoidance syndrome (SAS) were defined as those that were significantly differentially expressed between treatments A (SHADE, R:FR = 0.2) and B (SUN, R:FR = 1.2) in Scots pine (shade-intolerant), while not being differentially expressed in Norway spruce (shade-tolerant). Genes involved in shade tolerance response (STR) were defined as those that were significantly differentially expressed between the treatments A and B in Norway spruce (shade-tolerant), while not being differentially expressed in Scots pine (shade-intolerant). A third group of genes refers to those that were significantly differentially expressed between the treatments A and B in both species, but in opposite direction (i.e., up-regulated under SHADE in Scots pine and down-regulated under SHADE in Norway spruce (Pine_up_Spruce_down) or down-regulated under SHADE in Scots pine and up-regulated under SHADE in Norway spruce (Pine_down_Spruce_up)). The third group of genes would refer to those genes that were functionally active in shade response in both species.
Statistical analysis of single-gene differential expression was performed in R (v3.3.0; R Development Core Team 2015) using the Bioconductor (v3.3; Gentleman et al. 2004) DESeq 2 package (v1.12.0; Love et al. 2014). FDR adjusted P values were used to assess significance; a common threshold of 1% was used throughout. For the data quality assessment (QA) and visualisation, the read counts were normalised using a variance stabilizing transformation as implemented in DESeq 2.
Alignment of PHYA and PHYB
Multiple alignment of PHYA and PHYB respectively was carried out using CLUSTAL 2.1 multiple sequence alignment program. We used amino acid sequences from several shade tolerant and shade intolerant species from both angiosperms and gymnosperms.
Effect of shade on seedling morphology
Overall, ROOT was longer in Norway spruce than in Scots pine (Fig. 1a). In both species, SHADE (A and C) inhibited ROOT as compared to SUN (B). In Scots pine, treatment A (SHADE) showed a significantly higher inhibitory effect compared to the treatment C (SHADE) indicating that ROOT is more sensitive to the light intensity than HYP. In Norway spruce, however, both SHADE treatments had similar inhibitory effect on ROOT growth. Overall, ROOT was inhibited by SHADE in both species, which does not support a distinction between species on their level of shade tolerance. In the case of Norway spruce, inhibition of ROOT by treatment D was similar to both SHADE treatments, whereas in Scots pine treatment D inhibitory effect resembled treatment C. Similar to HYP, these results support the importance of light intensity as a factor determining seedling development.
COT length was longer in treatment B and C as compared to treatment A and D in Scots pine (Fig. 1a). In Norway spruce, COT length was similar in all treatments except for treatment B (SUN); COT length was longer under treatment B compared to all other treatments. Further, under treatment A and D, COT length was similar in both species. In Scots pine, COT was inhibited by SHADE, but more intensively by treatment A as compared to treatment C. In Norway spruce, both SHADE treatments equally inhibited COT elongation. As in the case of ROOT, COT response to SHADE did not agree with the species claimed differential response to SHADE. In Scots pine, treatment D inhibited COT elongation similarly to treatment A, whereas in Norway spruce the inhibitory effect of treatment D was equal to that of both SHADE treatments (A and C). Once again, these results support the role of light intensity as a key factor in the control of seedling growth even under contrasting R:FR values (see the effect of A and D with respect to B).
Irrespective of treatment, the ROOT_HYPCOT was higher in Norway spruce (Fig. 1a). In both species, the ROOT_HYPCOT decreased in a similar manner in response to both SHADE treatments (A and C). Also for this trait (as in case of ROOT), the differential effect of shade and sun did not reveal the difference in the level of shade tolerance between both species. In the case of Norway spruce, the effect of treatment D was significantly higher as compared to treatments A and C, indicating that this trait is very sensitive to low intensity. In the case of Scots pine, treatment D caused a decrease in the trait value at similar and intermediate level between SUN treatment B and the SHADE treatments. Thus, ROOT_HYPCOT also revealed the role of light intensity as a shade factor that interacts with the light quality composition (even if treatment A and D both have low intensity, depending on the trait they show similar or dissimilar effects).
ANOVA and Duncan post hoc test revealed two different patterns of the TOTAL_LENGTH in response to SHADE (treatments A and C) versus SUN (treatment B) (Fig. 1b; Suppl. Table S2). In Scots pine, treatment C (SHADE) caused a significant increase of the TOTAL_LENGTH as compared to treatment B (SUN) and treatment A (SHADE, low light intensity), both A and B having similar effect on the TOTAL_LENGTH (Suppl. Table S2). Instead, in Norway spruce, both the SHADE treatments decreased the TOTAL_LENGTH equally with respect to the SUN treatment. Overall, it indicates that Scots pine responds to SHADE by reallocating resources (i.e., increase in hypocotyl is compensated by a repression of root elongation), while Norway spruce responds to shade by decelerating seedling growth (i.e., maintaining hypocotyl length similar to sun conditions and repressing root elongation). RNA sequencing was performed using pine and spruce seedlings grown under treatment A (SHADE) and B (SUN) as the phenotypic response (e.g. hypocotyl elongation) under these treatments in both species was determined to be the strongest among all.
Genes involved in shade avoidance (SAS) and tolerance (STS) in conifers
Chi-square analysis supported a higher number of the SAS genes being down-regulated by SHADE (661) as compared to the genes up-regulated by SHADE (271) (P value < 0.0001), whereas there were similar number of the STR genes which were found to be down-regulated by SHADE (247) and up-regulated by SHADE (201) (P value = 0.10). We also detected a few genes that were differentially regulated between the SUN and SHADE conditions in both species. We classified them into two groups, one refers to the genes that were up-regulated by SHADE in Scots pine and down-regulated by SHADE in Norway spruce (Pine_up_Spruce_down, Suppl. Table S5); there were 12 such genes. The other group involves genes that were down-regulated by SHADE in Scots pine and up-regulated by SHADE in Norway spruce (Pine_down_Spruce_up, Suppl. Table S6); there were 22 genes in this category. An overview of the data, including raw and post-QC read counts, and alignment rates is provided in Suppl. Table S7. A total of 84518 and 70736 expressed genes were sequenced in Scots pine and Norway spruce, respectively.
We compared the SAS response in Scots pine to the well-characterized shade-intolerant A. thaliana but since STR appears to be less explored in this context, there are limitations to compare the genes involved in STR with a well-studied model system.
Analysis of the classical SAS genes in conifers
Multiple studies have shown a decrease in anthocyanin synthesis in response to low R:FR in angiosperms (Alokam et al. 2002; Cagnola et al. 2012). In gymnosperms, anthocyanin synthesis in response to shade seems to be species dependent; reduced anthocyanin accumulation was observed in Sequoia sempervirens (Peer et al. 1999) in contrast to increased anthocyanin accumulation reported in Scots pine (Razzak et al. 2017). Razzak et al. (2017) demonstrated that anthocyanin level increased gradually with increase in light intensity for both R and FR light in Scots pine (monochromatic light treatments); anthocyanin accumulation increased significantly under SHADE condition (R:FR 0.25) as compared to the SUN condition (R:FR 1.2). Likewise, dihydroflavonol 4-reductase (DFR), involved in anthocyanin biosynthesis pathway was found to be up-regulated in pine, whereas it was downregulated in spruce under shade. Ribonuclease 1 (RNS1) was reported to inhibit anthocyanin accumulation in A. thaliana (Bariola et al. 1999); congruently, we found RNS1 to be down-regulated in Norway spruce. On the other hand, flavanone 3-hydroxylase (F3H) and leucoanthocyanidin dioxygenase (ANS/LDOX) which are involved in anthocyanin biosynthesis (Petroni and Tonelli 2011), were down-regulated by shade in Norway spruce. Overall, our results are not conclusive about the possible role of anthocyanin in shade tolerance in conifers.
None of the candidate genes selected by Gommers et al. (2017) from the transcriptome analysis in response to low R:FR in Geraniums, were found to be associated with SAS or STR in the current study in conifers. Yet, few genes that were listed to be differentially expressed in the two Geranium species were found to be associated with SAS in Scots pine; genes that were down-regulated under shade in Scots pine include—ONE-HELIX PROTEIN 2 (associated with PSI), PHOTOSYSTEM II SUBUNIT P-1 (associated with PSII), RIBULOSE BISPHOSPHATE CARBOXYLASE SMALL CHAIN 1A (photosynthetic activity) and SIGMA FACTOR E (plastid gene regulation).
Transcription factors (TF) involved in SAS and STR
Expression of PHY genes in the conifer species, the major contributors to SAS in A. thaliana
The SAS molecular control is well-characterized in A. thaliana (Devlin et al. 2003; Franklin et al. 2003; Martinez-Garcia et al. 2014), whereas little is known about the molecular mechanisms that control shade tolerance, and the lack of knowledge is even more evident with reference to both types of shade responses (tolerance and avoidance) in conifers. Gommers et al. (2013) suggested three hypothetical models for the molecular regulation of shade tolerance, one of which involves alterations in the molecular structure of PHYA to increase phyA stability and, consequently, suppression of hypocotyl elongation antagonistically to the PhyB-mediated SAS response. In addition, in A. thaliana both PHYA and PHYB expressions are known to be rapidly up-regulated following exposure to shade (Devlin et al. 2003; Martinez-Garcia et al. 2014). Our RNA-Seq data revealed no changes in PHYN/A expression in either species, while PHYP2/B was found to be down-regulated by shade in the shade-intolerant species (Scots pine) and up-regulated in the shade tolerant species (Norway spruce). The results are in contrast to what has been reported in A. thaliana thus leaving the intriguing possibility that the phytochrome differentially regulates shade response in angiosperms and gymnosperms. Association of differentially expressed PHYB under low R:FR light in the two Geranium species with contrasting responses to shade was reported by Gommers et al. (2017). We conducted an alignment of both PHYN/A and PHYP/B gene sequences where we included multiple angiosperm and gymnosperm species from both the shade response categories—shade tolerant and shade intolerant (Suppl. Fig. S5). This exercise revealed multiple non-synonymous polymorphic sites associated to their shade response category rather than to their phylogenetic one, thus indicating that even if there is no co-relation between the mode of phytochrome expression in response to shade between angiosperms and gymnosperms, it is still possible that they share a similar mode of action which warrants further research. Moreover, a few amino acid positions in the PHYA and PHYB were conserved among the angiosperms and among the gymnosperms, irrespective of the shade response category. A polymorphism I143L in PHYB of A. thaliana is associated with variation in red light response (Filiault et al. 2008); presence of leucine at the corresponding position in all the gymnosperm species included in the alignment indicates that gymnosperms will respond to red light in a different manner than the angiosperms. This suggests that due to the sequence variability, phytochromes may attain a different conformation leading to distinct biochemical properties and functions in the two groups.
Jasmonic acid (JA) and salicylic acid (SA) pathways
Suppression of JA-mediated defence against biotic stress is a strategy to prioritize the SAS over other stresses (de Wit et al. 2013; Leone et al. 2014; Xu et al. 2016). The Skp1/Cullin/F-box E3 ubiquitin ligase complex (SCFCOI1) containing coronatine-insensitive protein 1 (COI1) activates JA-dependent responses (Devoto et al. 2002). SCFCOI1 degrades jasmonate-zim-domain (JAZ) proteins, which are known repressors of JA signalling (Kazan and Manners 2012). Jasmonate-zim-domain protein 3 (JAZ3), known to act as a negative regulator of JA signalling (Kazan and Manners 2012) was found to be down-regulated in Scots pine in response to shade which seems contradictory to the shade intolerant nature of the species.
Arabidopsis thaliana ethylene responsive element binding factors (ATERFs) are primarily involved in biotic stress responses; however, some ERFs have also been characterized as being responsive to abiotic stress such as temperature, drought and wounding (Fujimoto et al. 2000). ATERF1 is a downstream element of the ethylene and jasmonate pathways, and participates in the regulation of defence-related genes (Lorenzo et al. 2003). Like-wise, basic endochitinase B (CHI-B) encodes a basic chitinase involved in ethylene/JA-mediated signalling pathway, which renders defence against chitin-containing fungal pathogens (Thomma et al. 1998). Down-regulation of ATERF5 in spruce and up-regulation of ATERF1 expression in pine in response to shade again contradicts the suppression of JA-mediated defence in SAS. However, up-regulation of CHI-B in spruce and insignificant CHI-B expression in pine under shade is in accordance with the suppression of defence mechanism during SAS response.
Salicylic acid (SA) pathway is also known to be repressed under shade (de Wit et al. 2013). Arabidopsis thaliana methyl esterase 1 (ATMES1) and other members of the ATMES gene family regulate interaction between SA and JA through regulation of the levels of their respective methylated derivatives (Dempsey et al. 2011). ATMES1 which is involved in SA hydrolysis (Vlot et al. 2008) was found to be down-regulated in Scots pine, challenging the known suppression of SA in the SAS. Arabidopsis thaliana phytoalexin deficient 4 (ATPAD4) functions in SA-dependent defence signalling by interacting with another lipase-like protein (A. thaliana enhanced disease susceptibility 1, AtEDS1), in a positive feedback loop to promote SA biosynthesis (Glazebrook et al. 1997). ATPAD4 was down-regulated by shade in the shade-intolerant Scots pine supporting its role in the SAS activation through diminishing SA signal. To the best of our knowledge, this gene has not been previously associated to the SAS. In Norway spruce, phenylalanine ammonia-lyase 2 (PAL2), a gene that mediates SA synthesis (Chen et al. 2009), was detected to be up-regulated by shade suggesting a role of SA in the STR.
Genes related to defence response
Analysis of the genes that belong to GO categories such as defence response, immune response and acquired resistance shows a higher number of defence-related genes being down-regulated by SHADE (48) as compared to the genes up-regulated by SHADE (28) (P value = 0.02) in pine, whereas similar number of genes were down-regulated (18) and up-regulated by SHADE (26) (P value = 0.23) in spruce. Therefore, from the expression analysis we speculate that SAS in conifers is associated with reduced defence response making the plant prone to diseases which is in accordance with the studies in A. thaliana where it was demonstrated that low R:FR light down-regulates the defence pathways making the plant more susceptible to pathogens (Cerrudo et al. 2012; de Wit et al. 2013; Chico et al. 2014).
Comparison between gene expression patterns in response to shade in A. thaliana and conifers
Comparison between genes involved in shade response in A. thaliana and conifers
Plays role in shade-induced elongation growth
↑ Auxin biosynthesis
Yang and Li (2017)
AUX/IAA-responsive genes—SAUR-like auxin-responsive proteins
Regulate plant growth and development
↓ SAUR32 under light enriched in FR
↑ SAUR76 under light enriched in FR
SAUR15, SAUR67 under shade
↓ SAUR32, SAUR76, SAUR70 under shade
↑ SAUR12 under shade
↓ SAUR70 under shade
ATHB—HD-Zip class II subfamily transcription factor
Promotes hypocotyl growth by modifying the responsiveness to AUX/IAA
↑ ATHB2 and ATHB6 under low R:FR
↓ ATHB6 and ATHB15 under
Gretchen Hagen 3 (GH3)
Involved in auxin homeostasis
↑ GH3.3 and GH3.4 after 1 h under FR
↓ GH3.3 and GH3.9 after 24 h under FR
↑ GH3.17 under shade
Leivar et al. (2012b)
ATP binding cassette subfamily B (ABCB)
ABCB family members mediate auxin efflux
ABCB-mediated auxin transport required for shade-induced hypocotyl elongation
↓ ABCB4, ABCB19 under shade
Ge et al. (2017)
Auxin1/like AUX (AUX/LAX)-LAX2
LAX2-transporter of auxin
↑ LAX2 under shade
Swarup and Péret (2012)
Auxin response factors (ARFs)
Mediate auxin regulation of multiple processes
↓ ARF11, ARF18 under FR
↓ ARF16 under shade
Leivar et al. (2012b)
Brassinosteroid (BR) regulates photomorphogenesis, promotion of stem growth under shade
Yang and Li (2017)
BRI1-EMS-SUPPRESSOR 1 (BES1) homolog protein 1-(BEH1)
BEH1 mediates brassinosteroid-induced growth
↓ BEH1 under shade
Promotes expression of BR target genes
↑ MYB30 under shade
↑ GA under shade
↑ Gibberellin-regulated family proteins under shade-(AT1G74670, AT1G22690)
↑ Gibberellin-regulated family proteins under shade-(AT2G18420, AT2G39540)
Yang and Li (2017)
Shade avoidance and shade tolerance are different plant strategies to optimize photosynthesis in response to shade. These two shade-response strategies are also found in conifer species, where pine species are considered to have a lower level of shade tolerance compared to spruce species (Warrington et al. 1989; Hoddinott and Scott 1996). R:FR ratio is considered a reliable indicator of the degree of shade and its low values are associated with shade avoiding and shade tolerance responses. Here we demonstrate the distinct morphological and transcriptional changes in response to shade in two conifer species with contrasting levels of shade tolerance; Scots pine, shade-intolerant, and Norway spruce, shade-tolerant.
In our comparative system, Scots pine versus Norway spruce, hypocotyl and total seedling elongation in response to shade reflect the level of the species shade tolerance, whereas this is not the case for root, cotyledons and root to aerial tissue ratio responses, suggesting that hypocotyl and seedling elongation should be the shade response markers for further physiological studies in conifers. Previous studies with simulated shade reported plant elongation associated to shade intolerant species as compared to tolerant ones in angiosperms (Gommers et al. 2017) and gymnosperms (Hoddinott and Scott 1996). Furthermore, our results indicate that differences in shade tolerance between both conifer species could be related to differences in carbon re allocation. In Scots pine, carbon accumulates in the stem at the expense of root and cotyledon development. On the contrary, Norway spruce seems to respond to shade with an overall decrease in biomass production. This interpretation agrees with the previously proposed “carbon gain hypothesis” that defines shade-tolerant species and involvement of maximization of light capture (i.e., increase in specific leaf area and chlorophyll content) together with a scant trunk elongation and growth as compared to the shade-intolerant species where stem elongation aims to outreach light as a strategy to survive (Valladares and Niinemets 2008; Hallik et al. 2009; Modrzynski et al. 2015).
We investigated the relative effect of R:FR and light intensity in seedling development in both conifer species. Scots pine and Norway spruce were exposed to two simulated shade conditions (SHADE, R:FR = 0.2) with different light intensities (36 and 65 µmol m−2 s−1, treatment A and C, respectively) and two simulated sunny conditions (SUN, R:FR = 1.2) with contrasting light intensities (65 and 20 µmol m−2 s−1, treatment B and D, respectively). Our results suggest that response to shade is essentially triggered by changes in R:FR; low light intensity under shade (low R:FR) can amplify the shade response, at least in the case of Scots pine, and can also trigger the shade response even under low light intensity with sunny conditions (high R:FR). In a recent study in Scots pine, the role of light intensity in the modulation of response to FR and R wavelengths was demonstrated (Razzak et al. 2017). In Norway spruce, however, the low R:FR value overrides the effect of light intensity, at least for the assayed conditions, as the seedling growth responds similarly to both SHADE treatments (despite differences in light intensity).
Our third research question was to identify the potential candidate genes involved in the regulation SAS and STR in conifers; we compared the expression profiling (RNA-Seq) between seedlings of Scots pine (shade intolerant) and Norway spruce (shade tolerant). As a first exploratory approach of the RNA-Seq data, the gene count already revealed interesting results. Firstly, 67% of the genes showing a significant response to shade were associated to the SAS; secondly, among those genes, 63% were down-regulated, whereas among the STR genes the proportion of up-regulated and down-regulated genes was similar. These two outcomes provide evidences that the shade-tolerant species also adapts to shade by altering the transcriptional level of multiple genes (see PCA and Heatmaps). However, there are clear differences in the extent and main direction of those transcriptional alterations.
Our transcriptome analysis provides evidences about the involvement of pigment and hormone biosynthetic pathways in SAS and STR responses in conifers in a comparable way to what has been previously described in angiosperms (Nozue et al. 2015; Gommers et al. 2017; Yang and Li 2017). Although we suggest a few potential candidates involved in the SAS/STR mechanisms in conifers, further investigation is required to resolve the phenomenon. We have identified a number of major gene family players associated to SAS or STR in conifers which were previously found to be associated to the SAS in angiosperms, e.g. pathways involving auxin/indole-3-acetic acid (AUX/IAA), brassinosteroid, ethylene, gibberellins (GAs), JA and SA. Some of those gene families, such as SAURs and auxin response factors (ARFs) from the AUX/IAA pathways, seemed to involve a highly dynamic feedback mechanism that regulates the auxin cellular levels characterized by a rapid and transient enrichment in these genes (Ciolfi et al. 2013; Ren and Gray 2015) which indicates that the experimental design also in terms of duration of the light treatment will affect the level of expression. Similar feed-back regulatory evidences were also detected in gene families from the other hormonal and anthocyanin biosynthesis pathways. For example, up-regulation of GA20OX3 is described as conditional to the amount of gibberellin hormone, where high levels of gibberellin inhibit GA20OX3 expression (Sun 2008). Association of SAS with suppression of JA and SA mediated responses involved in plant defence against insect/pathogen and disease resistance is well characterised in A. thaliana; JA-mediated defences are repressed by low R:FR in shade-intolerant but enhanced in shade-tolerant wild species (Gommers et al. 2017). In the current work, although the expression of few genes (JAZ3, ATERF, ATMES1) related to JA/SA-pathway was found to be contradictory with reference to SAS/STR, analysis of genes that belong to the GO categories related to defence response supports that SAS in conifers is associated with reduced defence response, whereas defence mechanism remains unaffected in STR. Thus, the suppression of defence mechanism appears to be conserved in conifers but the underlying regulatory network differs from angiosperms. Although significant progress have been made to decipher the complex regulatory mechanisms that operate through the interaction of JA–SA signalling which controls the defence strategies in angiosperms, the molecular mechanisms in conifers still needs to be explored.
Consistently with previous studies where reduction in chlorophyll content has been associated to shade avoidance in A. thaliana (McLaren and Smith 1978; Smith and Whitelam 1997) and in Scots pine (Razzak et al. 2017), we have found several genes from the chlorophyll biosynthesis pathway, which were down-regulated in pine: LHCA1, LHCA3, LHCA4, LHCB7, LIL3:1, HCF173, PORC, CHLM, CHL and CPO. Moreover, down-regulation of pheophytinase (PPH) and accelerated cell death 2 (ACD2) in Scots pine, two genes known to mediate chlorophyll-breakdown (Eckhardt et al. 2004; Zhang et al. 2014), suggests that chlorophyll synthesis during the SAS is also affected by feedback regulatory mechanisms. The LHC genes associated with SAS in the current study were different than those which were found to be differentially expressed under low R:FR light in the two Geranium species with contrasting responses to shade (LHCA6, LHCB4.1, LHCB5) (Gommers et al. 2017). Our study has also contributed with evidences about chlorophyll accumulation during the STR, concluded from the expression pattern observed for ELIP2 and PORB genes. In the literature, increased chlorophyll content has been suggested as an adaptive mechanism exhibited by the shade-tolerant species which involves maximization of light capture (Valladares and Niinemets 2008). Increase in chlorophyll content contrasts with a lower number of GO cellular components such as chloroplast activity in STR as compared to SAS. One possible interpretation is that during the process of plant response to shade the aim is to optimize light acquisition while maintaining growth to a low rate (Loach 1967; Valladares and Niinemets 2008; Hallik et al. 2009; Modrzynski et al. 2015). In A. thaliana, ELIP2 was reported to be associated to FR response (Leivar et al. 2012a), whereas, to our knowledge, HCF173, CHL, LHCA4, CPO, PORB, LIL3:1, CHLM and PORC have not been previously linked to shade response.
LATE ELONGATED HYPOCOTYL (LHY), a TF from MYB family was found to be repressed by shade in association with SAS in pine; LHY plays key role in the circadian oscillator in A. thaliana and its involvement in shade avoidance in A. thaliana is not established (Mizoguchi et al. 2002), but an ortholog of LHY was down-regulated under shade in maize (Wang et al. 2016). PHYTOCLOCK 1 (PCL1), a G2-like TF family member, which is characterised as circadian clock gene (Onai and Ishiura 2005), is found to be up-regulated by shade with reference to SAS. LEAFY (LFY TF family) is a meristem identity regulator and it targets LATE MERISTEM IDENTITY2 (LMI2) (MYB TF family) that has a role in the meristem identity transition. Thus, LFY plays a role in floral meristem development and promotes transition from vegetative growth to flowering (Pastore et al. 2011). Both LEAFY and LMI2 were up-regulated in pine in response to shade. STERILE APETALA (SAP) is a transcription regulator essential for the maintenance of floral identity acting in a similar manner as APETALA1 (Byzova et al. 1999), which was found to be co-expressed with LHY under shade in pine. Changes to the circadian clock and early flowering are one of the major components of the shade avoidance response as reported in A. thaliana (Adams et al. 2009; Ciolfi et al. 2013); thus involvement of circadian and flowering genes in shade avoidance response appears to be conserved in pine and A. thaliana. Circadian rhythm associated TF was not detected in association to STR. However, TEMPRANILLO (TEM) 1 was found to be down-regulated and, one of the homolog of TEM1 and APETALA 2 (AP2) were up-regulated by shade in spruce. TEM1 along with TEM2 delays flowering in A. thaliana until the plant is ready for this process by accumulating enough reserves or has reached the appropriate growth stage (Matias-Hernandez et al. 2014). Involvement of AP2 is not restricted to establishment of the floral meristem and floral organ identity, but it also plays a general role in the control of A. thaliana development (Jofuku et al. 1994). This can be interpreted as postponing the process of flowering associated to STR in spruce at the seedling stage.
From previous studies it is known that low R:FR triggers the SAS morphological and physiological changes to improve light capture; a response mediated primarily by the phytochromes (Martinez-Garcia et al. 2010). Shade reduces phyB activity and, consequently, increases the mRNA levels of the bHLH transcription factors such as phytochrome interacting factors (PIF) (Lorrain et al. 2008). PIFs regulate a large number of genes encoding metabolic enzymes and genes in the phytohormones signalling pathway such as auxin (AUX/IAA) (Hersch et al. 2014), ethylene (Jeong et al. 2016), brassinosteroids (BRs) (Oh et al. 2012), and gibberellins (Schwechheimer 2011), which control low R:FR-induced shade avoidance responses.
In A. thaliana, role of PHYA and PHYB in shade avoidance is well-documented and involves up-regulation of PHYA and PHYB in response to low R:FR (Devlin et al. 2003; Franklin et al. 2005; Martinez-Garcia et al. 2014). Our study reveals that PHYP2/B is down-regulated by low R:FR light in Scots pine (shade intolerant) and up-regulated in Norway spruce (shade tolerant), whereas no change was detected in the expression level of PHYN/A. In Scots pine, down-regulation of PHYP2/B could result in a decrease in the absolute value of phyP2/B active form leading to the activation of the downstream cascade that mediates hypocotyl elongation. On the controversy, in Norway spruce, up-regulation of PHYP2/B could result in an increase in the absolute value of phyP2/B active form and the consequent prevention of the SAS activation. In contrast to A. thaliana, where PHYA and PHYB are rapidly up-regulated in response to shade (Devlin et al. 2003; Martinez-Garcia et al. 2010, 2014), our expression study does not support a role for PHYN/A in shade avoidance or tolerance in conifers.
Moreover, in A. thaliana up-regulation of the PHYs does not result in an increase in phyA and phyB activity, instead, SAS is initiated with the FR-mediated conversion of the phyB into its inactive form and the degradation of its antagonistic protein, phyA (only under very low R:FR values phyA is stabilized mediating the so-called FR high irradiance response (FR-HIR) (Martinez-Garcia et al. 2010, 2014). It could be speculated that, despite the expression pattern of the two PHYs differ between A. thaliana and the two conifer species, they may still share similar patterns of protein activity regulation. In fact, alignment of PHYA and PHYB gene sequences from five different species (A. thaliana, Populus, Eucalyptus, Glycine max, Scots pine, Picea glauca and Norway spruce) reveals multiple non-synonymous polymorphisms associated to the species level of shade tolerance (tolerant versus intolerant) rather than to their phylogenetic classification (angiosperm versus gymnosperm). It remains to be investigated if this is an evidence of a shared functional role of the phytochrome proteins in angiosperms and gymnosperms with reference to shade tolerance. Conserved amino-acids positions in PHYA and PHYB within angiosperms and within gymnosperms suggests that there is a possibility of altered function due to sequence variability as in the case of cryptochrome 2 in A. thaliana (El-Assal et al. 2001), due to which the mode of action of phytochromes may differ in the two groups. Thus, from the phytochrome (phyA and phyB) amino-acid sequence patterns that either categorise the plant species by their type of shade response (shade tolerant or shade intolerant) or by the plant group (angiosperm or gymnosperm), we conclude that the phytochromes may possess a common functional role with reference to shade response and simultaneously, also mediate shade response in a different fashion due to altered conformation. In this context, the polymorphism I143L in PHYB of A. thaliana is associated with variation in red light response (Filiault et al. 2008); and from the alignments it is seen that in all the gymnosperm species there is Leucine at the corresponding position indicating that gymnosperms will respond to red light in a different manner than the angiosperms.
Whereas a lack of correspondence between the expression level and protein activity may be the case in PHYP2/B, it is interesting to mention that PHYN/A gene expression was previously shown to remain steady in dark- and light- grown spruce seedlings (Clapham et al. 1999). This apparent lack of induced PHYA expression in response to shade could be related to the absence of FR high irradiance response (FR-HIR) (known to be regulated by phyA) previously described in several conifer species including pine and Ginkgo (Fernbach and Mohr 1990; Mathews and Tremonte 2012) or presence of mild FR-HIR in Scots pine (Razzak et al. 2017). Clapham et al. (1998) suggested the PHYA light-mediated self-regulation as a character which was acquired late in phytochrome evolution, after the separation of the gymnosperms and angiosperms lineages, which together with the results of this study suggest that such a role may not have been acquired by the PHYN/A in conifers. In this respect, phylogenetic study of FR-HIR distribution by Mathews and Tremonte (2012), supports FR-HIR to be ancestral in living seed plants. The authors also presented evidences of several episodes of positive selections in PHYA, early in the history of angiosperms that resulted in the acquisition of new roles of FR-HIR, such as the control of seedling de-etiolation, and that could have resulted in a divergent evolution of PHYA function between gymnosperms and angiosperms. In contrast, PHYB lineage has been less affected by selection (Mathews et al. 2003; Mathews 2010). In the present study, we contribute with the evidence that PHYA did not change its expression level in response to shade, but a change in the expression of PHYB was detected in both the conifer species. In conclusion, our study supports a major putative role of PHYB in response to shade in conifers, where further research must be conducted to solve the role of PHYA.
Our comparative study of two conifers with contrasting levels of shade tolerance unveils conifer seedlings as a suitable system to study the mechanism of shade response, where hypocotyl elongation is the morphological feature that better reflects the differences in shade tolerance between both species. Seedling total length reveals that the shade tolerant species (Norway spruce) has adopted a mechanism to improve light capture while decreasing biomass production, whereas in the shade intolerant species (Scots pine), light use optimization is achieved through elongation to escape the shade. We also conclude that low light intensity can trigger similar morphological shade response as low R:FR. In Norway spruce, R:FR is the main factor determining seedling development under shade, whereas in Scots pine we observed an interaction between light intensity and R:FR. The comparative RNA-Seq analysis sheds light on our understanding of the involvement of light and hormone signalling pathways that control both processes, the SAS and the STR. Most of the genes show a role that was exclusive to one of the processes and a large proportion of them are novel while genes expressed in opposite directions in each species seem less abundant. There are other interesting features that also differentiate both responses such as the higher number of genes found in relation to the SAS and a clear preference towards gene down-regulation in SAS as compared to the STR. Our results revealed that PHYB may play a central role in the control of SAS and STR in conifers as compared to A. thaliana where both PHYA and PHYB are known to respond to shade. Overall, the SAS and STR seem to be regulated by a complex mechanism where negative feedback loops and antagonistic effects play an important role to modulate the extent of the response to shade, especially, in the control of the hormone levels. It is therefore sensible to conclude that the full understanding of the mechanism behind shade response in conifers warrants further research.
Author contribution statement
SSR contributed with experiment performance, data collection, data analysis and interpretation, and manuscript writing. ND contributed with experimental design and bioinformatics support. MRGG contributed with experimental design, data analysis and interpretation, and manuscript writing. All authors read and approved the manuscript.
The authors thank the UPSC bioinformatics facility (https://bioinfomatics.upsc.se) for technical support with regards to the RNA-Seq data pre-processing and analyses. We acknowledge the support from Science for Life Laboratory (SciLifeLab), the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure funded by the Swedish Research Council, and Uppsala Multidisciplinary Centre for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We thank the personals from Wallenberg greenhouse at SLU, Umeå for help with the handling of plants. This work was supported by the Kempe Foundation (JCK-1311) and Kungl. Skogs- och Lantbruksakademien (KSLA- H14-0150-ADA). We also acknowledge Swedish Research Council (VR) and Swedish Governmental Agency for Innovation Systems (VINNOVA) for their support.
Compliance with ethical standards
Conflict of interests
Authors declare that they have no competing interest.
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