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. 2019 Feb 27:10:152.
doi: 10.3389/fpls.2019.00152. eCollection 2019.

Phytochrome A Regulates Carbon Flux in Dark Grown Tomato Seedlings

Affiliations

Phytochrome A Regulates Carbon Flux in Dark Grown Tomato Seedlings

Keisha D Carlson et al. Front Plant Sci. .

Abstract

Phytochromes comprise a small family of photoreceptors with which plants gather environmental information that they use to make developmental decisions, from germination to photomorphogenesis to fruit development. Most phytochromes are activated by red light and de-activated by far-red light, but phytochrome A (phyA) is responsive to both and plays an important role during the well-studied transition of seedlings from dark to light growth. The role of phytochromes during skotomorphogenesis (dark development) prior to reaching light, however, has received considerably less attention although previous studies have suggested that phytochrome must play a role even in the dark. We profiled proteomic and transcriptomic seedling responses in tomato during the transition from dark to light growth and found that phyA participates in the regulation of carbon flux through major primary metabolic pathways, such as glycolysis, beta-oxidation, and the tricarboxylic acid (TCA) cycle. Additionally, phyA is involved in the attenuation of root growth soon after reaching light, possibly via control of sucrose allocation throughout the seedling by fine-tuning the expression levels of several sucrose transporters of the SWEET gene family even before the seedling reaches the light. Presumably, by participating in the control of major metabolic pathways, phyA sets the stage for photomorphogenesis for the dark grown seedling in anticipation of light.

Keywords: beta oxidation; glycolysis; photomorphogenesis; phytochrome; primary metabolism; skotomorphogenesis; storage proteins; tricarboxylic acid (TCA) cycle.

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Figures

FIGURE 1
FIGURE 1
Differentially expressed transcripts and proteins between phyA mutants and WT in the dark and after exposure to R. (A) Experimental design: Comparisons to determine differential expression were made between four genotype/condition groups. Significantly differently expressed proteins (B) and transcripts (C) were assigned to a sector based on comparisons in which they were differentially expressed.
FIGURE 2
FIGURE 2
Primary metabolism pathway genes are differentially expressed at the transcript and/or protein level in phyA mutants compared to WT in the dark and after exposure to R. Normalized read counts [differentially expressed transcripts, (DETs), squares] or normalized spot volumes [differentially expressed proteins (DEPs), circles] were Z-score normalized to a color scale where white represents average expression across genotype/conditions. Glycolysis, the tricarboxylic acid cycle, the glyoxylate cycle, and beta-oxidation pathways are represented. For each enzyme, multiple gene IDs are annotated with that function. Genes are shown in order from top down: lowest chromosome number and coordinates to highest chromosome number and coordinates. If both the transcript and protein of the same gene ID are differentially expressed (DE), this is represented by connected circles and squares. If more than one protein spot was DE and identified as the same gene, this is represented by connected circles. Numeric values for gene expression, protein expression and gene IDs can be found in Supplementary Tables S1, S2, S6.
FIGURE 3
FIGURE 3
Co-expression modules show expression patterns that correlate with genotype and treatment. Modules are indicated by color (same order in A,B). In (A) z-score normalized expression on a color scale of normalized read counts is shown where white represents average expression across genotype/conditions. The gray “non-module” at the bottom consists of genes that were not significantly co-expressed with other genes. In (B) the average expression pattern of each module (eigengene) was correlated to genotype (“genotype,” WT = 0, phyA = 1) and light treatment (“condition,” dark = 0, red = 1). The R2 value from Pearson’s correlation are indicated above p-values in the boxes as well as by a red to green color scale.
FIGURE 4
FIGURE 4
Turquoise and purple gene networks show upregulation in phyA mutants and contain metabolism and seed storage genes. The turquoise (A) and purple (B) gene networks in which metabolism and seed storage genes from Figure 2 were highlighted in yellow. Oleosins were highlighted in gray. Gene names and IDs, network membership, and highlighted genes can be found in Supplementary Table S7.
FIGURE 5
FIGURE 5
PhyA reduces shoot elongation in dark grown seedlings. Seedlings of WT and phyA mutants were germinated in light-excluding boxes for 2 days and checked for germination. Only synchronized seedlings with roughly 2 mm long protruding radicles were used for subsequent experiments. A subset of seedlings was removed on days 5 and 15, scanned, and their shoot length measured using ImageJ. To determine if light exposure during seedling sterilization and imbibition prior to sowing the seeds in the boxes made a difference, seed batches were either sterilized, and sown in green safe light (“total dark”) or ambient lab light (“ambient”). Subsequently, both batches were grown in complete darkness without any light treatment for germination. Two-way ANOVAs were conducted using R for day 5 and day 15. F/p-values can be found in Supplementary Table S10. Since no difference was found between ambient light and dark sterilized seeds, the data for both conditions were combined. Condition-specific data can be seen in Supplementary Figure S8. T-tests were performed using R to determine significance ( indicates difference between WT and mutant, p < 0.05, Supplementary Table S10). Sample size N = 552 (10–12 per genotype, imbibition condition, and time past imbibition). Regardless of a short ambient light exposure during seed sterilization, phyA mutants were statistically significantly taller by the end of the experiment.
FIGURE 6
FIGURE 6
PhyA attenuates root growth in R and interacts with sucrose response. Root length (A) and shoot length (B) of germination-matched 5 day old seedlings was measured using Image J software. Three-way (factorial) ANOVAs were conducted using R. F/p-values can be found in Supplementary Table S13. Tukey post hoc analysis was performed using R to assign groups (letters). Data points not connected by a common letter are statistically significantly different from each other. Sample size N = 765 (94–96 per genotype, light environment, and sucrose treatment). Box plots in A and B indicate range of data, including the median (bold line), 25th and 75th percentiles (lower and upper box limits), 5th and 95th percentiles (lower and upper whiskers, respectively), and outliers (indicated with dots). (C) Gene expression values were extracted from the RNA-seq analysis using normalized read counts from DESeq analysis. Letters and colored boxes underneath the graph are connected with each gene and indicate the sector in which the gene was located on the Venn diagram analysis of DE genes (Figure 2B) and the module (Figure 4) the gene belongs to (if any).

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