Results of the correlation analysis between DEGs and DAMs.

There were 50 of the former and 100 of the latter. Red represents a positive correlation and blue represents a negative correlation.</p

Sequencing output statistics of six samples.

Sequencing output statistics of six samples.</p

Characteristics of celery unigenes generated by Illumina sequencing.

(A) The length distribution of all assembled transcripts and unigenes. (B) The number of unigenes annotated by seven different databases, including Nr, Nt, Swiss-Prot, KO, KOG, GO and Pfam. (C) Species distributions of the top BLAST hits for all homologous sequences. (D) KOG functional classifications of all the unigenes. Nr: NCBI non-redundant protein sequences; Nt: NCBI nucleotide sequences; KO: Kyoto encyclopedia of genes and genomes ortholog; KOG: eukaryotic ortholog groups; GO: gene ontology; Pfam: protein family.</p

GO (A) and KEGG (B) functional classifications of the annotated unigenes in celery.

The unigenes were distributed into three GO categories: biological process, cellular component and molecular function. The unigenes were divided into five KEGG groups: metabolism (a), genetic information processing (b), environmental information processing (c), cellular processes (d) and organismal systems (e).</p

The genes related with sulfur and selenocompound metabolism in the stems of celery plants.

The genes related with sulfur and selenocompound metabolism in the stems of celery plants.</p

Differential metabolites analysis.

(A) The PLS-DA score plot shows groupings of Se-treated vs. mock samples in both ESI+ and ESI− modes. The abscissa represents the score of the sample for the first principal component; the ordinate represents the score of the sample for the second principal component; R2Y is the interpretation rate of the second principal component of the model; Q2Y is the prediction rate of the model. (B) Volcanic map of differential metabolites in both ESI+ and ESI− modes. Black represents metabolites having no significant differences, red represents upregulated metabolites, green represents downregulated metabolites, and the dot size represents the Variable Importance in the Projection Value. (C). Heat map and cluster analyses of mock and Se-treated celery varieties at the metabolome level in both ESI+ and ESI− modes. Hierarchical clustering was used to analyze the differentiated metabolites. The relative quantitative values of differentiated metabolites were transformed into Z values and clustered. Different color regions represent different clustering information. The metabolic expression patterns within the same group are similar, which indicates that they may have similar functions or participate in the same biological process.</p

Transcriptional variations in tomato shoots under different hormone treatments.

<p>(a) Expression profiles of the DEGs under different hormone treatments were shown by a heatmap. (b) Significance analysis of the DEGs in different comparisons by Volcanoplots. (c) The number of up- and down-regulated genes in different comparisons. (d) Venn diagrams showed the proportions of the up- and down-regulated genes in three comparisons.</p

Transcriptome analysis of tomato (<i>Solanum lycopersicum</i> L.) shoots reveals a crosstalk between auxin and strigolactone

<div><p>Auxin and strigolactone (SL) are two important phytohormones involved in shoot branching and morphology. Tomato (<i>Solanum lycopersicum</i> L.), a member of the Solanaceae family, is one of the most popular food crops with high economic value in the world. To seek a better understanding of the responses to exogenous hormones, transcriptome analyses of the tomato shoots treated with exogenous auxin and SL, separately or together, were performed. A total of 2326, 260 and 1379 differential expressed genes (DEGs) were identified under the IAA, GR24 and IAA+GR24 treatments, respectively. Network analysis pointed out two enriched interaction clusters, including “ethylene biosynthesis” and “photosynthesis”. Several ethylene biosynthesis and metabolism-related genes were up-regulated under both IAA and IAA+GR24 treatments, suggesting their involvement in the regulation of ethylene biosynthesis. Besides, auxin-SLs-triggered the expression of several <i>CAB</i> genes may lead to systemic increases in the induction of photosynthesis. Several auxin-activated metabolic pathways could be reduced by the GR24 treatment, indicated that the crosstalk between auxin and SLs may be involved in the metabolic regulation of tomato. Further analysis showed that SLs affect the responses of tomato shoots to auxin by inducing the expression of a series of auxin downstream genes. On the other hand, auxin regulated the biosynthesis of SLs by affecting the genes in the “Carotenoid biosynthesis” pathway. Our data will give us an opportunity to reveal the crosstalk between auxin and SLs in the shoots of tomato.</p></div

The DEGs related with phosphate and sulfate transporters.

The DEGs related with phosphate and sulfate transporters.</p

Real-time quantitative PCR validation of several hormone-related genes.

<p>The histogram shows the relative expression level of these genes with respect to the ACTIN in tomato. The data were analyzed by three independent repeats, and standard deviations were shown with error bars. Significant differences in expression level were indicated by “*”.</p