Integrating gene expression analysis and ecophysiological responses to water deficit in leaves of tomato plants

Abstract

Soil water deficit (WD) significantly impacts plant survival and crop yields. Many gaps remain in our understanding of the synergistic coordination between molecular and ecophysiological responses delaying substantial drought-induced effects on plant growth. To investigate this synergism in tomato leaves, we combined molecular, ecophysiological, and anatomical methods to examine gene expression patterns and physio-anatomical characteristics during a progressing WD experiment. Four sampling points were selected for transcriptomic analysis based on the key ecophysiological responses of the tomato leaves: 4 and 5 days after WD (d-WD), corresponding to 10% and 90% decrease in leaf stomatal conductance; 8 d-WD, the leaf wilting point; and 10 d-WD, when air embolism blocks 12% of the leaf xylem water transport. At 4 d-WD, upregulated genes were mostly linked to ABA-independent responses, with larger-scale ABA-dependent responses occurring at 5 d-WD. At 8 d-WD, we observed an upregulation of heat shock transcription factors, and two days later (10 d-WD), we found a strong upregulation of oxidative stress transcription factors. Finally, we found that young leaves present a stronger dehydration tolerance than mature leaves at the same drought intensity level, presumably because young leaves upregulate genes related to increased callose deposition resulting in limiting water loss to the phloem, and related to increased cell rigidity by modifying cell wall structures. This combined dataset will serve as a framework for future studies that aim to obtain a more holistic WD plant response at the molecular, ecophysiological and anatomical level.

Keywords: ABA-dependent; ABA-independent; Ecophysiology; Embolism; Gene expression; Tomato; Transcription factors; Water deficit; Xylem hydraulics.

Fig. 1

Sampling strategy and physiological thresholds in 50-day-old S. lycopersicum cv. MoneyMaker plants. (A) Leaf water potential (Ψ_leaf) variation over time for well-watered (WW, green circles) and water-deficit (WD, yellow circles) plants during the 10d drought experiment. The four sampling points for RNA extraction (at 4, 5, 8, and 10 days after water deficit, d-WD) are indicated with black vertical lines. Symbols represent averages ± SE (n = 3–6 per sampling point). (B) Stomatal safety margin during Ψ_leaf decline, defined by the difference between the best-fitted blue curve for stomata dynamics (gs, n = 33), and the red vulnerability curve (average ± SE) based on leaf percentage of embolized pixels (leaf PEP, n = 8). The purple vertical line indicates the turgor loss point (Ψ_TLP), and the black vertical lines indicate the four sampling dates for RNA extraction.

Fig. 2

Transcriptomic profiling of water deficit (WD) and well-watered (WW) tomato plants. (A) Multidimensional scaling plot visualizing (dis)similarity between WD and WW samples. Symbols represent biological replicates, colors represent the different treatments (yellow for WD, green for WW conditions), and different shapes represent the different sampling points (circle for 4d-WD, square for 5d-WD, rhombus for 8d-WD, triangle for 10d-WD, and plus signs for young leaves at 10d-WD). (B) Expression heatmap and hierarchical clustering of the top 500 most variable genes. Each column corresponds to one replicate: WW or WD, mature (M) or young (Y) leaves, and different clusters are separated by white lines. All biological replicates cluster to their respective time points and treatments. Color is determined by z-score, ranging from − 3 (blue) to 3 (red). (C) Volcano plots showing differentially expressed genes between WW and WD conditions in mature leaves for every time point. Differential expression is defined as having a log₂ fold change over WW conditions of at least 1, and a Benjamini-Hochberg FDR-adjusted p-value below 0.05.

Fig. 3

Weighted gene correlation network analysis (WGCNA). (A) Dendrogram denoting WGCNA results for all previously identified DE genes. The y-axis (Height) represents the distance, or dissimilarity between clusters. Nineteen distinct co-expression clusters were identified, with different colors and Roman numerals (i-xix). Gene cluster designations can be found in Suppl. Table S2. (B) Cluster-trait relationship heatmap, correlating the module eigengenes (ME) to the measured physiological traits: leaf water potential (Ψ_leaf), stomatal conductance (gs), CO₂ assimilation (A), and loss of hydraulic conductance in leaves (leaf PEP). Correlations are plotted on a diverging color scale centered on 0 (yellow), with red denoting a positive correlation and green a negative correlation. (C) Expression z-scores for each cluster, using scaled and centered VST normalized counts over increasing water deficit from basal (WW) conditions, consisting of WW plants on the first sampling date, to 10d-WD.

Fig. 4

Transcription factor expression and number of correlated genes over a progressive water deficit. Transcription factors are separated by which sampling time point they first break the differential expression threshold (log₂ fold change > 1; p_adj < 0.05), focusing only on upregulated transcription factors. In the columns (from left to right) we indicated: a histogram showing the distribution of correlation strengths (weight) of correlated genes, grouping weights within 0.01 difference together; the gene cluster (see Fig. 3); the number of correlated genes from 0 (light yellow) to 1500 (green); the differential expression for each transcription factor across time points is given in log₂ fold change spanning from − 8 (blue) to 8 (red) and centered on 0 (white); and the locus ID of the gene.

Fig. 5

Comparative transcriptomic analysis of young and mature leaves under well-watered and water-deficit conditions. (A) Heatmap showing z-scores of differentially regulated genes between young and mature leaves under well-watered (WW) and water deficit (WD) conditions (10d-WD). Z-scores are represented by a diverging color scale from low (blue) to high (red), centered on 0 (light yellow). Clusters were determined by K-means clustering and cluster assignments (numbered 1-7) are given on the left-most column. Gene cluster assignments are given in Suppl. Table S3. (B) Line plots detailing average (± SE) gene expression in each cluster for young and mature leaves under WW and WD conditions. Values are given in variance stabilized transformed (VST) counts. The average gene expression for mature leaves is shown in yellow, and for young leaves in blue.