Physiological analysis
SlBRI1 transgenic plants have increased SlBRI1 expression levels
To investigate the associations of drought tolerance with the SlBRI1 expression level, we generated transgenic tomato plants in the tomato cultivar ‘Money Maker’ background in which SlBRI1, driven by the constitutive CaMV 35S promoter, was overexpressed. The transcript levels of SlBRI1 in the two transgenic lines, SlBRI1-OE-6 and SlBRI1-OE-7, were 5.4 and 16.5 times higher, respectively, than those in MM plants (Fig. 1B). Moreover, the SlBRI1 protein levels in the SlBRI1-OE-6 and SlBRI1-OE-7 lines were confirmed by Western blot analysis (Fig. 1A). The expression levels of the BR biosynthetic genes DWARF and CPD were significantly lower than those in MM plants (Fig. 1C and D). These results showed that transgenic plants had increased SlBRI1 expression levels and BR signaling intensity.
SlBRI1 expression level alters plant growth, leaf relative water content and electrolyte leakage under drought stress
To investigate whether the SlBRI1 expression level is related to the drought resistance of tomato seedlings, SlBRI1 overexpressing, MM and abs (SlBRI1 weak mutants) tomato seedlings were all subjected to drought stress (water withheld) for 12 d. After 12 d of drought stress, all plants showed different degrees of leaf wilting. The abs plants showed slight wilting, while the wilting was the most serious in the SlBRI1-OE-6 and SlBRI1-OE-7 plants (Fig. 2A, B).
Drought stress decreased leaf relative water content (RWC), and the leaf RWC in SlBRI1 overexpressing lines was significantly lower than that in MM plants, while the RWC of abs plants was significantly higher than that of MM plants at 10 d of drought stress, and was 24.5%, 30.6% and 35.6% higher than those of MM, SlBRI1-OE-6 and SlBRI1-OE-7 plants, respectively (Fig. 2C). Drought stress resulted in enhanced electrolyte leakage levels in all plants. The leaf electrolyte leakage levels of SlBRI1 overexpressing lines were significantly higher than those of MM plants, while the electrolyte leakage levels of abs plants were significantly lower than those of MM plants at 10 d of drought stress and were 19.1%, 33.6% and 40.5% lower than those of MM, SlBRI1-OE-6 and SlBRI1-OE-7 plants, respectively (Fig. 2D). These results indicated that SlBRI1 expression levels negatively regulated the drought tolerance of tomato seedlings.
SlBRI1 expression level affects gas exchange under drought stress
Compared with the control, SlBRI1 overexpressing plants had slightly increased net photosynthetic rate (Pn) and stomatal conductance (Gs) before drought stress. However, drought stress obviously decreased the Pn, Gs and transpiration rate (Tr) but increased the intercellular CO2 concentration (Ci) in all plants (Fig. 3A-D). At 10 d of drought stress, the Pn and Tr of abs plants were significantly higher, and Ci was obviously lower, than those of other plants, while in SlBRI1 overexpressing plants, Pn and Tr were obviously lower, and Ci was markedly higher, than in other plants (Fig. 3A-D). For example, the Pn of abs plants was 27.1%, 49.2% and 56.5% higher than those of MM, SlBRI1-OE-6 and SlBRI1-OE-7 plants, respectively. There were no significant differences in Gs among all plants (Fig. 3A).
SlBRI1 expression level affects accumulation of H2O2, O2− and antioxidant enzyme activities under drought stress
Histochemical observations were used to assess the accumulation of hydrogen peroxide (H2O2) and superoxide (O2−) in tomato leaves. Before drought stress, there were no significant differences in H2O2 and O2− accumulation among all plants (Fig. 4A, B). After 10 d of drought stress, the accumulation of H2O2 and O2− in abs leaves was lower than that in MM leaves, but SlBRI1-overexpressing leaves accumulated much higher levels than MM (Fig. 4A, B). Therefore, abs plants had lower ROS levels, and SlBRI1 overexpressing plants had higher ROS levels than MM plants under drought stress.
Drought stress obviously increased the antioxidant enzyme activities of all plants. The SOD, POD and CAT activities of abs plants were significantly higher than those of other plants at 10 d of drought stress and were 39.9%, 47.9% and 29.8% higher than those of SlBRI1-OE-6 plants, respectively. The APX activities of MM and abs plants were significantly higher than those of SlBRI1 overexpressing plants after drought stress (Fig. 4C-F). These results showed that BR signalling was negatively related to the antioxidant enzyme activities of tomato seedlings under drought stress.
Transcriptome Analysis
Sequencing of different SlBRI1 expression level plants RNA-Seq
To further understand how SlBRI1 negatively regulates drought responses, we performed global gene expression studies with MM, SlBRI1-OE-7 and abs plants by high-throughput RNA sequencing (RNA-seq). As shown in Table 1, six cDNA libraries (three replicates per library) were constructed. RNA-Seq of these libraries generated approximately 47–62 million total reads, with an average of 98.9% clean reads obtained after quality filtering. Clean reads from every library showed a match rate of approximately 95% to the tomato genome, indicating that the sequencing data could be used for subsequent transcriptome analysis (Table 1).
Table 1
Summary of RNA-Seq datasets.
Sample
|
Total reads
|
Clean reads
|
Multiple mapped
|
Uniquely mapped
|
Q30(%)
|
MM_1
|
49508234
|
49000446
|
1682647(3.43%)
|
45330385(92.51%)
|
95.14
|
MM_2
|
51088508
|
50546354
|
2757649(5.46%)
|
44715920(88.47%)
|
95.33
|
MM_3
|
47788844
|
47336100
|
3387809(7.16%)
|
38838001(82.05%)
|
95.45
|
SlBRI1OE_1
|
51510028
|
51003574
|
1536162(3.01%)
|
47370570(92.88%)
|
95.02
|
SlBRI1OE_2
|
50321154
|
49823380
|
1743341(3.5%)
|
46222183(92.77%)
|
95.24
|
SlBRI1OE_3
|
48124782
|
47623938
|
2051124(4.31%)
|
43224455(90.76%)
|
95.14
|
abs_1
|
50356448
|
50014982
|
1731053(3.46%)
|
46186727(92.35%)
|
95.73
|
abs _2
|
55847692
|
55342986
|
2315453(4.18%)
|
51076174(92.29%)
|
95.43
|
abs _3
|
54333414
|
53803982
|
1946159(3.62%)
|
49851557(92.65%)
|
94.82
|
MMDS_1
|
48958602
|
48519080
|
1373243(2.83%)
|
45016374(92.78%)
|
95.35
|
MMDS_2
|
48481508
|
47966526
|
1658663(3.46%)
|
44716200(93.22%)
|
95.34
|
MMDS_3
|
57482010
|
56987708
|
2183676(3.83%)
|
52715415(92.5%)
|
95.59
|
SlBRI1OE DS_1
|
52315202
|
51751238
|
1574749(3.04%)
|
48059300(92.87%)
|
95.35
|
SlBRI1OE DS_2
|
49916312
|
49379104
|
1304795(2.64%)
|
46550624(94.27%)
|
95.22
|
SlBRI1OE DS_3
|
50834194
|
50350288
|
2526321(5.02%)
|
44485042(88.35%)
|
95.27
|
absDS_1
|
59879032
|
59361416
|
2887893(4.86%)
|
54465020(91.75%)
|
95.11
|
absDS_2
|
62685918
|
62142522
|
1947751(3.13%)
|
56526086(90.96%)
|
95.43
|
absDS_3
|
58976216
|
58470256
|
2040186(3.49%)
|
53175772(90.94%)
|
95.42
|
SlBRI1 negatively regulates drought responsive genes expression
Analysis of DEGs was performed between every pair of groups (MMDS/SlBRI1OEDS, MMDS/absDS, MM/abs, abs/absDS, MM/MMDS, SlBRI1OE/SlBRI1OEDS and MM/SlBRI1OE) based on FPKM with thresholds FDR < 0.05 and FC > 2. There were 3144 DEGs (2096 up- and 1048 downregulated) between MMDS and absDS, 6162 DEGs (3873 up- and 2289 downregulated) between MM and abs, and 2265 DEGs (1425 up- and 840 downregulated) between MM and MMDS. There were only 85 DEGs between MM and SlBRI1OE, comprising 59 upregulated and 26 downregulated DEGs (Fig. 5). We selected the above 4 groups for comprehensive analysis. The number of upregulated DEGs was higher than that of downregulated DEGs across all four comparisons (Fig. 5). However, we further found that 768 (53.9%) of 1425 drought-induced and 418 (49.8%) of 840 drought-repressed genes were regulated by abs in the same direction under normal conditions (Fig. 6A, B). There were 158 drought-induced and 43 drought-repressed genes that were further upregulated and downregulated in absDS, respectively (Fig. 6A, B). These results indicated that abs may regulate the expression of a number of drought-related genes, which results in the inhibition of plant growth under normal conditions, consistent with the growth phenotype of abs.
To further investigate how SlBRI1-OE and abs affect drought-related gene expression, we performed clustering analysis of the genes that were upregulated and downregulated in each treatment. Under normal conditions, MM upregulated genes and downregulated genes were repressed and induced under drought conditions, respectively (Fig. 6C). However, many drought stress-induced genes and repressed genes were already upregulated and downregulated in abs under normal conditions, respectively (cluster b). Many drought stress-induced genes had higher expression in absDS, while many drought stress-repressed genes had lower expression in absDS under drought conditions (cluster a). Overall, our transcriptome analyses support a role of the SlBRI1 expression level in modulating drought-responsive gene expression, largely in an antagonistic manner.
Gene Ontology (GO) and GO enrichment analyses of different SlBRI1 levels under normal conditions
To explore the effects of SlBRI1 overexpression under normal conditions, we performed GO analyses, focusing on differences between the MM group and the SlBRI1OE group. There were 71 DEGs, 72 DEGs and 74 DEGs enriched in “biological process”, “cellular component” and “molecular function”, respectively (Fig. 7, Table S2). The main biological process categories were “metabolic process” and “cellular process”. DEGs in the molecular function category were related to “catalytic activity” and “binding”. The most DEGs were assigned to the “cell” and “membrane part” cellular component categories (Fig. 7, Table S2). These results highlighted the involvement of SlBRI1-OE in cellular processes and metabolic processes, consistent with the regulation of growth by SlBRI1-OE under normal conditions.
To explore how abs functions under normal conditions, we performed GO enrichment analyses, focusing on differences between the MM group and abs group. The top 20 most obviously enriched pathways are shown in Fig. 8. The DEGs were enriched for “photosynthesis, light harvesting in photosystem I”, “photosynthesis, light harvesting”, “protein phosphorylation”, “phosphorylation”, “plastoglobule”, “cellular protein modification process”, “protein modification process”, “response to abiotic stimulus”, “lipid metabolic process”, “phosphorus metabolic process”, “phosphate-containing compound metabolic process”, “carbohydrate metabolic process” and “intrinsic component of membrane” (Fig. 8, Table S3). In addition, the most enriched category for DEGs in this study was “catalytic activity”, with a total of 2445 DEGs. A total of 148 DEGs were annotated as “response to abiotic stimulus” (Fig. 8, Table S3). These results indicated that abs upregulated the expression of a number of stress response-related genes under normal conditions.
Differences in stress response gene expression between different treatments
To further explore how abs increased drought resistance, we selected stress-related metabolic pathways from GO enrichment analyses. Four ABA biosynthesis genes, 9-cis-epoxycarotenoid dioxygenase 2 (Solyc08g016720.1), notabilis 9-cis-epoxycarotenoid dioxygenase (Solyc07g056570.1), beta-carotene, Pfam: PF05834 (Solyc06g074240.3), and zeaxanthin epoxidase (Solyc02g090890.4), were upregulated in MM under drought stress (Table S4). These genes were also induced in abs compared with MM under normal conditions. However, the expression of these genes was not obviously changed in SlBRI1OE plants compared with MM plants. Solyc08g016720.1 and Solyc06g074240.3 were upregulated between MMDS and absDS (Table S4). Eleven of 13 polyamine biosynthetic processes were upregulated in MM under drought stress. All 13 genes were induced in abs compared with MM under normal conditions. However, the expression of these genes was not obviously changed in SlBRI1OE plants compared with MM plants. Eight of 13 were upregulated between MMDS and absDS. These results indicated that abs may increase ABA and polyamine contents by inducing ABA and polyamine biosynthetic gene expression under normal and drought conditions (Table S5). Seven of 11 oxidoreductase activity genes were upregulated in MM under drought stress. All 11 genes were induced in abs compared with MM under normal conditions. However, the expression of most of these genes was not obviously changed in SlBRI1OE plants compared with MM plants. Nine of 11 genes were upregulated between MMDS and absDS, whereas 2 of 11 genes were downregulated (Fig. 9A; Table S6). These results indicated that abs may decrease reactive oxygen content by inducing oxidoreductase activity gene expression and further enhance antioxidant enzyme activities under normal and drought conditions.
Transcription factors (TFs) play a critical role in abiotic stress via gene regulatory networks. We further selected 25 TFs in 7 different families from the MMDS group, 18 upregulated and 7 downregulated. Most of the differentially expressed TFs participate in the drought stress response, and the majority are derived from the WRKY, ERF, bHLH and MYB families (Fig. 9B; Table S7). Eighteen drought stress-induced TFs were also upregulated, and 7 of the drought-downregulated TFs were also downregulated in abs under normal conditions. Seventeen TFs did not show obvious changes in expression in SlBRI1OE plants compared with MM plants; 4 TFs, ERF (Solyc06g068360.3), AP2-ERF (Solyc10g084340.2), MYB75 (Solyc10g086250.2) and bHLH079 (Solyc02g078130.3), had the same expression direction, while 4 TFs, WRKY33 (Solyc09g014990.4), WRKY46 (Solyc08g067340.4), MYB76 (Solyc05g008250.2) and bHLH150 (Solyc09g065100.3), had opposite expression changes in SlBRI1OE plants and drought-exposed plants (Fig. 8B; Table S5). Eighteen of 25 TFs had the same expression direction in absDS compared with MMDS, and 7 of 25 TFs were not obviously changed (Fig. 9B; Table S7). In abs plants, reduced BR signalling may upregulate or downregulate drought-related TFs, which further regulate drought stress-related gene expression and improve drought resistance under both normal conditions and drought conditions.
Validation of RNA-Seq data by qRT-PCR analysis
To validate the RNA-seq data, we selected 15 DEGs of MM vs abs for qRT-PCR determination. We further compared the results obtained from qRT-PCR with those generated from the RNA-seq data. The trends of expression were consistent for all transcripts in both analyses, with a correlation coefficient of R2 = 0.883 (Fig. 10). These results confirmed the reliability of the RNA-seq data.