Abstract
Drought is among the most common abiotic constraints of crop growth, development, and productivity. Integrating different omics approaches offers a possibility for deciphering the metabolic pathways and fundamental mechanisms involved in abiotic stress tolerance. Here, we explored the transcriptional and post-transcriptional changes in drought-stressed tomato plants using transcriptomic and proteomic profiles to determine the molecular dynamics of tomato drought stress responses. We identified 22467 genes and 5507 proteins, among which the expression of 3765 genes and 294 proteins was significantly changed under drought stress. Furthermore, the differentially expressed genes (DEGs) and differentially abundant proteins (DAPs) showed a good correlation (0.743). The results indicated that integrating different omics approaches is promising in exploring the multilayered regulatory mechanisms of plant drought resistance. Gene ontology (GO) and pathway analysis identified several GO terms and pathways related to stress resistance, including response to stress, abiotic stimulus, and oxidative stress. The plant hormone abscisic acid (ABA) plays pivotal roles in response to drought stress, ABA-response element binding factor ( AREB ) is a key positive regulator of ABA signaling. Moreover, our analysis indicated that drought stress increased the abscisic acid (ABA) content, which activated AREB1 expression to regulate the expression of TAS14 , GSH-Px-1 , and Hsp , ultimately improving tomato drought resistance. In addition, the yeast one-hybrid assay demonstrated that the AREB1 could bind the Hsp promoter to activate Hsp expression. Thus, this study involved a full-scale analysis of gene and protein expression in drought-stressed tomato, deepening the understanding of the regulatory mechanisms of the essential drought-tolerance genes in tomato.
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Claims 8
Claim · model-written summary
The study identified 22467 genes and 5507 proteins in tomato.
- Taxon
- tomato
Solanum lycopersicume1 - Outcome
- genes and 5507 proteinse0
- Value
- 22467 genes and 5507 proteinse0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“We identified 22467 genes and 5507 proteins”
e1“drought-stressed tomato plants”
Claim · model-written summary
Expression of 3765 genes changed significantly under drought stress.
- Taxon
- tomatoSolanum lycopersicume1
- Treatment
- drought stresse0
- Outcome
- expression of 3765 genese0
- Value
- 3765 genese0
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the expression of 3765 genes and 294 proteins was significantly changed under drought stress”
e1“drought-stressed tomato plants”
Claim · model-written summary
Abundance of 294 proteins changed significantly under drought stress.
- Taxon
- tomatoSolanum lycopersicume1
- Treatment
- drought stresse0
- Outcome
- 294 proteinse0
- Value
- 294 proteinse0
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the expression of 3765 genes and 294 proteins was significantly changed under drought stress”
e1“drought-stressed tomato plants”
Claim · model-written summary
Differential gene expression and protein abundance were correlated at 0.743.
- Taxon
- tomatoSolanum lycopersicume1
- Gene
- differentially expressed genes (DEGs)e0
- Outcome
- good correlatione0
- Value
- 0.743e0
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the differentially expressed genes (DEGs) and differentially abundant proteins (DAPs) showed a good correlation (0.743)”
e1“drought-stressed tomato plants”
Claim · model-written summary
GO and pathway analysis identified stress resistance related terms and pathways.
- Taxon
- tomatoSolanum lycopersicume1
- Outcome
- GO terms and pathways related to stress resistancee0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Gene ontology (GO) and pathway analysis identified several GO terms and pathways related to stress resistance, including response to stress, abiotic stimulus, and oxidative stress.”
e1“drought-stressed tomato plants”
Claim · model-written summary
Drought stress increased tomato ABA content.
- Taxon
- tomatoSolanum lycopersicume1
- Treatment
- drought stresse0
- Outcome
- abscisic acid (ABA) contente0
- Direction
- increasede0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“drought stress increased the abscisic acid (ABA) content”
e1“drought-stressed tomato plants”
Claim · model-written summary
Increased ABA activated AREB1 expression and downstream TAS14, GSH-Px-1 and Hsp expression, improving drought resistance.
- Taxon
- tomatoSolanum lycopersicume0
- Gene
- AREB1e0
- Compound
- abscisic acid (ABA)e1
- Outcome
- tomato drought resistancee0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“which activated AREB1 expression to regulate the expression of TAS14 , GSH-Px-1 , and Hsp , ultimately improving tomato drought resistance”
e1“drought stress increased the abscisic acid (ABA) content”
Claim · model-written summary
AREB1 bound the Hsp promoter and activated Hsp expression in a yeast one-hybrid assay.
- Taxon
- tomatoSolanum lycopersicume1
- Gene
- AREB1e0
- Outcome
- Hsp expressione0
- Qualifier
- bind the Hsp promotere0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“the yeast one-hybrid assay demonstrated that the AREB1 could bind the Hsp promoter to activate Hsp expression”
e1“drought-stressed tomato plants”
The same questions in other papers
drought · physiology: hormones · Solanum lycopersicum (tomato)Results differ
2 papers in the same direction as this paper · 8 in the opposite direction
- no effect
- negative
- negative
7 papers more in this group
See all 11 papers →Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.