Transcriptome analysis of rice-seedling roots under soil–salt stress using RNA-Seq method
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Soil salinity is a major production constrain for agricultural crops, especially in Oryza sativa (rice). Analyzing physiological effect and molecular mechanism under salt stress is key for developing stress-tolerant plants. Roots system has a major role in coping with the osmotic change impacted by salinity and few salt-stress-related transcriptome studies in rice have been previously reported. However, transcriptome data sets using rice roots grown in soil condition are more relevant for further applications, but have not yet been available. The present work analyzed rice root and shoot physiological characteristics in response to salt stress using 250 mM NaCl for different timepoints. Subsequently, we identified that 5 day treatment is critical timepoint for stress response in the specific experimental design. We then generated RNA-Seq-based transcriptome data set with rice roots treated with 250 mM NaCl for 5 days along with untreated controls in soil condition using rice japonica cultivar Chilbo. We identified 447 upregulated genes under salt stress with more than fourfold changes (p value < 0.05, FDR < 0.05) and used qRT-PCR for six genes to confirm their salt-dependent induction patterns. GO-enrichment analysis indicated that carbohydrate and amino-acid metabolic process are significantly affected by the salt stress. MapMan overview analysis indicated that secondary metabolite-related genes are induced under salt stress. Metabolites profiling analysis confirmed that phenolics and flavonoids accumulate in root under salt stress. We further constructed a functional network consisting of regulatory genes based on predicted protein–protein interactions, suggesting useful regulatory molecular network for future applications.
KeywordsGene ontology MapMan Rice Root RNA-Seq Salt stress
We thank Dr. Gynheung An for providing valuable comments and sharing research facilities. This work was supported by Grants from the Next-Generation BioGreen 21 Program (PJ01366401 and PJ01369001 to KHJ), the Rural Development Administration, Republic of Korea, and by the Collaborative Genome Program of the Korea Institute of Marine Science and Technology Promotion (KIMST) funded by the Ministry of Oceans and Fisheries (MOF) (no. 2018043004 to KHJ).
KHJ, YJK, and MHC conceived and designed the research plans; AKNC and JWK performed most of the experiments; YHY carried out the network analysis; HLP estimated the secondary metabolites, AKNC and KHJ analyzed the data, AKNC, JWK, and KHJ wrote this paper.
Compliance with ethical standards
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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