Abstract
Screening and breeding more salt-tolerant varieties is an effective way to deal with the global reduction in rice (Oryza sativa L.) yield caused by salt stress. However, the molecular mechanism underlying differences in salt tolerance between varieties, especially between the subspecies, is still unclear. We herein performed a comparative transcriptomic analysis under salt stress in contrasting two rice genotypes, namely RPY geng (japonica, tolerant variety) and Luohui 9 (named as Chao 2R in this study, indica, susceptible variety). 7208 and 3874 differentially expressed genes (DEGs) were identified under salt stress in Chao 2R and RPY geng, separately. Of them, 2714 DEGs were co-expressed in both genotypes, while 4494 and 1190 DEGs were specifically up/down-regulated in Chao 2R and RPY geng, respectively. Gene ontology (GO) analysis results provided a more reasonable explanation for the salt tolerance difference between the two genotypes. The expression of normal life process genes in Chao 2R were severely affected under salt stress, but RPY geng regulated the expression of multiple stress-related genes to adapt to the same intensity of salt stress, such as secondary metabolic process (GO:0019748), oxidation-reduction process (GO:0009067), etc. Furthermore, we highlighted important pathways and transcription factors (TFs) related to salt tolerance in RPY geng specific DEGs sets based on MapMan annotation and TF identification. Through Meta-QTLs mapping and homologous analysis, we screened out 18 salt stress-related candidate genes (RPY geng specific DEGs) in 15 Meta-QTLs. Our findings not only offer new insights into the difference in salt stress tolerance between the rice subspecies but also provide critical target genes to facilitate gene editing to enhance salt stress tolerance in rice.
Highlights
Rice (Oryza sativa L.) is one of the main food crops in the world and feeds nearly half of the world’s population (Parihar et al, 2015; Kong et al, 2019b)
We found that RPY geng had a higher survival rate than Chao 2R (81% vs. 31%) (Figure 1)
At 0d vs. 3d, RPY geng and Chao 2R shared 595 differentially expressed genes (DEGs), at 0d vs. 7d, RPY geng and Chao 2R co-expressed 1744 DEGs (Figures 2D,E). Both RPY geng and Chao 2R had more DEGs in 0d vs. 7d than 0d vs. 3d, which indicated that more genes changed significantly the transcription levels with the extension of the salt stress time
Summary
Rice (Oryza sativa L.) is one of the main food crops in the world and feeds nearly half of the world’s population (Parihar et al, 2015; Kong et al, 2019b). Salt Tolerance in Rice of people around the world. Hundreds of salt stress-related QTLs have been identified among different rice populations to date (Kong et al, 2019b; Mansuri et al, 2020). Candidate genes in most QTLs reported so far are unknown due to the too large mapping interval. Meta-QTLs analysis can effectively narrow the mapping interval of QTLs to achieve reliable prediction of candidate genes by integrating the QTLs results from a large number of studies (Kong et al, 2020). Mansuri et al (2020) identified 46 Meta-QTLs of salt stress-related traits, including salinity tolerance score, shoot potassium concentration, shoot sodium concentration, chlorophyll content, shoot dry weight trait, etc., (Mansuri et al, 2020)
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