Abstract
A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8–61 nodes comprised 239 genes. From these 10 modules, 10 genes common to all the three stresses were selected. Further, based on the centrality properties and highly dense interactions, we identified 7 intra-modular hub genes leading to a total of 17 potential candidate genes. Out of these 17 genes, 15 were validated by expression analysis using a panel of 4 test genotypes and a pair of standard check genotypes for each abiotic stress response. Interestingly, all the 15 genes showed upregulation under all stresses and in all the genotypes, suggesting that they could be representing some of the core abiotic stress-responsive genes. More pertinently, eight of the genes were found to be co-localized with the stress-tolerance QTL regions. Thus, in conclusion, our study not only provided an effective approach for studying abiotic stress tolerance in rice, but also identified major candidate genes which could be further validated by functional genomics for abiotic stress tolerance.
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All the input data and genes are available in the public domain except for the heat stress-responsive genes (HRG) and the appropriate references are given. HRG work is under publication and the gene list is available on request. Other information is available in the main manuscript or supplementary information.
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Funding
The financial assistance to carry out this work was obtained from the ICAR-CABin, a network project run by Indian council of agricultural research-Centre for agricultural bioinformatics and Department of Biotechnology (DBT), Government of India, through BT/PR10787/AGIII/103/883/2014.
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Conceptualization, MKR and AMS; Data curation, SSK; Facilities: NKS; Execution of plant stress studies and expression analysis, MKR, EM and VJ; Bioinformatics analyses, VS; Bioinformatics guidance, AUS; Material Resources, SG, MR and AKS; Overall guidance and supervision, AMS; Manuscript preparation – MKR and AMS. All authors read and approved the manuscript.
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13205_2022_3182_MOESM1_ESM.tif
Supplementary file1 Workflow of bioinformatics analysis performed to identify candidate genes for multiple abiotic stress tolerance in rice (TIF 1359 KB)
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Ramkumar, M.K., Mulani, E., Jadon, V. et al. Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice (Oryza sativa L.). 3 Biotech 12, 127 (2022). https://doi.org/10.1007/s13205-022-03182-7
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DOI: https://doi.org/10.1007/s13205-022-03182-7