G-proteins are implicated in plant productivity, but their genome-wide roles in regulating agronomically important traits remain uncharacterized. Transcriptomic analyses of rice G-protein alpha subunit mutant (rga1) revealed 2270 differentially expressed genes (DEGs) including those involved in C/N and lipid metabolism, cell wall, hormones and stress. Many DEGs were associated with root, leaf, culm, inflorescence, panicle, grain yield and heading date. The mutant performed better in total weight of filled grains, ratio of filled to unfilled grains and tillers per plant. Protein–protein interaction (PPI) network analysis using experimentally validated interactors revealed many RGA1-responsive genes involved in tiller development. qPCR validated the differential expression of genes involved in strigolactone-mediated tiller formation and grain development. Further, the mutant growth and biomass were unaffected by submergence indicating its role in submergence response. Transcription factor network analysis revealed the importance of RGA1 in nitrogen signaling with DEGs such as Nin-like, WRKY, NAC, bHLH families, nitrite reductase, glutamine synthetase, OsCIPK23 and urea transporter. Sub-clustering of DEGs-associated PPI network revealed that RGA1 regulates metabolism, stress and gene regulation among others. Predicted rice G-protein networks mapped DEGs and revealed potential effectors. Thus, this study expands the roles of RGA1 to agronomically important traits and reveals their underlying processes.
Rice is an important target to improve crop nitrogen (N) use efficiency (NUE), and the identification and shortlisting of the candidate genes are still in progress. We analyzed data from 16 published N-responsive transcriptomes/microarrays to identify, eight datasets that contained the maximum number of 3020 common genes, referred to as N-responsive genes. These include different classes of transcription factors, transporters, miRNA targets, kinases and events of post-translational modifications. A Weighted gene co-expression network analysis (WGCNA) with all the 3020 N-responsive genes revealed 15 co-expression modules and their annotated biological roles. Protein-protein interaction network analysis of the main module revealed the hub genes and their functional annotation revealed their involvement in the ubiquitin process. Further, the occurrences of G-quadruplex sequences were examined, which are known to play important roles in epigenetic regulation but are hitherto unknown in N-response/NUE. Out of the 3020 N-responsive genes studied, 2298 contained G-quadruplex sequences. We compared these N-responsive genes containing G-quadruplex sequences with the 3601 genes we previously identified as NUE-related (for being both N-responsive and yield-associated). This analysis revealed 389 (17%) NUE-related genes containing G-quadruplex sequences. These genes may be involved in the epigenetic regulation of NUE, while the rest of the 83% (1811) genes may regulate NUE through genetic mechanisms and/or other epigenetic means besides G-quadruplexes. A few potentially important genes/processes identified as associated with NUE were experimentally validated in a pair of rice genotypes contrasting for NUE. The results from the WGCNA and G4 sequence analysis of N-responsive genes helped identify and shortlist six genes as candidates to improve NUE. Further, the hitherto unavailable segregation of genetic and epigenetic gene targets could aid in informed interventions through genetic and epigenetic means of crop improvement.
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