Nitrate-responsive transcriptome analysis of rice RGA1 mutant reveals the role of G-protein alpha subunit in negative regulation of nitrogen-sensitivity and use efficiency.

KEY MESSAGE: Nitrate-responsive transcriptomic, phenotypic and physiological analyses of rice RGA1 mutant revealed many novel RGA1-regulated genes/processes/traits related to nitrogen use efficiency, and provided robust genetic evidence of RGA1-regulation of NUE. Nitrogen (N) use efficiency (NUE) is important for sustainable agriculture. G-protein signalling was implicated in N-response/NUE in rice, but needed firm genetic characterization of the role of alpha subunit (RGA1). The knock-out mutant of RGA1 in japonica rice exhibited lesser nitrate-dose sensitivity than the wild type (WT), in yield and NUE. We, therefore, investigated its genomewide nitrate-response relative to WT. It revealed 3416 differentially expressed genes (DEGs), including 719 associated with development, grain yield and phenotypic traits for NUE. The upregulated DEGs were related to photosynthesis, chlorophyll, tetrapyrrole and porphyrin biosynthesis, while the downregulated DEGs belonged to cellular protein metabolism and transport, small GTPase signalling, cell redox homeostasis, etc. We validated 26 nitrate-responsive DEGs across functional categories by RT-qPCR. Physiological validation of nitrate-response in the mutant and the WT at 1.5 and 15 mM doses revealed higher chlorophyll and stomatal length but decreased stomatal density, conductance and transpiration. The consequent increase in photosynthesis and water use efficiency may have contributed to better yield and NUE in the mutant, whereas the WT was N-dose sensitive. The mutant was not as N-dose-responsive as the WT in shoot/root growth, productive tillers and heading date, but equally responsive as WT in total N and protein content. The RGA1 mutant was less impacted by higher N-dose or salt stress in terms of yield, protein content, photosynthetic performance, relative water content, water use efficiency and catalase activity. PPI network analyses revealed known NUE-related proteins as RGA1 interactors. Therefore, RGA1 negatively regulates N-dose sensitivity and NUE in rice.

Nitrate-responsive transcriptome analysis reveals additional genes/processes and associated traits viz. height, tillering, heading date, stomatal density and yield in japonica rice.

MAIN CONCLUSION: Our transcriptomic analysis expanded the repertoire of nitrate-responsive genes/processes in rice and revealed their phenotypic association with root/shoot, stomata, tiller, panicle/flowering and yield, with agronomic implications for nitrogen use efficiency. Nitrogen use efficiency (NUE) is a multigenic quantitative trait, involving many N-responsive genes/processes that are yet to be fully characterized. Microarray analysis of early nitrate response in excised leaves of japonica rice revealed 6688 differentially expressed genes (DEGs), including 2640 hitherto unreported across multiple functional categories. They include transporters, enzymes involved in primary/secondary metabolism, transcription factors (TFs), EF-hand containing calcium binding proteins, hormone metabolism/signaling and methytransferases. Some DEGs belonged to hitherto unreported processes viz. alcohol, lipid and trehalose metabolism, mitochondrial membrane organization, protein targeting and stomatal opening. 1158 DEGs were associated with growth physiology and grain yield or phenotypic traits for NUE. We identified seven DEGs for shoot apical meristem, 66 for leaf/culm/root, 31 for tiller, 70 for heading date/inflorescence/spikelet/panicle, 144 for seed and 78 for yield. RT-qPCR validated nitrate regulation of 31 DEGs belonging to various important functional categories/traits. Physiological validation of N-dose responsive changes in plant development revealed that relative to 1.5 mM, 15 mM nitrate significantly increased stomatal density, stomatal conductance and transpiration rate. Further, root/shoot growth, number of tillers and grain yield declined and panicle emergence/heading date delayed, despite increased photosynthetic rate. We report the binding sites of diverse classes of TFs such as WRKY, MYB, HMG etc., in the 1 kb up-stream regions of 6676 nitrate-responsive DEGs indicating their role in regulating nitrate response/NUE. Together, these findings expand the repertoire of genes and processes involved in genomewide nitrate response in rice and reveal their physiological, phenotypic and agronomic implications for NUE.

Heterotrimeric G-protein α subunit (RGA1) regulates tiller development, yield, cell wall, nitrogen response and biotic stress in rice.

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.