Meta-Analysis of Yield-Related and N-Responsive Genes Reveals Chromosomal Hotspots, Key Processes and Candidate Genes for Nitrogen-Use Efficiency in Rice

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.

Promising physiological traits associated with nitrogen use efficiency in rice under reduced N application

Higher grain yield in high-yielding rice varieties is mostly driven by nitrogen (N) fertilizer applied in abundant amounts leading to increased production cost and environmental pollution. This has fueled the studies on nitrogen use efficiency (NUE) to decrease the N fertilizer application in rice to the possible extent. NUE is a complex physiological trait controlled by multiple genes, but yet to be completely deciphered in rice. With an objective of identifying the promising physiological traits associated with NUE in rice, the performance of 14 rice genotypes was assessed at N0, N50, N100, and N150 for four (two wet and two dry) seasons using agro-morphological, grain yield, flag leaf traits, photosynthetic pigment content, flag leaf gas exchange traits, and chlorophyll fluorescence traits. Furthermore, the data were used to derive various NUE indices to identify the most appropriate indices useful to screen rice genotypes at N50. Results indicate that with the increase in N application, cumulative grain yield increased significantly up to N100 (5.02 t ha-1); however, the increment in grain yield was marginal at N150 (5.09 t ha-1). The mean reduction of grain yield was only 26.66% at N50 ranging from 15.0% to 34.2%. The significant finding of the study is the identification of flag leaf chlorophyll fluorescence traits (Fv/Fm, ΦPSII, ETR, and qP) and Ci associated with grain yield under N50, which can be used to screen N use efficient genotypes in rice under reduced N application. Out of nine NUE indices assessed, NUpE, NUtE, and NUEyield were able to delineate the high-yielding genotypes at N50 and were useful to screen rice under reduced N conditions. Birupa emerged as one of the high yielders under N50, even though it is a moderate yielder at N100 and infers the possibility of cultivating some of the released rice varieties under reduced N inputs. The study indicates the possibility of the existence of promising genetic variability for grain yield under reduced N, the potential of flag leaf chlorophyll fluorescence, and gas exchange traits as physiological markers and best suitable NUE indices to be deployed in rice breeding programs.

Phenotypic and genome-wide association analyses for nitrogen use efficiency related traits in maize (Zea mays L.) exotic introgression lines

Nitrogen (N) limits crop production, yet more than half of N fertilizer inputs are lost to the environment. Developing maize hybrids with improved N use efficiency can help minimize N losses and in turn reduce adverse ecological, economical, and health consequences. This study aimed to identify single nucleotide polymorphisms (SNPs) associated with agronomic traits (plant height, grain yield, and anthesis to silking interval) under high and low N conditions. A genome-wide association study (GWAS) was conducted using 181 doubled haploid (DH) lines derived from crosses between landraces from the Germplasm Enhancement of Maize (BGEM lines) project and two inbreds, PHB47 and PHZ51. These DH lines were genotyped using 62,077 SNP markers. The same lines from the per se trials were used as parental lines for the testcross field trials. Plant height, anthesis to silking interval, and grain yield were collected from high and low N conditions in three environments for both per se and testcross trials. We used three GWAS models, namely, general linear model (GLM), mixed linear model (MLM), and Fixed and Random model Circulating Probability Unification (FarmCPU) model. We observed significant genetic variation among the DH lines and their derived testcrosses. Interestingly, some testcrosses of exotic introgression lines were superior under high and low N conditions compared to the check hybrid, PHB47/PHZ51. We detected multiple SNPs associated with agronomic traits under high and low N, some of which co-localized with gene models associated with stress response and N metabolism. The BGEM panel is, thus, a promising source of allelic diversity for genes controlling agronomic traits under different N conditions.

A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice (Oryza sativa L.)

Phosphorus use efficiency (PUE) is a complex trait, governed by many minor quantitative trait loci (QTLs) with small effects. Advances in molecular marker technology have led to the identification of QTLs underlying PUE. However, their practical use in breeding programs remains challenging due to the unstable effects in different genetic backgrounds and environments, interaction with soil status, and linkage drag. Here, we compiled PUE QTL information from 16 independent studies. A total of 192 QTLs were subjected to meta-QTL (MQTL) analysis and were projected into a high-density SNP consensus map. A total of 60 MQTLs, with significantly reduced number of initial QTLs and confidence intervals (CI), were identified across the rice genome. Candidate gene (CG) mining was carried out for the 38 MQTLs supported by multiple QTLs from at least two independent studies. Genes related to amino and organic acid transport and auxin response were found to be abundant in the MQTLs linked to PUE. CGs were cross validated using a root transcriptome database (RiceXPro) and haplotype analysis. This led to the identification of the eight CGs (OsARF8, OsSPX-MFS3, OsRING141, OsMIOX, HsfC2b, OsFER2, OsWRKY64, and OsYUCCA11) modulating PUE. Potential donors for superior PUE CG haplotypes were identified through haplotype analysis. The distribution of superior haplotypes varied among subspecies being mostly found in indica but were largely scarce in japonica. Our study offers an insight on the complex genetic networks that modulate PUE in rice. The MQTLs, CGs, and superior CG haplotypes identified in our study are useful in the combination of beneficial alleles for PUE in rice.

Weighted gene co-expression network analysis of nitrogen (N)-responsive genes and the putative role of G-quadruplexes in N use efficiency (NUE) in rice

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.

Genome-Wide Urea Response in Rice Genotypes Contrasting for Nitrogen Use Efficiency

Rice is an ideal crop for improvement of nitrogen use efficiency (NUE), especially with urea, its predominant fertilizer. There is a paucity of studies on rice genotypes contrasting for NUE. We compared low urea-responsive transcriptomes of contrasting rice genotypes, namely Nidhi (low NUE) and Panvel1 (high NUE). Transcriptomes of whole plants grown with media containing normal (15 mM) and low urea (1.5 mM) revealed 1497 and 2819 differentially expressed genes (DEGs) in Nidhi and Panvel1, respectively, of which 271 were common. Though 1226 DEGs were genotype-specific in Nidhi and 2548 in Panvel1, there was far higher commonality in underlying processes. High NUE is associated with the urea-responsive regulation of other nutrient transporters, miRNAs, transcription factors (TFs) and better photosynthesis, water use efficiency and post-translational modifications. Many of their genes co-localized to NUE-QTLs on chromosomes 1, 3 and 9. A field evaluation under different doses of urea revealed better agronomic performance including grain yield, transport/uptake efficiencies and NUE of Panvel1. Comparison of our urea-based transcriptomes with our previous nitrate-based transcriptomes revealed many common processes despite large differences in their expression profiles. Our model proposes that differential involvement of transporters and TFs, among others, contributes to better urea uptake, translocation, utilization, flower development and yield for high NUE.

Variation in nitrogen partitioning and reproductive stage nitrogen remobilization determines nitrogen grain production efficiency (NUEg) in diverse rice genotypes under varying nitrogen supply

Nitrogen (N) is an important macronutrient needed for grain yield, grain N and grain protein content in rice. Grain yield and quality are significantly determined by N availability. In this study, to understand the mechanisms associated with reproductive stage N remobilization and N partitioning to grain 2 years of field experiments were conducted with 30 diverse rice genotypes during 2019-Kharif and 2020-Kharif seasons. The experiments were conducted with two different N treatments; N deficient (N0-no external N application, available soil N; 2019-234.15 kgha-1, 2020-225.79 kgha-1) and N sufficient (N120-120 kgha-1 external N application, available soil N; 2019-363.77 kgha-1, 2020-367.95 kgha-1). N application increased the NDVI value, biomass accumulation, grain yield, harvest index and grain N accumulation. Post-anthesis N uptake and N remobilization from vegetative tissues to grain are critical for grain yield and N harvest index. Rice genotypes, Kalinga-1, BAM-4234, IR-8384-B-B102-3, Sahbhagi Dhan, BVD-109 and Nerica-L-42 showed a higher rate of N remobilization under N sufficient conditions. But, under N deficiency, rice genotypes-83929-B-B-291-3-1-1, BVD-109, IR-8384-B-B102-3 and BAM-4234 performed well showing higher N remobilization efficiency. The total amount of N remobilization was recorded to be high in the N120 treatment. The harvest index was higher in N120 during both the cropping seasons. RANBIR BASMATI, BAM-832, APO, BAM-247, IR-64, Vandana, and Nerica-L-44 were more efficient in N grain production efficiency under N deficient conditions. From this study, it is evident that higher grain N accumulation is not always associated with higher yield. IR-83929-B-B-291-3-1-1, Kalinga-1, APO, Pusa Basmati-1, and Nerica-L-44 performed well for different N use efficiency component traits under both N deficient (N0) and N sufficient (N120) conditions. Identifying genotypes/donors for N use efficiency-component traits is crucial in improving the fertilizer N recovery rate and site specific N management.

Maize Breeding for Low Nitrogen Inputs in Agriculture: Mechanisms Underlying the Tolerance to the Abiotic Stress

Nitrogen (N) is essential for sustaining life on Earth and plays a vital role in plant growth and thus agricultural production. The excessive use of N fertilizers not only harms the economy, but also the environment. In the context of the environmental impacts caused by agriculture, global maize improvement programs aim to develop cultivars with high N-use efficiency (NUE) to reduce the use of N fertilizers. Since N is highly mobile in plants, NUE is related to numerous little-known morphophysiological and molecular mechanisms. In this review paper we present an overview of the morpho-physiological adaptations of shoot and root, molecular mechanisms involved in plant response to low nitrogen environment, and the genetic effects involved in the control of key traits for NUE. Some studies show that the efficiency of cultivars growing under low N is related to deep root architecture, more lateral roots (LR), and sparser branching of LR, resulting in lower metabolic costs. The NUE cultivars also exhibit more efficient photosynthesis, which affects plant growth under suboptimal nitrogen conditions. In this sense, obtaining superior genotypes for NUE can be achieved with the exploitation of heterosis, as non-additive effects are more important in the expression of traits associated with NUE.

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

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.

Comparative Transcriptomic Analyses of Nitrate-Response in Rice Genotypes With Contrasting Nitrogen Use Efficiency Reveals Common and Genotype-Specific Processes, Molecular Targets and Nitrogen Use Efficiency-Candidates

The genetic basis for nitrogen (N)-response and N use efficiency (NUE) must be found in N-responsive gene expression or protein regulation. Our transcriptomic analysis of nitrate response in two contrasting rice genotypes of Oryza sativa ssp. Indica (Nidhi with low NUE and Panvel1 with high NUE) revealed the processes/functions underlying differential N-response/NUE. The microarray analysis of low nitrate response (1.5 mM) relative to normal nitrate control (15 mM) used potted 21-days old whole plants. It revealed 1,327 differentially expressed genes (DEGs) exclusive to Nidhi and 666 exclusive to Panvel1, apart from 70 common DEGs, of which 10 were either oppositely expressed or regulated to different extents. Gene ontology analyses revealed that photosynthetic processes were among the very few processes common to both the genotypes in low N response. Those unique to Nidhi include cell division, nitrogen utilization, cytoskeleton, etc. in low N-response, whereas those unique to Panvel1 include signal transduction, protein import into the nucleus, and mitochondria. This trend of a few common but mostly unique categories was also true for transporters, transcription factors, microRNAs, and post-translational modifications, indicating their differential involvement in Nidhi and Panvel1. Protein-protein interaction networks constructed using DEG-associated experimentally validated interactors revealed subnetworks involved in cytoskeleton organization, cell wall, etc. in Nidhi, whereas in Panvel1, it was chloroplast development. NUE genes were identified by selecting yield-related genes from N-responsive DEGs and their co-localization on NUE-QTLs revealed the differential distribution of NUE-genes between genotypes but on the same chromosomes 1 and 3. Such hotspots are important for NUE breeders.

Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship

The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.

Nitrogen use efficiency (NUE): elucidated mechanisms, mapped genes and gene networks in maize (Zea mays L.)

Nitrogen, the vital primary plant growth nutrient at deficit soil conditions, drastically affects the growth and yield of a crop. Over the years, excess use of inorganic nitrogenous fertilizers resulted in pollution, eutrophication and thereby demanding the reduction in the use of chemical fertilizers. Being a C₄ plant with fibrous root system and high NUE, maize can be deployed to be the best candidate for better N uptake and utilization in nitrogen deficient soils. The maize germplasm sources has enormous genetic variation for better nitrogen uptake contributing traits. Adoption of single cross maize hybrids as well as inherent property of high NUE has helped maize cultivars to achieve the highest growth rate among the cereals during last decade. Further, considering the high cost of nitrogenous fertilizers, adverse effects on soil health and environmental impact, maize improvement demands better utilization of existing genetic variation for NUE via introgression of novel allelic combinations in existing cultivars. Marker assisted breeding efforts need to be supplemented with introgression of genes/QTLs related to NUE in ruling varieties and thereby enhancing the overall productivity of maize in a sustainable manner. To achieve this, we need mapped genes and network of interacting genes and proteins to be elucidated. Identified genes may be used in screening ideal maize genotypes in terms of better physiological functionality exhibiting high NUE. Future genome editing may help in developing lines with increased productivity under low N conditions in an environment of optimum agronomic practices.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01113-z.

Meta-QTLs, ortho-MQTLs and candidate genes for nitrogen use efficiency and root system architecture in bread wheat (Triticum aestivum L.)

In wheat, meta-QTLs (MQTLs), ortho-MQTLs, and candidate genes (CGs) were identified for nitrogen use efficiency and root system architecture. For this purpose, 1788 QTLs were available from 24 studies published during 2006-2020. Of these, 1098 QTLs were projected onto the consensus map resulting in 118 MQTLs. The average confidence interval (CI) of MQTLs was reduced up to 8.56 folds in comparison to the average CI of QTLs. Of the 118 MQTLs, 112 were anchored to the physical map of the wheat reference genome. The physical interval of MQTLs ranged from 0.02 to 666.18 Mb with a mean of 94.36 Mb. Eighty-eight of these 112 MQTLs were verified by marker-trait associations (MTAs) identified in published genome-wide association studies (GWAS); the MQTLs that were verified using GWAS also included 9 most robust MQTLs, which are particularly useful for breeders; we call them 'Breeder's QTLs'. Some selected wheat MQTLs were further utilized for the identification of ortho-MQTLs for wheat and maize; 9 such ortho-MQTLs were available. As many as 1991 candidate genes (CGs) were also detected, which included 930 CGs with an expression level of > 2 transcripts per million in relevant organs/tissues. Among the CGs, 97 CGs with functions previously reported as important for the traits under study were selected. Based on homology analysis and expression patterns, 49 orthologues of 35 rice genes were also identified in MQTL regions. The results of the present study may prove useful for the improvement of selection strategy for yield potential, stability, and performance under N-limiting conditions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01085-0.