RDWN6XB, a major quantitative trait locus positively enhances root system architecture under nitrogen deficiency in rice

Empowering rice breeding with NextGen genomics tools for rapid enhancement nitrogen use efficiency

As rice has no physiological capacity of fixing nitrogen in the soil, its production had always been reliant on the external application of nitrogen (N) to ensure enhanced productivity. In the light of improving nitrogen use efficiency (NUE) in rice, several advanced agronomic strategies have been proposed. However, the soared increase of the prices of N fertilizers and subsequent environmental downfalls caused by the excessive use of N fertilizers, reinforces the prerequisite adaptation of other sustainable, affordable, and globally acceptable strategies. An appropriate alternative approach would be to develop rice cultivars with better NUE. Conventional breeding techniques, however, have had only sporadic success in improving NUE, and hence, this paper proposes a new schema that employs the wholesome benefits of the recent advancements in omics technologies. The suggested approach promotes multidisciplinary research, since such cooperation enables the synthesis of many viewpoints, approaches, and data that result in a comprehensive understanding of NUE in rice. Such collaboration also encourages innovation that leads to developing rice varieties that use nitrogen more effectively, facilitate smart technology transfer, and promotes the adoption of NUE practices by farmers and stakeholders to minimize ecological impact and contribute to a sustainable agricultural future.

Genome-wide association study using specific-locus amplified fragment sequencing identifies new genes influencing nitrogen use efficiency in rice landraces

Nitrogen is essential for crop production. It is a critical macronutrient for plant growth and development. However, excessive application of nitrogen fertilizer is not only a waste of resources but also pollutes the environment. An effective approach to solving this problem is to breed rice varieties with high nitrogen use efficiency (NUE). In this study, we performed a genome-wide association study (GWAS) on 419 rice landraces using 208,993 single nucleotide polymorphisms (SNPs). With the mixed linear model (MLM) in the Tassel software, we identified 834 SNPs associated with root surface area (RSA), root length (RL), root branch number (RBN), root number (RN), plant dry weight (PDW), plant height (PH), root volume (RL), plant fresh weight (PFW), root fractal dimension (RFD), number of root nodes (NRN), and average root diameter (ARD), with a significant level of p < 2.39×10^-7. In addition, we found 49 SNPs that were correlated with RL, RBN, RN, PDW, PH, PFW, RFD, and NRN using genome-wide efficient mixed-model association (GEMMA), with a significant level of p < 1×10^-6. Additionally, the final results for eight traits associated with 193 significant SNPs by using multi-locus random-SNP-effect mixed linear model (mrMLM) model and 272 significant SNPs associated with 11 traits by using IIIVmrMLM. Within the linkage intervals of significantly associated SNP, we identified eight known related genes to NUE in rice, namely, OsAMT2;3, OsGS1, OsNR2, OsNPF7.4, OsPTR9, OsNRT1.1B, OsNRT2.3, and OsNRT2.2. According to the linkage disequilibrium (LD) decay value of this population, there were 75 candidate genes within the 150-kb regions upstream and downstream of the most significantly associated SNP (Chr5_29804690, Chr5_29956584, and Chr10_17540654). These candidate genes included 22 transposon genes, 25 expressed genes, and 28 putative functional genes. The expression levels of these candidate genes were measured by real-time quantitative PCR (RT-qPCR), and the expression levels of LOC_Os05g51700 and LOC_Os05g51710 in C347 were significantly lower than that in C117; the expression levels of LOC_Os05g51740, LOC_Os05g51780, LOC_Os05g51960, LOC_Os05g51970, and LOC_Os10g33210 were significantly higher in C347 than C117. Among them, LOC_Os10g33210 encodes a peptide transporter, and LOC_Os05g51690 encodes a CCT domain protein and responds to NUE in rice. This study identified new loci related to NUE in rice, providing new genetic resources for the molecular breeding of rice landraces with high NUE.

Calcium signalling components underlying NPK homeostasis: potential avenues for exploration

Plants require the major macronutrients, nitrogen (N), phosphorus (P) and potassium (K) for normal growth and development. Their deficiency in soil directly affects vital cellular processes, particularly root growth and architecture. Their perception, uptake and assimilation are regulated by complex signalling pathways. To overcome nutrient deficiencies, plants have developed certain response mechanisms that determine developmental and physiological adaptations. The signal transduction pathways underlying these responses involve a complex interplay of components such as nutrient transporters, transcription factors and others. In addition to their involvement in cross-talk with intracellular calcium signalling pathways, these components are also engaged in NPK sensing and homeostasis. The NPK sensing and homeostatic mechanisms hold the key to identify and understand the crucial players in nutrient regulatory networks in plants under both abiotic and biotic stresses. In this review, we discuss calcium signalling components/pathways underlying plant responses to NPK sensing, with a focus on the sensors, transporters and transcription factors involved in their respective signalling and homeostasis.

Root system architecture in rice: impacts of genes, phytohormones and root microbiota

To feed the continuously expanding world's population, new crop varieties have been generated, which significantly contribute to the world's food security. However, the growth of these improved plant varieties relies primarily on synthetic fertilizers, which negatively affect the environment and human health; therefore, continuous improvement is needed for sustainable agriculture. Several plants, including cereal crops, have the adaptive capability to combat adverse environmental changes by altering physiological and molecular mechanisms and modifying their root system to improve nutrient uptake efficiency. These plants operate distinct pathways at various developmental stages to optimally establish their root system. These processes include changes in the expression profile of genes, changes in phytohormone level, and microbiome-induced root system architecture (RSA) modification. Several studies have been performed to understand microbial colonization and their involvement in RSA improvement through changes in phytohormone and transcriptomic levels. This review highlights the impact of genes, phytohormones, and particularly root microbiota in influencing RSA and provides new insights resulting from recent studies on rice root as a model system and summarizes the current knowledge about biochemical and central molecular mechanisms.

Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Oryza sativa L.)

The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.

Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach

Applying an integrated meta-analysis approach led to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits. Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA-related MQTLs were detected and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance-associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA), and lignification (e.g. C4H, PAL, PRX and CAD). The genes located within both the SNP peak positions and the QTL-overview peaks for RSA are suggested as novel candidate genes for further functional analysis. The promising candidate genes and MQTLs can be used as basis for genetic engineering and MQTL-assisted breeding of root phenotypes to improve yield potential, stability and performance in a water-stressed environment.

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.

Integration of Dual Stress Transcriptomes and Major QTLs from a Pair of Genotypes Contrasting for Drought and Chronic Nitrogen Starvation Identifies Key Stress Responsive Genes in Rice

We report here the genome-wide changes resulting from low N (N-W+), low water (N+W-)) and dual stresses (N-W-) in root and shoot tissues of two rice genotypes, namely, IR 64 (IR64) and Nagina 22 (N22), and their association with the QTLs for nitrogen use efficiency. For all the root parameters, except for root length under N-W+, N22 performed better than IR64. Chlorophyll a, b and carotenoid content were higher in IR64 under N+W+ treatment and N-W+ and N+W- stresses; however, under dual stress, N22 had higher chlorophyll b content. While nitrite reductase, glutamate synthase (GS) and citrate synthase assays showed better specific activity in IR64, glutamate dehydrogenase showed better specific activity in N22 under dual stress (N-W-); the other N and C assimilating enzymes showed similar but low specific activities in both the genotypes. A total of 8926 differentially expressed genes (DEGs) were identified compared to optimal (N+W+) condition from across all treatments. While 1174, 698 and 903 DEGs in IR64 roots and 1197, 187 and 781 in N22 roots were identified, nearly double the number of DEGs were found in the shoot tissues; 3357, 1006 and 4005 in IR64 and 4004, 990 and 2143 in N22, under N-W+, N+W- and N-W- treatments, respectively. IR64 and N22 showed differential expression in 15 and 11 N-transporter genes respectively, under one or more stress treatments, out of which four showed differential expression also in N+W- condition. The negative regulators of N- stress, e.g., NIGT1, OsACTPK1 and OsBT were downregulated in IR64 while in N22, OsBT was not downregulated. Overall, N22 performed better under dual stress conditions owing to its better root architecture, chlorophyll and porphyrin synthesis and oxidative stress management. We identified 12 QTLs for seed and straw N content using 253 recombinant inbred lines derived from IR64 and N22 and a 5K SNP array. The QTL hotspot region on chromosome 6 comprised of 61 genes, of which, five were DEGs encoding for UDP-glucuronosyltransferase, serine threonine kinase, anthocyanidin 3-O-glucosyltransferase, and nitrate induced proteins. The DEGs, QTLs and candidate genes reported in this study can serve as a major resource for both rice improvement and functional biology.

Fine mapping and candidate gene analysis of qRN5a, a novel QTL promoting root number in rice under low potassium

KEY MESSAGE: qRN5a, a novel QTL for increasing root number under low K in rice, was fine mapped to a 48.8-kb region on chromosome 5, and LOC_Os05g27980 is the most likely candidate gene. Potassium (K) is a mineral nutrient essential for plant growth and development, but the molecular mechanism for low-K (LK) tolerance in rice remains poorly understood. In our previous study, the quantitative trait locus (QTL) qRN5a for root number (RN) under LK was identified in the chromosome segment substitution line CSSL35 carrying segments from XieqingzaoB in the genetic background of Zhonghui9308 (ZH9308). CSSL35 developed more roots than ZH9308 under LK at the seedling stage, and qRN5a was initially located within a 1,023-kb genomic region. In this study, to understand the molecular basis of qRN5a, a large F_2:3 (BC₅F_2:3) population obtained from crossing CSSL35 and ZH9308 was constructed for fine mapping. High-resolution linkage analysis narrowed down qRN5a to a 48.8-kb interval flanked by markers A99 and A139. Seven putative candidate genes were annotated in the delimited region, and three genes (Os05g0346700, LOC_Os05g27980, and LOC_Os05g28000) had nonsynonymous single-nucleotide polymorphisms in the coding sequence between the two parents. Expression analysis suggests that LOC_Os05g27980, which encodes a LATERAL ORGAN BOUNDARIES domain-containing protein, is a positive regulator of RN under LK and is the most likely candidate gene for qRN5a. Moreover, we found that qRN5a promotes expression of OsIAA23 and represses OsHAK5 expression in root tissues to promote root initiation in CSSL35 under LK conditions. Additional investigations on OsHAK5 in rice are needed to elucidate the basis of changing root architecture under different K⁺ concentrations. qRN5a is useful for marker-assisted selection to develop an ideotype with improved root architecture in rice under K deficiency.

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

Nitrogen-use efficiency (NUE) is a function of N-response and yield that is controlled by many genes and phenotypic parameters that are poorly characterized. This study compiled all known yield-related genes in rice and mined them from the N-responsive microarray data to find 1,064 NUE-related genes. Many of them are novel genes hitherto unreported as related to NUE, including 80 transporters, 235 transcription factors (TFs), 44 MicroRNAs (miRNAs), 91 kinases, and 8 phosphatases. They were further shortlisted to 62 NUE-candidate genes following hierarchical methods, including quantitative trait locus (QTL) co-localization, functional evaluation in the literature, and protein-protein interactions (PPIs). They were localized to chromosomes 1, 3, 5, and 9, of which chromosome 1 with 26 genes emerged as a hotspot for NUE spanning 81% of the chromosomes. Further, co-localization of the NUE genes on NUE-QTLs resolved differences in the earlier studies that relied mainly on N-responsive genes regardless of their role in yield. Functional annotations and PPIs for all the 1,064 NUE-related genes and also the shortlisted 62 candidates revealed transcription, redox, phosphorylation, transport, development, metabolism, photosynthesis, water deprivation, and hormonal and stomatal function among the prominent processes. In silico expression analysis confirmed differential expression of the 62 NUE-candidate genes in a tissue/stage-specific manner. Experimental validation in two contrasting genotypes revealed that high NUE rice shows better photosynthetic performance, transpiration efficiency and internal water-use efficiency in comparison to low NUE rice. Feature Selection Analysis independently identified one-third of the common genes at every stage of hierarchical shortlisting, offering 6 priority targets to validate for improving the crop NUE.

Improvement of nutrient use efficiency in rice: current toolbox and future perspectives

Modern agriculture relies heavily on chemical fertilizers, especially in terms of cereal production. The excess application of fertilizers not only increases production cost, but also causes severe environmental problems. As one of the major cereal crops, rice (Oryza sativa L.) provides the staple food for nearly half of population worldwide, especially in developing countries. Therefore, improving rice yield is always the priority for rice breeding. Macronutrients, especially nitrogen (N) and phosphorus (P), are two most important players for the grain yield of rice. However, with economic development and improved living standard, improving nutritional quality such as micronutrient contents in grains has become a new goal in order to solve the "hidden hunger." Micronutrients, such as iron (Fe), zinc (Zn), and selenium (Se), are critical nutritional elements for human health. Therefore, breeding the rice varieties with improved nutrient use efficiency (NUE) is thought to be one of the most feasible ways to increase both grain yield and nutritional quality with limited fertilizer input. In this review, we summarized the progresses in molecular dissection of genes for NUE by reverse genetics on macronutrients (N and P) and micronutrients (Fe, Zn, and Se), exploring natural variations for improving NUE in rice; and also, the current genetic toolbox and future perspectives for improving rice NUE are discussed.

Genetic Analysis for Cooking and Eating Quality of Super Rice and Fine Mapping of a Novel Locus qGC10 for Gel Consistency

Rice (Oryza sativa L.) is an important cereal that provides food for more than half of the world's population. Besides grain yield, improving grain quality is also essential to rice breeders. Amylose content (AC), gelatinization temperature (GT) and gel consistency (GC) are considered to be three indicators for cooking and eating quality in rice. Using a genetic map of RILs derived from the super rice Liang-You-Pei-Jiu with high-density SNPs, we detected 3 QTLs for AC, 3 QTLs for GT, and 8 QTLs for GC on chromosomes 3, 4, 5, 6, 10, and 12. Wx locus, an important determinator for AC and GC, resided in one QTL cluster for AC and GC, qAC6 and qGC6 here. And a novel major QTL qGC10 on chromosome 10 was identified in both Lingshui and Hangzhou. With the BC₄F₂ population derived from a CSSL harboring the segment for qGC10 from 93-11 in PA64s background, it was fine mapped between two molecular markers within 181 kb region with 27 annotated genes. Quantitative real-time PCR results showed that eight genes were differentially expressed in endosperm of two parents. After DNA sequencing, only LOC_Os10g04900, which encodes a F-box domain containing protein, has 2 bp deletion in the exon of PA64s, resulting in a premature stop codon. Therefore, LOC_Os10g04900 is considered to be the most likely candidate gene for qGC10 associated with gel consistency. Identification of qGC10 provides a new genetic resource for improvement of rice quality.

Morphological study of different varieties of rice traits influencing nitrogen and water uptake efficiency

This research aimed at establishing the morphology of the root and sizes under various irrigation cultures. The comparison was made for root to shoot ratio under the traditional culture of flooding. We hypothesize that, due to limited root system development under aerobic conditions, rice is poorly adapted to different environments. In the meantime, there has to be an increase in demand for grain and output per area, as newly planted areas are scarce. This study discusses the latest theoretical physiological, metabolic and genetic factors affecting nitrogen intake and use in different N processes. It covers the root system's position and nitrate- ammonium assimilation and its relationship with Nitrogen Use Efficiency (NUE) and Water Use Efficiency (WUE), were discussed. Phenotyping and molecular breeding techniques concerning N and water regimes and genetic diversity were also evaluated and simulated.