Nitrogen Use Efficiency in Wheat: Genome to Field

Abstract

Nitrogen (N), being the most limiting macroelement for optimal plant growth and development needs synthetic N fertilizer usage for uplifting crop yields; nevertheless, an excessive and inefficient use of N fertilizer is a global concern incurring high production costs, environment pollution, and greenhouse gas emissions. Hence, developing crop plants with high nitrogen use efficiency (NUE) is an essential research target to achieve a better agricultural sustainability. NUE being a complex trait depends on our understanding of genetics (G), environment (E), management (M), and their interrelationships (G x E x M). NUE improvement is preceded by key processes such as nitrogen capture, utilization efficiency, nitrogen partitioning, trade-offs between yield and quality aspects, as well as interactions with the capture and utilization of other nutrients. An in-depth knowledge can be attained on NUE mechanisms through the UK Wheat Genetic Improvement Network project (http://www.wgin.org.uk/) using an integrated strategy that look into the physiological, metabolic, molecular, and genetic aspects influencing NUE in wheat. The current book chapter highlights the recent progress in understanding and improving NUE in wheat, focussing on N impact on plant morphology and agronomic performances, using a combination of approaches, including whole-plant physiology and quantitative, forward and reverse genetics.

1. Introduction

Cereal crops are widely farmed across the world in comparison to other crops. Rice (Oryza sativa L.), wheat (Triticum aestivum L.), and maize (Zea mays L.) are the most significant cereals in terms of human nutrition, accounting for 90% of global grain output. Since the Green Revolution, the importance of cereal crops in world agriculture has expanded dramatically. Of them, wheat is well-known to redeem global protein and calorie demands, either directly or indirectly in animals [1]. A number of factors have been found to influence the quality and quantity of cereal crops produced across the world; nitrogen availability is one of them. All plants require an external supply of N as in inorganic form, it functions as a key component of biomolecules, such as proteins, nucleic acids, chlorophyll, and various secondary metabolites. Nitrogen availability is a limiting factor in agricultural activities, and roughly 100 TgNyr⁻¹ of reactive nitrogen is administered to crop fields in the form of fertilizers globally [1]. Total N fertilizer usage has increased globally, from 112.5 million tonnes in 2015 to 118.2 million tonnes in 2019. Nitrogenous fertilizer usage has been grown at a faster rate in various nations between 1970 and 2020. In cereals, yield is found to be closely related to nitrogen application [1]. Report says, more than 94 million tonnes of nitrogen fertilizer are applied to cereal crops each year, but unfortunately around only 40% of this is absorbed by the crops, with the rest dispersing in the environment, posing major environmental issues, such as water pollution and greenhouse gas emissions [2, 3]. Among all the cereal crops, barley shows the highest nitrogen recovery (63%), followed by maize (37%), wheat (35–45%), and rice (30–50%) [3]. Nitrogen recovery is affected by various factors, including crop type, ambient conditions, fertilizer type, management technique, and genotype-environment interactions. Fertilizer use will be anticipated to more than double by 2050, rising from 112 Mt in 2015 to 236 Mt in 2050 [4]. Around 50–70% of applied nitrogen is constantly lost in the plant-soil interaction. Overuse of commercially available fertilizers has led to pollution of the air, soil, and water, as well as depletion of natural resources, such as nutrients and water. Nitrogen builds in the soil when nitrogen availability exceeds crop nitrogen requirements, rendering plants sensitive to a variety of loss mechanisms. As a result, enhancing cereal crop resource use efficiency is necessary to mitigate the negative effects of higher output on the environment and natural resources. Improving nitrogen use efficiency (NUE) in cereals must be a goal in breeding efforts to lessen the impact of increased fertilizer usage on climate change and to manage sustainable feeding to the world’s rising population. To deal with nitrogen application concerns in fields, it is critical to understand the underlying process of nitrogen usage efficiency.

The utilization of Nin plants requires multiple phases, such as the initial N intake phase, followed by nitrogen reduction to usable forms, amino acid assimilation, translocation, and lastly, nitrogen remobilization to reproductive organs Figure 1 [5]. The grain yield per unit of nitrogen available in the soil is defined as NUE (nitrogen use efficiency) in the wheat crop Figure 1 [6]. NUE analysis gives information on plant responses to diverse nitrogen availability conditions. Nitrogen use efficiency may be quantified using a variety of formulas and ideas. Cereal NUE is determined by how efficiently plants gather nitrogen (uptake efficiency, NUpE) and how efficiently plants use the nitrogen that has been taken up (utilization efficiency, NUtE) Figure 1 [7]. NUpE is calculated by dividing the total amount of above-ground nitrogen content during harvest by the available N in the soil, whereas NUtE is calculated by dividing the nitrogen in grain tissues by the N in above-ground plant biomass at harvest (Figure 1). As a result, NUE is determined at harvest, i.e., at the conclusion of the crop cycle. The agronomic efficiency of plants evaluates the efficiency with which they convert applied nitrogen to grain yield, whereas the apparent nitrogen efficiency of plants absorbs nitrogen from the soil [8]. The physiological efficiency of plants is determined by the amount of nitrogen collected and converted to grain production. For major cereal crops, improving resource use efficiency is a must to mitigate the negative effects of greater yield with increased input consumption on the environment and natural resources. The challenge here is to pick the most fertilizer-sensitive stage, to create a plant that maximizes early nitrogen uptake, and to have qualities, such as early vegetative vigor and a large root system for effective fertilizer uptake, all while considering above and below ground components. Later in the growth phase, a plant’s ability to absorb and remobilize available nitrogen and carbon to the grain is crucial. Major issues include appropriate root phenotyping, genotype x environmental interactions, soil characteristics, water-nutrient management, and nutrient dynamics balance. The primary question is whether it is feasible to improve nutrient absorption while reducing excessive fertilizer input and safeguarding soil health while maintaining optimal production and grain protein content. Nanotechnology, particularly the use of nanofertilizers (1–100 nm in size), is helpful and has been shown to have positive outcomes, while a further study on the impact of nanofertilizers on specific crops is required [9]. Before delving into the biochemistry and genetics of nitrogen use efficiency improvement in cereal crops, it is necessary to comprehend the new potential source of nitrogen fertilizers, the effect of nitrogen at various stages of growth, the nitrogen status of the crop, and development and NUE in the effect of fertilizers [10]. Anhydrous ammonia (82% N), urea (46% N), ammonium nitrate (34% N), ammonium nitrate sulfate (26% N), and aqua ammonia (25% N) are among the fertilizer sources. Organic and inorganic nitrogen fertilizers are the two primary categories of nitrogen fertilizers. In terms of inorganic fertilizers, anhydrous ammonia application contributes the most nitrogen, i.e., greater than 80%. Aqua ammonia, also known as ammonium hydroxide, is the second most significant source of inorganic nitrogen fertilizers and comprises 25–29% ammonia by weight. Another type of nitrogen fertilizer is ammonium nitrate, which is an agronomically relevant mixture of two distinct types of nitrogen (NH₄NO₃). This type of fertilizer is said to improve wheat baking quality [11]. Urea [CO(NH₂)₂] is an organic kind of fertilizer [12].

Figure 1.

Schematic representation of the relationship between the nitrogen sources, uptake, utilization, and conversion to the wheat grain yield.

The grain crop goes through numerous stages of development and growth. The rate of nutrient absorption in wheat varies with growth stage, variety, growing conditions, and environment. Detailed research of wheat’s nutrient absorption mechanisms is required to determine the optimal time and exact stage of fertilizer applications. Small amounts of nitrogen are required for seedling viability in the early stages. The mid-tillering stage uses almost half of the nitrogen required [13]. A high nitrogen dose, on the other hand, may damage seedlings and increase vegetative growth early in the season, resulting in poorer yields. Excess nitrogen might cause crop maturity to be pushed back. Nitrogen demand is said to be influenced by a number of factors, and NUE decreases when nitrogen application exceeds demand [14]. NUE is impacted by a number of variables [15], including soil type, the availability of other macro and micronutrients (phosphorus, potassium, etc.) in the soil, and crop rotation, which has been proven to affect nitrogen absorption and utilization [16]. Nitrogen fertilization is influenced by the intensity, timing, and depth of tillage [17, 18]. The most active subject of study to boost N fertilization yield is developing strategies for assessing nitrogen status. Satellite imaging [19], portable hyperspectral sensors [20], drones, chlorophyll meters (SPAD), red edge optical reflectance (R750/R710) [21], NDVI (normalized vegetation index), and RVI (ration vegetation index) [19] all offer the possibility of N estimation in less time.

Wild and primitive cereal crop species are currently undervalued as a source of unique nutrient utilization efficiency differences. Association studies exploiting the best alleles to be assembled in superior varieties, as well as the identification and characterization of candidate genes with non-synonymous and regulatory SNPs, will aid breeders in selecting specific donors to develop resource-efficient high-yielding wheat varieties. Furthermore, because yield and grain protein content, which represent nitrogen use efficiency, are inversely related, it is critical for breeders to design cultivation programs that achieve comparatively successful NUE without sacrificing grain yield [22], and it is critical to understand the details of various genetic, physiological, and biochemical factors affecting NUpE and NUtE to develop such cultivars.

Agronomic practices and field management also had a role in avoiding nitrogen loss to the environment [23]. The present chapter focuses on the myriad biochemical and genetic factors that influence NUE in both direct and indirect ways. The biochemistry of nitrogen absorption and utilization, as well as the genetic system that controls NUE in cereals and the phenotypic results that positively influence NUE, are all covered in this chapter. The associated cereals study will aid in the development of approaches for enhancing NUE while maintaining other desirable characteristics.

2. Traits affecting nitrogen utilization efficiency

2.1 Root architecture

Nutrient availability has a big influence on root growth and root system design. To present, little is known about the root architectural plasticity features, genetic foundation, mechanism, control, and function [24] linked to nutrient absorption. The root architecture is thought to be a key factor in NUE enhancement [25]. In cereal crops (wheat, rice, and maize), root systems can be separated into two types—embryonic (seminal roots) and post-embryonic roots (crown roots). The “steep, inexpensive, and deep” root architecture explains nutrient absorption, especially nitrogen absorption, rather well [26]. It specifies that main roots are responsible for obtaining nitrogen from deeper layers, whilst lateral roots with steep angles are responsible for covering a larger area of soil [27]. Lateral roots are said to be more vulnerable to biotic and abiotic stress, as well as fluctuating nitrogen concentration. Low nitrogen concentration promotes lateral root initiation in the early stages, while severe nitrogen deprivation prevents root emergence and elongation. In the soil, a high nitrate to ammonia ratio had a favorable effect on lateral root length [28].

Understanding the role of root traits in nutrient uptake and dissecting the genetic basis to maximize the potential to breed high-yielding resource-efficient varieties of cereal crops by using modern biotechnological and bioinformatic approaches is required to address the challenge of efficient nutrient uptake. It is critical to uncover the latent potential of root characteristics for enhancing nutrient absorption and identifying important marker correlations that may be used in molecular breeding to develop resource-efficient cultivars. The use of a suitable root prototype as well as strong marker-trait associations/QTL/candidate genes may help to solve the problem of nutrient insufficiency and inadequate nutrient absorption. Efforts to design a robust root system architecture that combines a variety of root traits (nodal root, root hair length, root hair density, root length density, root dry weight, percent lateral root, root branching, root thickness, and root volume) could be a solution to the problem of efficient nutrient uptake, particularly nitrogen (N) (Figure 2). The development of root architecture is said to be influenced by a number of elements both above and below ground [25]. At different phases of crop growth and development, different root characteristics are critical for nutrient absorption. Root size and morphological features are directly related to nitrogen uptake efficiency, as it has been observed that among the various forms of nitrogenous compounds present in the soil, particularly nitrate, easily escapes the soil system through leaching, implying the need to improve nitrogen uptake by improving root architecture, including depth, density, and capacity of roots for post-anthesis N uptake [29]. Although primary investigations in Arabidopsis were conducted to determine the molecular regulation of root architecture, multiple homologs in rice and other cereal crops have been found [30]. In wheat, the NAM, ATAF, and CUC transcription factors (TaNAC2-5A) stimulated root growth, whereas the NUCLEAR FACTOR Y (TaNFYA-B1) accelerated root development [31].

Figure 2.

Role of above and below ground N-affecting factors, G × E × M interactions playing significant roles in the development of root architecture at different stages of plant development.

In wheat, root growth was found to have an important role in increasing nitrogen absorption [32]. As a result, the rooting profile required for nitrate absorption at lower depths was investigated by measuring root length density at a threshold of 1 cm/cm³ [33], where root length density is a measurement of root length per unit volume of soil [24]. Wheat roots showed a significant level of genetic diversity [24, 34]. Furthermore, a variety of environmental conditions, including soil type and nutrient availability, have a significant impact on root spreading characteristics. Deeper rooting systems have been observed in Aegilops tauschii (D genome), a wild cousin of wheat. The found candidate genes might be used in genomics-assisted breeding strategies to create cultivars with reasonably deep root systems. Under low nitrogen circumstances, an increase in the root biomass to total plant biomass ratio (root dry weight ratio; RDWR) was reported to preserve the functional balance between root and shoot development [35]. Even with a limited nitrogen supply, the increase in root-shoot biomass eventually increased crop growth rate (CGR), resulting in better grain production and improved NUE.

Along with root length and density, root hairs are an essential feature to consider for increased nitrogen absorption by active transport. Root hairs play a significant role in increasing the surface area of roots, which may boost nitrogen uptake by active transport. It is challenging to target specific genes for enhanced nitrogen absorption since root structure and function appear to be the result of the cumulative influence of numerous genes [36]. The strategy for increasing nitrogen absorption comprises marker-assisted selection and pyramiding numerous advantageous characteristics. The quantitative trait loci (QTL) for traits, such as root length, root hair number, root density, root angle, and root-to-shoot ratio, are well established in wheat [37, 38], but there is a need to understand the mechanism of orchestrated expression of multiple traits affecting root architecture to positively influence nitrogen uptake.

2.2 N transporter systems in roots

Nitrogen transporters for nitrate (NO³⁻), ammonium (NH⁴⁺), amino acids or peptides, and urea are involved in nitrogen absorption [39, 40]. Nitrogen accumulation by roots is an active process that is mediated by a specific type of nitrogen transport protein. The most common inorganic form of nitrogen in the rhizosphere is NO⁻₃, NH⁺₄ is also present in the soil, although at much lower concentrations than NO³⁻ [41]. The uptake and transport of nitrate in plants are mediated by five transporter families—the Nitrate Transporter 1/Peptide Transporter (NPF) family [42], the Nitrate Transporter 2 (NRT2) family, the Chloride Channel (CLC) family, the Slow Anion Associated Channel Homolog (SLC/SLAH) family, and aluminum-activated malate transporters (ALMT) [42]. Among the five families described above, NPF and NRT2 have been linked to nitrate absorption and plant localization.

Several kinds of plasma membrane-associated transporter proteins have been identified as being engaged in active transport and have been classed as high- and low-affinity transporters [43, 44]. In higher plants, three types of transport systems are active based on affinity and NO³⁻ content in the rhizosphere—inducible high-affinity transport system (iHATS), constitutively expressed high-affinity transport system (cHATS), and nonsaturable low-affinity transport system (LATS). iHATS is activated at low NO³⁻ concentrations (1–200 lM), and its activity varies depending on plant type and environmental conditions [45]. In wheat, iHATS has a Michaelis constant (Km) of around 27 lM and requires a 10-h induction time before commencing the transport process [46] cHATS, as the name implies, is constitutively produced and exhibited on the plasma membrane even in the absence of NO³⁻. Both cHATS and iHATS have the trait of becoming saturated once the external NO³⁻ concentration reaches a particular threshold. The third, LATS, has low-affinity transporters and is activated when there is a high concentration of NO³⁻ in the soil (250 lM). Unlike cHATS and iHATS, LATS contains nonsaturable transporters [47]. NRT1 and NRT2 are two important gene families involved in NO³⁻ transport in higher plants. NRT1/PTR stands for nitrate transporters, the peptide transporter family (NPF), and the main facilitator superfamily (MFS) of the NRT2 family [42]. In the absence of NO³⁻, the plant growth hormone abscisic acid activates the high-affinity transport system in wheat, which is controlled by five genes (TaNRT 2.1, TaNRT 2.2, TaNRT 2.3, TaNAR 2.1, and TaNAR2.2) [48]. LATS belongs to the ammonium methylammonium permeases/transporter/Rhesus (MEP/AMT/Rh) family of NH⁴⁺ permeases and is implicated in NH⁴⁺ uptake among the three transporter systems examined so far [49]. The activity of these transporters is controlled by post-translational processes, such as phosphorylation, which maintains the quantity of ammonia stored in the plant system under control [25, 50]. Because urea absorption in wheat is so low relative to other inorganic nitrogen sources, determining the kinetics of urea uptake can be problematic [51]. Ammonia, nitrate, and urea are all known to affect the expression of high-affinity urea transporters [52]. However, because urea is mostly utilized as a nitrogen fertilizer in Asian agriculture, further research into the process of urea absorption and metabolic conversion to beneficial physiological components in plant systems is needed.

2.3 Effect of rhizospheric associations

The rhizosphere is the area of the soil that comes into direct contact with the root system, and the organisms that dwell there have a substantial influence on mineral intake, particularly nitrogen uptake by roots [53]. Many higher plants, including wheat, are believed to emit a variety of exudates, including organic acids and sugars, that have a direct influence on the physiological activities of microbes in the root system [54]. Several environmental factors, including climate, water level, soil type, and agricultural practices, also have an influence on these microbial communities [55]. The microbial ecology of the rhizosphere has also been discovered to differ among wheat cultivars [56, 57]. Through the denitrification process, several bacteria minimize nitrogen consumption by converting inorganic nitrates to gaseous nitrogen [58]. As previously stated, denitrification converts nitrogen into an inaccessible form, hence suppressing such processes improves nitrogen absorption; nevertheless, the mechanism in cultivated cereal crops is not well-known [59]. Several attempts have been made to transfer beneficial root-microbial traits from wild relatives of domesticated cereal crops to domesticated cereal crops. A chromosome from Leymusracemosus, a wild wheat relative capable of preventing nitrification in the root rhizosphere, was transferred into cultivated wheat varieties [60, 61].

Improved nitrogen fixation can boost root nitrogen absorption. Although these nitrogen-fixing bacteria are a natural component of the wheat root rhizosphere [62, 63], the artificial introduction of N fixers may increase nitrogen intake, which has a favorable effect on production [64, 65]. The main option for introducing the legume-like system of nitrogen fixation from bacteria to cereal crops is genetic engineering [66]. The non-host-specific endophyte Pseudomonas stutzeri and epiphyte Klebsiella oxytoca, which infiltrate the root systems of rice and wheat, are the most effective strains for nitrogen fixation [67]. Bacterial systems have a wide variety of nif gene clusters, ranging in size from 11 to 64 kb operons. The conserved section in these operons comprises nitrogenase (nifHDK) and cofactor (FeMoCo), while the rest of the operon specifies nitrogen fixation under various environmental circumstances [68]. Auxins [69], cytokinins [70], and gibberellins, all of which are regulated by microorganisms in the rhizosphere, were found to impact root architecture by boosting the production of growth hormones. Gibberellins produced by the rhizospheric bacteria and fungi have been reported to boost the primary root elongation and lateral root growth in wheat [71]. Root-associated organisms influenced nitrogen uptake as well as the activation of plant defense systems against pathogenic infections [72, 73]. The pathogenic defense-related transcriptional accumulates in wheat when infected with the bacterium Pseudomonas fluorescens Q8r1-96 [74]. Overall, the microbial association with nitrogen absorption is a broad issue that must be investigated and explored to improve nitrogen uptake efficiency in wheat and other cereal crops.

3. Traits associated with nitrogen utilization efficiency

3.1 Nitrate assimilation

Nitrate is an essential component of the nitrogen cycle and a major player in inorganic nitrogen assimilation in cereals [75]. The nitrate assimilation is primarily driven by its reduction and incorporation of nitrogen into the carbon skeleton to generate biologically active, organic nitrogen form. Nitrate uptake in plants is root transporter-mediated, inside root cells nitrate is targeted by nitrate reductase (NR) enzyme along with NAD(P)H cofactor. NR is the key enzyme that is involved in the very first step of nitrogen utilization and its conversion into biologically active molecules. It is reported that in hexaploid wheat two genes encode the NADH-dependent nitrate reductase [76]. NR leads to the conversion of nitrate into nitrite. Nitrite is further reduced to ammonia by the action of enzyme nitrite reductase (NiR) which is usually present in plastids of the plant cell [77]. In the case of NiR, ferredoxin is associated with NiR and the electrons for reduction are provided by ferredoxin [78]. Ammonia released by the action of NiR is used for amino acid formation. The primary amino acid involved in ammonia incorporation is glutamate. Glutamine synthetase (GS) and glutamate synthase (GOGAT) are the two enzymes that act in conjugation for amino acid formation [79]. GS is present in two isoforms in different cellular organelles. GS1 is prevalent in the cytosol of plant cells and GS2 works in plastids of roots and etiolated tissues [79]. It is reported that in wheat, the expression of GS2 is uniform throughout the plant development and comes to a halt toward maturity, and the expression of GS1 isoenzyme is consistently observed in senescing tissues and phloem [80]. Second enzyme GOGAt or glutamate synthase works with the primary enzyme in the formation of two amino acids glutamate and glutamine. These two amino acids are further involved in amino acid, nucleic acid formation by acting as donors of the amino group for nitrogen-containing compounds [79]. Two isomeric forms of GOGAT are present in the plant system. Both isoforms vary in terms of cofactors that they use and the process they are involved in. One is FD-GOGAT; this form is ferredoxin dependent; it is involved in the reassimilation of ammonia released from the cycle of photorespiration. The second isoform of GOGAT is NADH dependent which is primarily involved in amino acid synthesis which is channelized for protein formation involved in the growth and development of photosynthetic and accessory organs [79]. Almost 95% of ammonia availed by plants is dependent on GS and GOGAT as reported from several mutational studies [79]. These amino acids lead to increased protein formation which ultimately enhances productivity [81].

3.2 Carbon metabolism in N assimilation

Multiple factors are reported to affect nitrogen assimilation but carbon metabolism is the major player having direct interaction with nitrogen metabolic pathways. The role of photosynthesis on nitrogen accumulation was analyzed in different target plants to dissect the interaction between carbon and nitrogen metabolic pathways. It was observed that nitrogen assimilation was changed when the photosynthetic rate was changed and vice versa. This is so because carbon fixation requires enzymes, such as RuBISCO, and as enzymes are protein a continuous flow of amino acid is needed for enzyme formation which further depends upon nitrogen availability [82]. So, nitrogen is critically important as it affects the photosynthetic activity which further regulates crop yield. Along with it, nitrogen metabolism is dependent on carbon metabolism as most of the enzymes involved in nitrogen metabolism need electron donors for their activity which is provided by carbon metabolism. Along with it, the GS/GOGAT pathway requires a carbon skeleton (Ketoglutarate) for ammonia assimilation which is the product of the TCA (tri carboxylic acid) cycle, an important regulator of carbon metabolism. So, carbon skeleton and other accessory elements needed for nitrate assimilation are provided by the carbon cycle [83]. So, overall nitrate assimilation is an interlinked metabolic pathway where several factors of carbon metabolism are critically related. Therefore, NUE is affected directly by components of nitrogen metabolic pathways and indirectly by players of carbon metabolism [75]. So, while targeting breeding programs for enhanced NUE enzymes and proteins associated with nitrogen and carbon metabolism can be targeted.

3.3 Photosynthesis and canopy traits

As discussed earlier, carbon fixation is an important process of plant growth and development. Rubisco is the major enzyme regulating the most critical step of Calvin cycle. Rubisco is the most abundant protein in the biosphere. The nitrogen accumulated by the plant is directly related to the amount of Rubisco formed which further defines the photosynthetic activity of the mesophyll cells. Almost 75% of N in wheat leaves is driven toward Rubisco enzyme formation which is important for photosynthesis [84, 85]. It is reported that in nitrogen-limited conditions, Rubisco content decreases which lead to reduced photosynthetic activity and reduced organic matter production. It is observed that photosynthetic activity is associated with leaf morphogenesis as it is the main region for carbon fixation. Leaf structure and canopy directly affect the yield output in crop plants [86]. High NUE increases the nitrogen uptake and utilization which enhances source and sink abilities and increases dry matter output and crop yield. The theory of optimization for canopy photosynthesis indicates that the coefficient of both light gradient (KL) and nitrogen (KN) positively contributes to photosynthesis [86]. Although the gradients for nitrogen observed in wheat were less steep than optimization theory [86]. Nitrogen utilization is majorly affected by the photosynthetic rate per unit of nitrogen. In light-saturated conditions, the photosynthetic rate was increased by 20–30 lmol CO₂/m²/s for around 2 g N/m² in C₃ crops, such as wheat. The important aspect to target nitrogen utilization efficiency is to identify wheat cultivars with the capacity of accumulating around 2.0 g N/m² under favorable conditions. A wide range of genetic variability was observed among various wheat lines specific leaf nitrogen (SLN) which is an indicator of leaf nitrogen content per unit leaf area. In earlier, Araus et al. [87] were grown a panel of 144 durum wheat genotypes in two rain-fed conditions and 125 of these were grown under supplementary irrigation before heading stage, and revealed that the SLN in these genotypes varied from 1.4 to 2.6 g/m². Another study by Giunta et al. [88] reported that SLN varied from 2.1 to 2.4 g/m² for the 17 durum wheat cultivars. A study in 16 bread wheat cultivars SLN varied from 1.4 to 2.2 g/m² [86]. The nitrogen content in different tissues, including stem, leaf lamina, and leaf sheath, at anthesis show heritability of >0.60 under low nitrogen in winter wheat. So, these traits can be used in targeted breeding programs [89]. The genetic diversity associated with nitrogen utilization efficiency in wheat germplasm can be used to achieve the desired modification in photosynthetic components. It was reported earlier that around 30% improvement in photosynthesis can be attained by targeting photo-respiration, along with its other mechanisms contributing to 15–22% increase in photosynthetic activity [90]. There is a need to understand the intricacy of the molecular mechanisms affecting the pathways for leaf development, photorespiration, and majorly photosynthesis. The recent advancement in technologies for gene editings, such as CRISPR-Cas9 or specific promoter expression can be used in regulating pathways for leave development. This can generate diverse germplasm with high NUE and ultimately high yield potential [91].

3.4 N remobilization and senescence

Nitrogen distribution in the plant is source-sink relation dependent. Initially nitrogen uptake by roots acting as source and transpiration of absorbed nitrogen from roots to leaves and buds acting as major sink organ. This source-sink relation changes with the plant’s developmental stage, as it is observed that toward maturity the capability of the plant for nitrogen uptake decreases so the root does not act as a major source of nitrogen for the rest of the plant. During maturity, the leaf acts as a source, as toward senescence the old leaves die off and their protein components are degraded to release nitrogen which is remobilized to the younger leaves [92]. Leaf lamina is a major storage house of nitrogen in above-ground tissue during anthesis in wheat under optimal N supply. Other tissues, such as true stem, ear, and leaf sheath, also retain nitrogen [93], whereas the trend of nitrogen accumulation changes under nitrogen-limiting conditions, with more nitrogen in ears as compared to other parts of the plant [93]. Although, the NUE is majorly determined by nitrogen remobilization from leaves to its developing parts during the grain-filling stage which further defines the crop yield. So, during the grain-filling stage, the photosynthates and proteins stored in the older leaves act as a major source of nutrients for developing seeds. Autophagy is the basic mechanism that affects remobilization during the grain-filling stage. Autophagy is programmed cell death for the regulated release of stored compounds which is regulated by senescence-associated genes (ATG and metacaspases) [94]. Specific tissue-specific transporters are activated during the reproductive stage which is important for nitrogen remobilization. NRT1.7 is an important nitrogen transporter and its gene is reported to be controlled by nitrogen limitation adaptation regulators which are further under the control of miRNA827 [95]. This double-level control over tissue-specific nitrogen transporters suggests that the remobilization of nitrogen is tightly regulated. The remobilization process is under multiple regulatory controls along with transporters the enzymes, such as GOGAT, are reported to be involved in ammonia recycling during remobilization [96]. Along with its certain transcription factors, such as NAM-B1, efficiently increase nitrogen remobilization toward grains from mature leaves in wheat [97]. As in the case of cereals grain nitrogen, almost 50–90% is contributed by nitrogen from leaves [5]. The stage of nitrogen remobilization in grains from flag leaves can be used as a phenotypic marker [97]. As it is established that an inverse relation exists between grain yield and grain protein content, so higher grain yield is associated with delayed senescence of flag leaf in cereals. Among multiple proteins present in the leaf during senescence, the Rubisco (the most abundant protein in the biosphere) acts as a major contributor to remobilized nitrogen. In older leaves, chloroplast is degraded first as compared to other cellular components because of upregulation of proteases enzymes [98]. The tissue breakdown in older tissue is programmed by autophagy (chloroplast and Rubisco degradation) by the action of exopeptidases and endopeptidases present in cell vacuoles during senescence [98].

3.5 Stay-green phenotype

The stay-green phenotype is a marker for the tendency of a genotype to remain green during the grain-filling stage. The plants with stay-green phenotype remain photosynthetically active after anthesis [99]. Stay green-phenotype is a trait of interest to enhance NUE in plants and a wide range of genetic diversity is reported for this trait in hexaploid wheat [100]. Along with stay-green phenotypes traits, such as Rubisco degradation, and stem nitrogen assimilation are important targets for efficient nitrogen remobilization to the grains post-anthesis. The target of high yield with balanced protein content in wheat depends on an in-depth understanding of the mechanisms affecting post-anthesis nitrogen accumulation and remobilization toward developing grains.

3.6 Grain yield and grain protein content

In cereals, endosperm contributes to the maximum nutritive value of the grain due to its size ratio as compared to germ. The metabolic composition of endosperm is very essential for grain with high nutritive value. In cereals, starch is the prevalent biomolecule, along with its protein is also present with starch. Among different storage forms, Gluten is the major storage fraction of endosperm. Glutens have two components polymeric glutenins and monomeric gliadins. This storage protein contributes to 60–70% of the nitrogen in seed endosperm. Glutens provide the dough-making properties to wheat. Gliadin is responsible for dough viscosity and glutelins ensure dough elasticity. This dough-making capacity is important for consumable products of wheat, including pasta, bread, and noodles. The gluten synthesis is dependent on the protein accumulation which depends on the nitrogen utilization efficiency. Grain protein quality changes under different genetic backgrounds in wheat [101, 102]. Grain protein content and grain yield are both affected by NUtE although they are inversely related to each other [22, 103] which creates a barrier in attaining both simultaneously. The inverse relation between grain yield and grain protein content is due to metabolic competition between carbon and nitrogen fluxes for biomolecule accumulation [104], so dilution in NUtE depends on the accumulation of carbon-based compounds [105]. The efficient nitrogen in grain can be calculated by calculating grain protein deviation (GPD). GPD is a measure of deviation from the regression between grain protein concentration (GPC) and grain yield. Identification of genotypes with higher GPC from an expected GY can be estimated by calculating GPD [106]. In cereals, grain yield is dependent on coordinated regulation between several factors, majorly competition between photosynthesis and photorespiration [107]. The correlation between yield and nitrogen uptake and utilization is important for high wheat yields. There is a need to completely understand the mechanisms and regulatory pathways for nutrient uptake and its transport to stems, sheaths, leaves, and finally to developing grains. Along with this, it is important to understand the mechanisms for improvement of slow and ineffective filling of grains [108].

4. Genetic factors

The number of genetic factors is associated with controlling NUE traits for cereal crops that include majorly six categories—transporters, signal molecules, amino acid biosynthesis, nitrate assimilation, transcription factors, and other genes. The upregulation and downregulation of these genes depend on nitrogen levels in the environment and thus are controlled by mechanisms as discussed in the following text.

4.1 QTLs related to NUE

One of the complex quantitative traits is nitrogen use efficiency (NUE) which is controlled by multiple genes and dissected using a powerful tool called QTL mapping [109, 110]. A successful QTL mapping for such a complicated trait relies on various factors, such as the selection of suitable parents, appropriate population size, multi-location testing, and genome coverage. QTL is conventionally affected by environmental variation where constitutive QTL is consistent over environments, while adaptive QTL shows an expression in a specific environment, or modulates its effect with a change in an environment. QTL analysis provides ample opportunities to identify correlations among different traits. A genetically and functionally linked trait is evident through co-localized QTL linked to phenotypically different traits.

Nitrogen use efficiency of cereal crops can be improved by employing classical genetics involving both conventional breeding and QTL mapping in combination with marker-assisted selection (MAS). To develop genomic knowledge for complex genomes of cereal crops, such as wheat, advances in next-generation sequencing and agronomically relevant traits can now be identified [111]. Wheat improvement could be heightened with the identification of cheap, easy-to-use, widely distributed, codominant, trait-associated, and regulatory SNPs, candidate genes, and regulatory pathways. Association mapping studies assist in accessing allelic diversity and identifying the best alleles to be assembled in superior varieties. Accuracy for identifying QTL for nitrogen uptake and utilization-related traits can be improved by using high-throughput genotyping techniques. In this regard, several promising means have also been proposed, such as focusing on root architecture [112] or senescence and remobilization [113].

Previous case studies reported various QTLs for NUE in the model crop plant, i.e., Arabidopsisas as well as in other cereals, such as maize, rice, and wheat [25, 114]. Significant QTLs were detected in the wheat RIL population (TN18 × LM6) for grain yield; root NUE and shoot dry [115]. A major QTL was observed on the short arm of chromosome 6B controlling grain protein content in wheat accounting for 66% of the phenotypic variation where the cloning of functional gene named Gpc-B1 was carried out [97]. Various novel NUE-related traits and alleles in adapted breeding materials [116], landraces [117, 118], and wheat wild relatives [119] were identified. One such report is on winter wheat where the QTL associated with NUE on chr 1D, 6A, 7A, and 7D with LOD scores ranging from 2.63 to 8.33 and phenotypic variation up to 18.1% were instigated [120].

The identification of genomic regions (QTL) associated with nitrogen response would enable more efficient cultivar selection [121]. This approach allows breeders to proficiently develop high nitrogen use efficient cultivars by screening germplasm and studying the genetic markers associated with nitrogen response. As per previous work on rice and wheat, identification of the novel traits, alleles, genes/QTL, adapted breeding lines, landraces, and wild relatives improving NUE differences in cereal crops were well established. Using bi-parental populations, genes/QTL influencing nitrogen uptake have been mapped in wheat under different doses of fertilizer application [122, 123]. Genome-wide association studies for nitrogen uptake and use efficiency associated with variability and marker-trait selection have been reported [95, 124]. The development of synthetic wheat introgression libraries through Genome-wide association studies (GWAS) was made possible at Punjab Agricultural University, Ludhiana (India) to exploit their phenotypic variability. Several marker-trait associations related to root and plant morphological traits, grain yield, and yield-related traits have been well documented. Other than wheat, rice also shows highly conserved sequences, new genes, and regulatory elements to link genomes, genes, proteins, and traits controlling traits of interest across different species and genera through comparative mapping. These inter-genome relational patterns can lead to new hypotheses, knowledge, and predictions about the related species and can pave the way for genetic gain for future cereal crops.

5. Genes related to NUE

Regulation of nitrogen utilization efficiencies, such as nitrogen absorption, accumulation, and remobilization, is controlled by multiple sets of genes in crop plants (wheat, rice, etc.). These genes are majorly classified into six categories, including transporters, signal molecules, amino acid biosynthesis, nitrate assimilation, transcription factors, and other genes. The detailed description of genes regulating nitrogen use efficiency in wheat crops is presented in Table 1. Transporters and nitrate assimilation genes actively participate in nitrogen uptake, while amino acid biosynthesis genes are involved in nitrogen utilization. On the contrary, signaling molecules, transcription factors, and other genes have a passive role in both nitrogen uptake and nitrogen utilization [126, 127]. Nitrate, being the most common form of nitrogen present in soil needs to be transported in a plant which is done by nitrate transporters that encode for NRT families. The first reported case was studied in Arabidopsis where NRT families were categorized into two subfamilies, i.e., the NRT1 family (low-affinity transporters) and the NRT2/NRT family (high-affinity transporters) [128]. Using the reciprocal best hit (RBH) approach, orthologs of NRT transporter genes were found in cereal crops. It was observed that around 16 low-affinity nitrate transporter NPFs showed their expression in wheat which was homologous to Arabidopsis NPFs [125]. For an expression of transporter in wheat, information on the nitrogen status of the plant and soil is a prerequisite, thereby indicating its role in the regulation of NPF genes in wheat.

Category	Gene	Chr	Location	IWGSC Gene ID	References
Nitrogen transporters	TaNPF6.2	1A	373,766,258–373,768,702	TraesCS1A02G210900	[125]
	TaNPF6.5	1A	14,519,757–14,525,659	TraesCS1A02G031300	[125]
	TaNPF7.7	1A	355,624,056–355,628,073	TraesCS1A02G197600	[5]
	TaNPF7.7	1B	385,644,930–385,648,470	TraesCS1B02G212200	[5]
	TaNPF7.7	1D	284,040,636–284,044,349	TraesCS1D02G201100	[5]
	TaNPF2.3	2A	17,869,278–17,871,731	TraesCS2A02G045500	[125]
	TaNPF1.1	3A	540,654,271–540,656,804	TraesCS3A02G304400	[125]
	TaNPF2.4	3A	660,436,466–660,444,074	TraesCS3A02G418700	[125]
	TaNRT2.3	3B	457,633,984–457,635,782	TraesCS3B02G285900	[5]
	TaNRT2.3	3D	356,623,041–356,624,585	TraesCS3D02G254900	[5]
	TaNAR2.1	4A	640,232,228–640,233,158	TraesCS4A02G367300	[5]
	TaNRT1	4B	483,508,916–483,514,108	TraesCS4B02G231500	[5]
	TaNPF2.1	5A	3,085,412–3,088,853	TraesCS5A02G004400	[125]
	TaNPF2.2	5A	34,980,804–34,986,700	TraesCS5A02G037900	[125]
	TaNPF6.6	5A	599,204,895–599,208,619	TraesCS5A02G409600	[125]
	TaNPF6.1	6A	486,547,388–486,550,355	TraesCS6A02G263500	[125]
	TaNPF7.1	6AL/BL/DL	486,547,388–486,550,355	TraesCS6A02G263500	[125]
	TaNAR2.2	6B	415,788,848–415,790,024	TraesCS6B02G238700	[5]
	TaAMT1.2/1.3	6B	458,486,050–458,487,918	TraesCS6B02G254800	[5]
	TaNAR2.2	6D	267,236,634–267,237,837	TraesCS6D02G193100	[5]
	TaAMT1.2/1.3	6D	293,801,873–293,803,683	TraesCS6D02G208200	[5]
	NRT1 PTR	7A	169,020,411–169,025,550	TraesCS7A02G206400	[42]
	TaLHT1	7A	109,262,804–109,265,004	TraesCS7A02G156600	[5]
	TaNRT2.4	7B	583,923,053–583,926,829	TraesCS7B02G328700	[5]
N assimilation	TaNiR1	6B	636,392,631–636,397,024	TraesCS6B02G364600	[5]
	TaNiR1	6D	422,078,484–422,081,985	TraesCS6D02G313100	[5]
Amino acid biosynthesis (glutamine synthase)	TaAlaAT10–1/TaAlaAT-4	1A	71,689,760–71,695,155	TraesCS1A02G085600	[5]
	TaASN2	1A	553,535,726–553,542,082	TraesCS1A02G382800	[5]
	TaASP6	1A	287,681,550–287,684,692	TraesCS1A02G160200	[5]
	TaAlaAT10–1/TaAlaAT-4	1B	112,748,629–112,753,960	TraesCS1B02G102700	[5]
	TaASN2	1B	635,920,024–635,926,285	TraesCS1B02G408200	[5]
	TaASP6	1B	317,791,804–317,795,107	TraesCS1B02G176400	[5]
	TaASP6	1D	221,915,283–221,918,343	TraesCS1D02G157400	[5]
	TaGOX4	2D	301,816,850–301,819,891	TraesCS2D02G251800	[5]
	TaASP4	3A	541,257,235–541,261,301	TraesCS3A02G305400	[5]
	TaASP4	3B	536,074,881–536,079,450	TraesCS3B02G331100	[5]
	TaGOGAT1/3	3B	481,595,302–481,606,660	TraesCS3B02G299800	[5]
	TaGOGAT1/3	3D	369,790,549–369,802,074	TraesCS3D02G266400	[5]
	TaASN1	4B	417,737,785–417,741,607	TraesCS4B02G194400	[5]
	TaGS1	4B	499,898,695–499,901,767	TraesCS4B02G240900	[5]
	TaGGT2	4B	573,273,107–573,276,702	TraesCS4B02G288100	[5]
	TaGGT3	4B	363,644,060–363,647,074	TraesCS4B02G167100	[5]
	TaAlaAT10–2	5B	74,659,823–74,670,378	TraesCS5B02G066600	[5]
	TaAS	5B	107,190,378–107,196,256	TraesCS5B02G084600	[5]
	TaGDH1	5D	494,216,160–494,219,691	TraesCS5D02G442000	[5]
	TaASP1	6B	668,432,728–668,437,537	TraesCS6B02G393600	[5]
	TaGS1	6B	577,183,711–577,187,787	TraesCS6B02G327500	[5]
	TaGS1	6AL/BL/DL	531,394,366–531,398,363	DQ124209;DQ124210; DQ124211	[125]
Transcription factors	TaNF-YB2.1	1A	572,334,701–572,336,969	TraesCS1A02G411700	[5]
	TaNF-YB2.1	1B	662,783,949–662,786,278	TraesCS1B02G442000	[5]
	TaNF-YB2.2	3B	605,665,548–605,668,470	TraesCS3B02G385600	[5]
	TaNF-YB2.2	3D	458,624,044–458,626,934	TraesCS3D02G347000	[5]
	TaHLHm1	4B	639,452,139–639,453,299	TraesCS4B02G345800	[5]
	TaFBX94	5B	133,417,326–133,419,111	TraesCS5B02G100300	[5]
	TaHLHm4	5B	13,081,769–13,086,120	TraesCS5B02G013000	[5]
	TaHLHm4	5D	13,313,304–13,318,505	TraesCS5D02G020600	[5]
	TaNAC9/NAM	6B/1B	51,579,298–51,580,659	TraesCS6B02G075200	[5]
Other genes (kinases)	TaSAPK6	1A	381,819,326–381,822,599	TraesCS1A02G215900	[5]
	TaSAPK6	1B	411,987,863–411,990,884	TraesCS1B02G229400	[5]
	TaSAPK6	1D	304,838,300–304,841,343	TraesCS1D02G218200	[5]
(Rubisco)	Rbcs	2A	171,076,784–171,079,172	TraesCS2A02G198700	[89]

Table 1.

Genes associated with nitrogen use efficiency in wheat.

Nitrate transporters, although are the main players in nitrogen uptake in most plants, in certain cases, such as rice, ammonia is the predominant form in the soil. Nitrogen uptake is followed by nitrogen assimilation. A crucial metabolic step regulating the grain yield and NUE is the nitrogen uptake followed by nitrogen assimilation in the form of amino acids which is usually carried out by glutamine synthetase (GS)/glutamate synthase (GOGAT) cycle. Increased GS1 activity is observed in the leaves of wheat crop directing an accumulation of nitrogen in grains and also enhanced dry grain matter. At high N content, the GS1 gene gets overexpressed thereby enhancing the nitrogen harvest index and NUE while at low N content, NUE does not change. Nitrogen remobilization is the last step in nitrogen use efficiency (NUE) for seeds during maturity. Generally monocots, dicots, C₃, and C₄ plants share a common mechanism for the nitrogen remobilization [5]. Asparagine and glutamine are common amino acid transport forms for nitrogen remobilization from leaves to reproductive tissues catalyzed by enzymes GS and GOGAT, respectively [129]. In durum wheat, asparagine synthetase encoding genes (AsnS1) are prominent for nitrogen remobilization from flag leaf to developing grains where their concentration increase in phloem sap during senescence of leaves [130]. Leaf senescence affects high yield in cereal crops as even though delayed leaf promotes prolonged photosynthesis for improving grain yield, it however decreases nitrogen remobilization efficiency and grain protein content [5].

6. Transcription factors concerned with NUE

Plant regulatory network is governed by transcription factors and like several other metabolic processes, NUE imperatively relies on coordinated transcription factors presented in Table 1 [131]. Transcription factors for lateral root growth in response to nitrate belong to the MADS-box family analogous to ANR1, a transcription factor reported in Arabidopsis [132]. It is reported that DOF1.3 (DNA-binding with one finger) gene gets overexpressed in wheat under stress conditions, such as nitrogen starvation [132]. Differential expression studies between nitrogen-stressed and control durum wheat tissues are controlled by a total of 170 unique genes encoding transcription factors belonging to different families, including bHLH (helix loop helix), MYB, bZIP, C2C2-Dof, TERF, WRKY, NF-Y, NAC, AUX/IAA, and the auxin-modulated ARF, etc.

7. miRNA involved in NUE

miRNAs have been reported to play a significant role in NUE along with several transcription factors. The miRNA169 family is instigated to regulate the expression of genes for nitrogen transport in durum wheat under the nitrogen starvation stage in both roots and leaves [133]. In a recent study on the durum wheat plant, ttu-miR169h and ttu-miR169c at the seedling and grain-filling stages and ttu-novel-61 belonging to the miR169family showed down-regulation under nitrogen-deficient conditions in both roots and leaves. These miRNAs negatively regulate the CCAAT box-binding transcription factors in several tissues influencing NUE-related genes in durum wheat plants [133]. Another report indicated the role of the NAM-B1 gene in bread wheat as a NAC transcription factor that affects the grain nutrient concentration as well as increases the remobilization of nutrients from leaves to developing grains in wild wheat [134].

At low nitrogen levels, upregulation of TaMIR1129, TaMIR1118, and TaMIR1136 and downregulation of TaMIR1133 in roots of wheat were reported. The miRNA expression was inversely proportional to the concentration and duration of nitrogen application [135]. A gradual uprise in the expression of TaMIR2275 during nitrogen starvation was observed which was restored progressively once nitrogen level is recovered. Overexpression of produced plants with increased nitrogen accumulation and biomass is obtained from overexpression of TaMIR2275, while knockdown mutants showed the reverse. Inevitably, several classes of miRNAs are involved in nitrogen metabolism by altering multiple processes associated directly or indirectly with NUE. To comprehend, it is crucial to have a deep understanding of the precise network of miRNA expression and interaction for channelizing the mechanism underlying NUE.

The development of nutrient efficient varieties calls for the identification of suitable traits, and candidate genes underlying QTL that may provide new opportunities for the introgression of these QTL and genes into elite genetic backgrounds (Figure 3).

Figure 3.

Schematic representation of flow work to the development of nitrogen-efficient wheat genotypes.

8. Conclusion

Immense use of nitrogen fertilizers even though uplift grain yields of cereal crops, negatively affect the environment by causing water, soil, air pollution, and greenhouse gas emissions. It thus poses an economic impact globally due to the high production costs of nitrogen fertilizer. To combat this, the challenge to improve NUE in cereal crops lies in achieving both high yield and high nitrogen use efficiency (NUE) simultaneously. Crop improvement can be achieved by improving our knowledge of agronomic management, suitable traits, QTL, genes, and the mechanisms and functions of genes associated with nitrogen use efficiency. Selection of diverse genotypes, exploitation of natural variation, exploring root architecture, high-throughput precise phenotyping, standardized field trials, new techniques for efficient fertilizer application, appropriate field management practices, and identification of new QTL/genes/nitrogen transporters, as well as signaling molecules, could contribute in reducing fertilizer consumption in the near future. Thus, an improvement in basic research in combination with agronomical, marker-aided molecular breeding and biotechnological strategies will help to achieve higher nitrogen use efficiency in cereal crops.