miRNA mediated regulation of nitrogen response and nitrogen use efficiency of plants: the case of wheat

Abstract

Nitrogen (N) is needed for plant growth and development and is the major limiting nutrient due to its higher demand in agricultural production globally. The use of N fertilizers has increased considerably in recent years to achieve higher cereal yields. High N inputs coupled with declining N use efficiency (NUE) result in the degradation of the environment. Plants have developed multidimensional strategies in response to changes in N availability in soil. These strategies include N stress-induced responses such as changes in gene expression patterns. Several N stress-induced genes and other regulatory factors, such as microRNAs (miRNAs), have been identified in different plant species, opening a new avenue of research in plant biology. This review presents a general overview of miRNA-mediated regulation of N response and NUE. Further, the in-silico target predictions and the predicted miRNA-gene network for nutrient metabolism/homeostasis in wheat provide novel insights. The information on N-regulated miRNAs and the differentially expressed target transcripts are necessary resources for genetic improvement of NUE by genome editing.

Introduction

Plants require 17 essential elements to reach their full growth potential, of which 14 mineral elements are absorbed from the soil. Nitrogen (N) is considered to be one of the most crucial nutrient (contributing 2% of plant dry matter) that plants absorb in higher amounts compared to other elements (Miller and Cramer 2005). Hence, N is one of the limiting factors for the growth of plants in terms of availability (Ueda et al. 2017). Nitrogen is a constituent of important macromolecules such as proteins, nucleic acids, pigments and secondary metabolites (Oijen and Levy 2004). The atmospheric concentration of gaseous N is approximately 78%, however, plants only use it if fixed by N-fixing microorganisms (Erisman et al. 2008) or by industrial fixation. The quantity of N fixed annually through biological fixation accounts for more than 2 × 10¹³ g, while atmospheric N fixation through lightning and thunder accounts for 10¹² to 10¹³ g annually (Raymond et al. 2004). The contribution of natural fixation of N has become minimal due to the advances in biological N fixation (BNF) mechanisms in plants (Silver and Postgate 1973). Since the introduction of the Haber–Bosch ammonia synthesis process, synthetic N fertilizers are now significant contributors to crop productivity worldwide (Hirel et al. 2007). According to Zhang et al. (2015), around 50% of the global population has benefitted from food security since the introduction of industrial N fixation. Currently, 170 million tonnes of ammonia are produced annually worldwide, consuming large amounts of non-renewable fossil fuels and the accompanying carbon footprint (Soloveichik 2019). Nitrogenous fertilizers are prone to leaching, volatilization and denitrification losses leading to environmental pollution (Kubota et al. 2018). Plants have developed adaptive strategies to tolerate low N stress, such as retardation in vegetative growth, reduction in photosynthesis, remobilization of N reserves to younger tissues, senescence of older leaves, early progression to the reproductive phase and anthocyanin accumulation (Liang and He 2018). It has been reported further that N use efficiency (NUE) of cereals is as low as 33% throughout the world, meaning more than 60% of applied N is lost and unavailable to plants (Hawkesford 2017). To make farming cost-effective and eco-friendly, the improvement of NUE is essential Hawkesford and Griffiths (2019).

MicroRNAs (miRNAs) are a group of small RNAs, single-stranded, non-coding and play an array of regulatory roles (Kidner and Martienssen 2005). Most plant miRNAs are 21 nt in length; some are 20 or 22 nt, long while, and 23- or 24-nt miRNAs are rare (Zhan and Meyers 2023). miRNAs regulate developmental and metabolic processes, including response to nutrients (Meng et al. 2010). miRNAs regulate adaptation to N limitation conditions, including alterations in N uptake, growth, development, phenology, crop architecture and secondary metabolite production (Nguyen et al. 2015; Jagadhesan et al. 2022). miRNAs have become novel targets to improve plants’ tolerance to abiotic stresses in the recent past (Zhang and Wang 2015). miRNA156, one of the well-characterized plant miRNAs, regulates plant morphology and phase changes. Studies showed that overexpression of miR156 imparts heat stress tolerance to plants (Matthews et al. 2019; Stief et al. 2014). Among plants’ largest miRNA families conserved, miR169 is another potential target for abiotic stress tolerance. When miR169 is overexpressed in transgenic plants, water loss is significantly reduced, giving better drought tolerance (Zhang et al. 2011). miR169overexpression in Arabidopsis resulted in sensitivity to N stress (Zhao et al. 2011). Constitutive expression of miR319 increased drought and salinity stress tolerance in creeping bentgrass (Zhou et al. 2013). Another study showed that overexpression of miR319 confers cold stress tolerance in rice (Yang et al. 2013). miR395 confers tolerance to heavy metals like cadmium in rapeseed (Zhang et al. 2013). Genomics and transcriptomics studies have identified several candidate genes and transcripts, including miRNAs related to N stress and NUE (Meyer et al. 2019; Zuluaga and Sonnante 2019). Although most of these studies were confined to model plants in the past, the advancement of technologies and wheat NGS data widened the scope of characterization and application of NUE aspects in the genetic improvement of wheat. In this review, we describe various aspects of NUE and N stress-related responses in plants with a detailed description of N stress-responsive plant miRNAs in different tissues and developmental stages. In silico analysis was conducted to predict miRNAs targeting NUE-associated genes in wheat. A miRNA-mRNA network has also been established to gain insight into their relationship in a tissue-specific manner. This will encourage further research about the expression and regulatory pathways related to such networks.

Crop responses to N and nitrogen use efficiency (NUE)

According to Moll et al. (1982), NUE is the ratio between grain dry weight and available N from different sources of plants. NUE has two major components: N uptake efficiency (NUpE) and N utilization efficiency (NUtE). Besides, Craswell and Godwin (1984) gave another three aspects of NUE, including agronomic efficiency (AE), apparent nitrogen recovery (AR) and physiological efficiency (PE). The different NUE parameters were described by Good et al. (2004). Since the approximate N recovery of the crops is 25–50% (Kubota et al. 2018), reducing the use of N fertilizers to maintain good yield is a worldwide challenge (Foulkes et al. 2009; Hirel et al. 2007). Plants show two-way responses under N deficiency. Firstly, plants decrease leaf elongation in the initial phase under low N, resulting in less shoot growth without altering the photosynthetic rate. The photosynthate is preferentially transported to root parts, boosting root growth (Werf and Nagel 1996). Plants remobilize the N reserves and increase nitrate uptake from soil. In the second phase, cellular macromolecules (nucleic acids and enzymes) start degrading, resulting in cell death and leaf senescence (Brandner et al. 1996, 1998). Plants depict changes in root architecture and increase in root-shoot ratio when exposed to prolonged N deficit. Nitrate, the predominant N form in agricultural soils, regulates primary and lateral root growth. There is an intrinsic relationship between auxin signalling pathways and nitrate supply for lateral root (LR) initiation. Auxin receptor Auxin signalling F-box 3 (AFB3) is induced by nitrate. LR initiation, induced by nitrate supply, is significantly reduced in auxin receptor afb3 mutant (Vidal et al. 2014). NAC4 transcription factor is an essential regulator in the downstream network of AFB3 in response to nitrate such that in nac4 mutant, LR initiation is reduced under nitrate supply (Vidal et al. 2013). NPF6.3 (CHL1/AtNRT1.1) and ANR1 MADS-box transcription factor induces meristem growth at the LR tip under nitrate treatment (Remans et al. 2006; Zhang and Forde 1998). Overexpression of ANR1 improves nitrate-responsive LR elongation without affecting primary root growth (Gan et al. 2005). At low external nitrate conditions, NPF6.3 helps in the basipetal transport of auxin at the LR tip, which reduces auxin concentration at the LR meristem reducing LR growth. Under N stress, all the root-related traits are observed to increase, but at extreme N deficiency, the root growth ceases (Gruber et al. 2013). CLAVATA3 (CLV3)/ENDOSPERM SURROUNDING REGION (ESR)-related peptides (CLE) and CLAVATA1 (CLV1) leucine-rich repeat receptor-like kinase (LRR-RLK) network regulates root development under N deficiency. At low nitrate, 4 CLE genes were up-regulated (Araya et al. 2014). Only CLV1 was found to increase LR growth when mutated among the receptors of CLE. Hence, it was concluded that CLV1 mediated pathway negatively regulates LR growth under N stress (Forde 2014). Development of LR at an early stage is positively regulated by the auxin biosynthetic gene TAR2 (Tryptophan Aminotransferase Related 2) under N deprivation due to increased auxin content at LR (Ma et al. 2014). Primary root (PR) growth is almost insensitive to nitrate concentration (Jiang et al. 2017), but at high nitrate concentration, it is inhibited (Vidal et al. 2010, 2013). In afb3 mutant and miR393 overexpressed lines, the negative effect on PR growth in the presence of nitrate was not found (Vidal et al. 2014). Although NAC3 was not found to be involved in PR growth, in the nac3 mutant, the growth was still suppressed by nitrate (Vidal et al. 2013). Therefore, there are two pathways: NAC3 dependent and NAC3 independent in terms of LR and PR growth regulated by AFB3 (Forde 2014).

miRNAs associated with nitrogen stress adaptation in plants

A limited amount of N causes a reduction in photosynthetic capability. Under N deprivation, the number of thylakoids per unit of chloroplast was reduced in spinach without changing the thylakoid membrane characteristics. N being an essential component of chlorophyll and proteins, Rubisco and chlorophyll content per unit of leaf area and Rubisco per unit of chlorophyll decreases at reduced N level (Sathee et al. 2021). Degradation of RUBISCO reduces the photosynthetic rate (Hörtensteiner and Feller 2002). Although a low N supply reduces chlorophyll content, reports also showed that with increased N supply, chlorophyll a/b and carotenoid content decreases due to profuse leaf growth and shading effects of leaves (Gallé and Feller 2007; Tóth et al. 2002). At low N, plants adapt some responses to maintain yield, which include remobilization of N reserves to growing parts, retardation of growth and anthocyanin pigmentation (Scott 1999; Diaz et al. 2006; Ding et al. 2005; Kant et al. 2011; Peng et al. 2007). Recently, Das et al. (2023) reported a reprogramming of N assimilation, N remobilisation and flavonoid biosynthesis associated miRNome in wheat. Anthocyanin is a secondary metabolite pigment with diverse colours and functions. It is found in petals, fruit skins and seed coats and can attract pollinators and animals for seed dispersal (Shirley 2001). Due to the lack of amide N for the synthesis of amino acids, the excess photosynthates are directed towards synthesizing anthocyanin and non-structural carbohydrates. During continuous episodes of N deficiency, the plant C/N ratio increases due to the accumulation of sugars, which reduces photosynthesis and induces leaf senescence (Wingler et al. 2004). Anthocyanin protects photosynthetic machinery from photo-oxidative damage and helps in N remobilization from senescing leaves (Smillie and Hetherington 1999). Anthocyanin also acts as an antioxidant (Gould et al. 2002) and scavenges reactive oxygen species (ROS). The biosynthesis of anthocyanin follows the phenylpropanoid pathway, where phenylalanine is converted into cinnamic acid by phenylalanine ammonia-lyase (PAL) and helps in anthocyanin formation through the flavonoid pathway. In Arabidopsis, a transcription factor- protein complex is involved in anthocyanin biosynthesis, which includes R2R3-MYB proteins (PAP1, PAP2, MYB61, TT2), bHLH protein (GL3, EGL3, TT8), and WD-40 protein (TTG1). Plants under N‐deficit accumulate anthocyanins in different tissues by inducing the expression of PAP2 and GL3 (Feyissa et al. 2014). Among these different families of transcription factors (TF), MYB is considered to be the most important TF. Overexpression of MYB75 (PAP1) leads to over-accumulation of anthocyanin (Tohge et al. 2005). PAP1 loss of function mutant (pap1-1) survival rate was significantly lower under N deficiency due to reduced adaptability (Liang and He 2018). Anthocyanin biosynthesis genes are found to be induced by N stress (Scott 1999; Peng et al. 2007; Das et al. 2023). Anthocyanin accumulation and purple colouration phenotype are also observed under sulphur (S) and phosphorus (P) stresses (Stewart et al. 2001). NITROGEN LIMITATION ADAPTATION (NLA), a RING-type ubiquitin ligase, plays a crucial part in N stress adaptation (Zhao et al. 2011). Peng et al. (2008) reported that the nla mutant of Arabidopsis showed susceptibility to N deficiency with a lack of anthocyanin accumulation but accumulated plenty of anthocyanin under combined N and P stress, probably because there are two pathways of anthocyanin biosynthesis induced by N and P deficiencies separately and this mutation disrupts N deficiency-induced pathway only. miR156 targeting SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) transcription factor (TF) gene (Wang et al. 2012) has been reported to regulate anthocyanin accumulation. High anthocyanin concentration at stem nodes in Arabidopsis was observed due to higher expression of miR156 and down-regulation of SPL, but in growing plants, SPL level rises with down-regulation of miR156 (Wu et al. 2009). As a result, anthocyanin biosynthesis is repressed, and flavonol synthesis is promoted. TAS4 RNA regulated by miR828 regulates MYB TFs in Arabidopsis and apple (Xia et al. 2012). TasiRNA derived from TAS4 is found to target RNAs encoding MYB75 and MYB113 in Arabidopsis and MYB90 and MYB113 in potatoes regulating anthocyanin accumulation (Liu et al. 2016). MYB11, MYB12 and MYB113 are found to be targeted by miR156 (Gou et al. 2011), whereas MYB111 is targeted by miR858 (Sharma et al. 2016), which regulates anthocyanin synthesis. The transgenic overexpressor line of miR828 in Arabidopsis showed a decrease in the expression of MYB75, MYB90 and MYB113, as well as anthocyanin biosynthesis (Yang et al. 2013).

miRNAs associated with N deficiency have been reported in recent studies. N responsive miRNAs, e.g. miR167 and miR393, were found to control root system architecture (RSA) (Gifford et al. 2008; Vidal et al. 2010). Another study showed that miR169 helps to cope with N stress (Zhao et al. 2011). ARF6 and ARF8, the two targets of miR167, were induced, as miR167 was down-regulated by nitrate treatment in Arabidopsis (Gifford et al. 2008). The information on N-responsive miRNAs and their responses to N deficiency and the general effects of overexpression are listed in Table 1. N stress leads to carbon accumulation in roots resulting in a higher root-to-shoot ratio for better forage of nitrate (Paul and Driscoll 1997; Scheible 2004; Scheible et al. 1997). N deficiency enhances primary root growth and lateral root elongation except for lateral root initiation up to a certain extent (Gruber et al. 2013; Bucio et al. 2003). Under extreme N deficiency, no lateral root elongation occurs (Krouk and Kiba 2020). miR399, which regulates phosphate homeostasis (Pant et al. 2009), is found to be up-regulated in maize (Xu et al. 2011) and down-regulated in Arabidopsis (Liang et al. 2012) in root under N deficiency. Root system architechture is reported to be regulated by several phytohormone-linked pathways (Osmont et al. 2007). Root tissues develop from root apical meristem (RAM) and have different tissue layers, epidermis, cortex, endodermis and pericycle surrounding the central xylem and phloem tissues in a concentric. The interaction between auxin recptors TRANSPORT INHIBITOR RESPONSE 1 (TIR1) or Auxin signalling F-box (AFB) proteins and Aux/IAA proteins results in ubiquitination and 26S proteasome-mediated degradation of Aux/IAA (Dharmasiri et al. 2005; Maraschin et al. 2009). This releases AUXIN RESPONSE FACTORS (ARFs) which are transcription factors that regulate the activation and repression of auxin-responsive genes (Guilfoyle 2015). miR165/166 targets PHABULOSA (PHB) and PHAVOLUTA (PHV), which are homeodomain leucine zipper class-III (HD-ZIP III) transcription factor genes involved in shoot apical meristem development and vascular tissue differentiation (Zhou et al. 2007). Khan et al. (2011) reported that loss of function of miR165/166 with higher expression of PHB and PHV resulted in lethal embryo and aberrant root development, confirming the role of miR165/166 mediated repression of PHB and PHV in embryonic root development. miR160 regulates gravitropism and root development and targets ARF10, ARF16 and ARF17. Overexpression of miR160 leads to agravitropic and shorter roots with tumour-like growth due to uncontrolled cell division in RAM and failure in columella cell differentiation (Wang et al. 2005). In Arabidopsis, miR396, which targets GROWTH REGULATION FACTORS (GRFs) genes that help in cell multiplication in leaves (Rodriguez et al. 2010), is also found to regulate root growth by restricting cell multiplication at RAM. SHORTROOT (SHR), a GRAS transcription factor produced in central vascular layers of root tissue, regulates cell differentiation in roots and transports to endodermis, where it activates SCARECROW (SCR) transcription factor (Gallagher et al. 2004). In endodermis, SHR and SCR activate miR165/166, which prevents PHB expression and ensures proper xylem differentiation (Carlsbecker et al. 2010). But overexpression of miR166 leads to a disordered vascular system of the root. Hence, regulating miR165/166 and its targets is essential for root vascular differentiation.

Table 1.

List of nitrogen (N) responsive miRNAs and their responses to N deficiency and general effects of overexpression

Family	Target genes	Potential function under N deficiency	Plant Response to overexpression
miR156	Squamosa Promoter Binding Protein Like (SPL) family of transcription factors	Anthocyanin accumulation, Modification of flowering time Liang et al. (2012)	Increased production of anthocyanin Gou et al. (2011), prolonged juvenile phase, improved biomass production Xie et al. (2012)
miR160	Auxin response factors (ARF10, ARF16 and ARF17)	Root and nodule organogenesis, morphogenesis, signaling Xu et al. (2011)	Defects in root growth and nodulation Bustos-Sanmamed et al. (2013)
miR162	Dicer-like proteins	Flower development, miRNA biogenesis Liu et al. (2014)	Induction of defense- genes and accumulation of hydrogen peroxide Li et al. (2020)
miR164	NAC transcription factors	Lateral root development and senescence Xu et al. (2011)	Altered phenology and morphology Rosas Cárdenas et al. (2017)
miR166	HD-ZIP transcription factors family (REVOLUTA (REV), PHABULOSA (PHB), PHAVOLUTA (PHV), CORONA (CNA) and ATHB8)	Development and stress signaling Zhang et al. (2014)	Increase in root length and sensitivity to plant hormones Singh et al. (2017)
miR167	ARF transcription factors (ARF6 and ARF8)	Adventitious and lateral rooting Gifford et al. (2008)	suppression of auxin response and biotic stress resistance Caruana et al. (2020)
miR168	Peptide transporter, Argonaute (AGO)	miRNA biogenesis, Nitrogen uptake Nischal et al. (2012) and Vaucheret et al. (2006)	Developmental defects Vaucheret et al. (2006)
miR169	Nuclear factor YA (NFYA)	Nitrogen homeostasis, stress response Zhao et al. (2011)	Sensitivity to N deficiency, low N accumulation Zhao et al. (2011)
miR171	Scarecrow-Like (SCL) transcription factors	Root morphogenesis Liang et al. (2012)	Altered phenology and developmental defects Curaba et al. (2013)
miR172	AP2 transcription factors (TOE1 and TOE2)	Flower development, nodulation Jung et al. (2011), Yan et al. (2013)	Promotion of flowering Zhu et al. (2009)
miR319	TCP transcription factors	Jasmonate biosynthesis and thus leaf growth and senescence Schommer et al. (2008, 2014)	Altered leaf development, cold tolerance Fang et al. (2020), Yang et al. (2013) and Zhou et al. (2013)
miR393	Auxin receptors TIR1, AFB1, AFB2, and AFB3	Root morphogenesis Vidal et al. (2010)	Increase in tillering Li et al. (2016)
miR396	GRF transcription factors	Yield and N assimilation Rodriguez et al. (2010) and Zhang et al. (2020)	Improved yield, altered leaf proliferation Rodriguez et al. (2010), and Zhang et al. (2020)
miR398	CSD; COX5b-1; CCS1	Oxidative stress defence under N deficiency Sunkar et al. (2006)	–
miR399	UBC24/PHO2	Nitrate dependent Phosphate metabolism	–
miR408	Laccases; plantacyanin	Copper metabolism, lignin biosynthesis Liang et al. (2015)	–
miR826/miR5090	2‐oxoglutarate‐dependent dioxygenase ALKENYL HYDROXALKYL PRODUCING 2 (AOP2) involved in the synthesis of glucosinolates, N‐containing metabolites	Glucosinolate biosynthesis Liang et al. (2012)	–
miR827	SPX (SYG1/ Pho81/ XPR1)	Nitrogen/phosphorus homeostasis Kant et al. (2011)	Impaired phosphorus homeostasis Wang et al. (2012)

The plant root system develops lateral roots (LR) that arise from pericycle cells for better water and nutrient uptake and good anchorage to the soil. Auxin is reported to promote LR initiation by inducing pericycle cell division (Fukaki et al. 2007). miR164 is found to negatively regulate LR initiation through repression of its target NAC1 expression (Guo et al. 2005), whereas miR160 is found to positively regulate LR initiation limiting ARF16 (Wang et al. 2005). Another set of non-coding RNAs called TAS RNAs is cleaved by miRNAs and processed to dsRNAs which are further cleaved by DCL4 into small 21nt long dsRNAs called trans-acting small interfering RNAs (siRNAs). These siRNAs were reported to regulate LR growth. TAS3 RNAs are cleaved by miR390, and tasiRNAs are generated (Fahlgren et al. 2006). miR390 generates tasiARFs that repress different ARFs to promote LR growth. It was reported in Arabidopsis that miR160 positively regulates adventitious root formation through ARF17 repression, and miR167 negatively regulates adventitious root formation targeting ARF6 and ARF8. This crosstalk between miR160 and miR167 is regulated by light and transcription-related processes (Gutierrez et al. 2009). But in rice, miR167 is a positive regulator of adventitious root formation (Meng et al. 2009). Hence, these auxin-mediated miRNA pathways in phylogenetically distant species are not completely conserved.

Nitrogen stress-responsive miRNAs in wheat, Structural prediction of precursor miRNAs and identification of nitrogen stress-responsive miRNA-mRNA network in wheat

Although wheat has a relatively complex genome with a larger genome size (~ 17 Gb) compared to other crops, recent advances in sequencing technologies have led to the discovery of some conserved and novel miRNAs in wheat. Similar to the other crops, N-responsive miRNAs have also been studied in wheat (Das et al. 2023). Zhao et al. (2015) identified that seven miRNA families were differentially expressed under low N stress in wheat. Gao et al. (2016) mentioned another N-responsive miRNA (miR444a) in wheat. Expression levels of N-responsive ttu-miRNAs have been studied under chronic and transient stress in durum wheat (Zuluaga et al. 2018). In another study, Zuluaga et al. (2017) focused on the the-miRNAs expressed only at the grain-filling stage in durum wheat. Similarly, several investigations have successfully identified a number of N stress-responsive miRNAs along with their putative target genes, responses under N deficiency, tissue, and developmental stage-specific expressions in bread wheat (Triticum aestivum L.), durum wheat (Triticum turgidum ssp. durum) and spherococcum wheat (T. spheococcum), respectively (Table 2).

Table 2.

List of nitrogen (N) stress responsive miRNAs in wheat. Responses of miRNAs are designated as U for up-regulated and D for down-regulated expressions

miRNA family	Validated/putative target genes	Potential function under N deficiency	Response	Developmental stage	Tissue	References	Treatments
tae-miR156	SPL, TGA1, glycosyl/glycerophosphate transferase, CYPs, Cob(I)alamin adenolsyl transferase	Shoot development, phase change, seed germination	U	Seedling	Roots	Zhao et al. (2015)	Transient stress
ttu-miR156a, b, j	SPL, TGA1, glycosyl/glycerophosphate transferase, CYPs, Cob(I)alamin adenolsyl transferase	Shoot development, phase change, seed germination	U	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
tae-miR159a, b	MYB, TCP	Plant morphogenesis	D	Seedling	Roots	Sinha et al. (2015)	Both
tae-miR160	Auxin Response Factor (ARF22)	Root development, signal transduction, phase change	D	Seedling	Roots	Sinha et al. (2015)	Both
ttu-miR160	Auxin Response Factor (ARF22)	Root development, signal transduction, phase change	U	Seedling	Leaves	(Zuluaga et al. (2018)	Chronic stress
ttu-miR160	Auxin Response Factor (ARF22)	Root development, signal transduction, phase change	U	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
tae-miR164	NAC7	Root development	B	Seedling	Roots	Sinha et al. (2015)	Both
ttu-miR164d	NAC7	Root development	U	Seedling	Roots	Zuluaga et al. (2018)	Chronic stress
ttu-miR164d	NAC7	Root development	D	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-miR164d	NAC7	Root development	U	Grain filling	Roots	(Zuluaga et al. (2017)	Chronic stress
ttu-miR166k	HD-ZIP TF	Shoot development	D	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-miR166q	HD-ZIP TF	Shoot development	U	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
ttu-miR167h	Auxin Response Factor (ARF8)	Root development, signal transduction	U	Seedling	Leaves, roots	Zuluaga et al. (2018)	Chronic stress
ttu-miR167h	Auxin Response Factor (ARF8)	Root development, signal transduction	D	Grain filling	Roots	Zuluaga et al. (2017)	Chronic stress
ttu-miR167h	Auxin Response Factor (ARF8)	Root development, signal transduction	U	Grain filling	Leaves, stems	Zuluaga et al. (2017)	Chronic stress
ttu-miR167i	Auxin Response Factor (ARF8)	Root development, signal transduction	U	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
ttu-miR168b, c	Argonaute (AGO1)	Signal transduction	U	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
tae-miR169a, b, d, e, f, h, m, n	CCAAT-box TF WHAP6, NFYAs	Nitrogen homeostasis, stress response	D	Seedling	Roots, shoots	Qu et al. (2015)	Chronic stress
ttu-miR169b	CCAAT-box TF WHAP6, NFYAs	Nitrogen homeostasis, stress response	U	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
ttu-miR169c	CCAAT-box TF WHAP6, NFYAs	Nitrogen homeostasis, stress response	D	Grain filling	Roots	Zuluaga et al. (2017)	Chronic stress
ttu-miR169c	CCAAT-box TF WHAP6, NFYAs	Nitrogen homeostasis, stress response	D	Grain filling	Leaves, stems	Zuluaga et al. (2017)	Chronic stress
ttu-miR169c	CCAAT-box TF WHAP6, NFYAs	Nitrogen homeostasis, stress response	D	Grain filling	Flag leaf	Zuluaga et al. (2017)	Chronic stress
ttu-miR169c	CCAAT-box TF WHAP6, NFYAs	Nitrogen homeostasis, stress response	D	Grain filling	Spikes	Zuluaga et al. (2017)	Chronic stress
ttu-miR319b	MYB3, TCP	Shoot development	U	Grain filling	Leaves, stems	Zuluaga et al. (2017)	Chronic stress
ttu-miR319b	MYB3, TCP	Shoot development	B	Grain filling	Flag leaf	Zuluaga et al. (2017)	Chronic stress
ttu-miR319d	MYB3, TCP	Shoot development	U	Seedling	Roots	Zuluaga et al. (2018)	Chronic stress
ttu-miR393c	Auxin signaling F-Box 2 (AFB2)	Root development, defense response	D	Grain filling	Roots	Zuluaga et al. (2017)	Chronic stress
ttu-miR393c	Auxin signaling F-Box 2 (AFB2)	Root development, defense response	D	Grain filling	Leaves, stems	Zuluaga et al. (2017)	Chronic stress
ttu-miR396b, g	GRF TF	Leaf development	U	Seedling	Roots	Zuluaga et al. (2018)	Chronic stress
tae-miR399	E2 ubiquitin conjugase PHOSPHATE 2 (PHO2)	Phosphate metabolism	D	Seedling	Roots	Zhao et al. (2015)	Transient stress
ttu-miR399b	E2 ubiquitin conjugase PHOSPHATE 2 (PHO2)	Phosphate metabolism	D	Seedling	Leaves, roots	Zuluaga et al. (2018)	Chronic stress
ttu-miR399b	E2 ubiquitin conjugase PHOSPHATE 2 (PHO2)	Phosphate metabolism	D	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-miR399b	E2 ubiquitin conjugase PHOSPHATE 2 (PHO2)	Phosphate metabolism	D	Grain filling	Roots	Zuluaga et al. (2017)	Chronic stress
ttu-miR399b	E2 ubiquitin conjugase PHOSPHATE 2 (PHO2)	Phosphate metabolism	U	Grain filling	Leaves, stems	Zuluaga et al. (2017)	Chronic stress
ttu-miR399b	E2 ubiquitin conjugase PHOSPHATE 2 (PHO2)	Phosphate metabolism	U	Grain filling	Spikes	Zuluaga et al. (2017)	Chronic stress
tae-miR444	MIKC-type MADS-box TF WM32B(MMW), GRAS family TF, maturase K	Signal transduction, defense response	U	Seedling	Roots	Zhao et al. (2015)	Transient stress
tae-miR444a	MIKC-type MADS-box TF WM32B(MMW), GRAS family TF, maturase K	Signal transduction, defense response	U	Seedling	Leaves, roots	Gao et al. (2016)	Both
ttu-miR444a	MIKC-type MADS-box TF WM32B(MMW), GRAS family TF, maturase K	Signal transduction, defense response	U	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-miR444d	MIKC-type MADS-box TF WM32B(MMW), GRAS family TF, maturase K	Signal transduction, defense response	U	Grain filling	Roots	Zuluaga et al. (2017)	Chronic stress
ttu-miR827a	E3 ubiquitin ligase Nitrogen Limitation Adaptation (NLA), SPX, Caseinolytic protease (CLP)	Nitrogen/phosphorus homeostasis	D	Seedling	Leaves, roots	Zuluaga et al. (2018)	Chronic stress
ttu-miR827a	E3 ubiquitin ligase Nitrogen Limitation Adaptation (NLA), SPX, Caseinolytic protease (CLP)	Nitrogen/phosphorus homeostasis	B	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-miR827a	E3 ubiquitin ligase Nitrogen Limitation Adaptation (NLA), SPX, Caseinolytic protease (CLP)	Nitrogen/phosphorus homeostasis	D	Grain filling	Roots	Zuluaga et al. (2017)	Chronic stress
ttu-miR827a	E3 ubiquitin ligase Nitrogen Limitation Adaptation (NLA), SPX, Caseinolytic protease (CLP)	Nitrogen/phosphorus homeostasis	U	Grain filling	Leaves, stems	Zuluaga et al. (2017)	Chronic stress
tae-miR1117	Drought related aquaporin	Stress response	D	Seedling	Roots	Sinha et al. (2015)	Both
tae-miR1118	HVA22, TaCaM2, glutathione S-transferase 2, RUBISCO large subunit, P347, sugar transporters	Stress response	U	Seedling	Roots	Zhao et al. (2015)	Transient stress
tae-miR1120	–	–	D	Seedling	Roots	Sinha et al. (2015)	Both
tae-miR1129	Molybdenum cofactor sulfurase, major facilitator family transporter	Stress response	U	Seedling	Roots	Zhao et al. (2015)	Transient stress
tae-miR1133	Calmodulin-like, SET domain histone methyltransferases, early nodulin, NADH-ubiquinone/plastoquinone oxidoreductase chain 6 precursor	Stress response	D	Seedling	Roots	Zhao et al. (2015)	Transient stress
tae-miR1136	Endo-1,4-beta-glucanase	Stress response	U	Seedling	Roots	Zhao et al. (2015)	Transient stress
tae-miR2275	TaBDP, TaPRP, TaWRK, TaSPK, TaPP, TaAAT, TaNTA, TaIM	Nitrogen homeostasis	U	Seedling	Roots	Qiao et al. (2018)	Transient stress
ttu-miR9778	–	–	U	Seedling	Roots	Zuluaga et al. (2018)	Chronic stress
ttu-novel-13	High-affinity nitrate transporter-activating protein 2.1 (NAR2.1)	–	D	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
ttu-novel-13	High-affinity nitrate transporter-activating protein 2.1 (NAR2.1)	–	U	Grain filling	Flag leaf	Zuluaga et al. (2017)	Chronic stress
ttu-novel-61	CCAAT-box TF WHAP6	–	D	Seedling	Leaves, roots	Zuluaga et al. (2018)	Chronic stress
ttu-novel-61	CCAAT-box TF WHAP6	–	D	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-novel-61	CCAAT-box TF WHAP6	–	D	Grain filling	Leaves, roots, stems, flag leaf, spikes	Zuluaga et al. (2017)	Chronic stress
ttu-novel-72	–	–	D	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-novel-74	Glutathione transferase F5	–	U	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-novel-85	Auxin Response Factor (ARF22)	–	U	Seedling	Roots	Zuluaga et al. (2018)	Transient stress
ttu-novel-87	NAC7	–	U	Seedling	Roots	Zuluaga et al. (2018)	Chronic stress
ttu-novel-103	–	–	U	Grain filling	Flag leaf	Zuluaga et al. (2017)	Chronic stress
ttu-novel-106	MYB-A	–	U	Seedling	Leaves	Zuluaga et al. (2018)	Chronic stress
ttu-novel-106	MYB-A	–	D	Seedling	Roots	Zuluaga et al. (2018)	Transient stress

Based on literature (Gao et al. 2016; Qiao et al. 2018; Qu et al. 2015; Sinha et al. 2015; Zuluaga et al. 2017, 2018), a number of tae-miRNA and tte-miRNA members have been enlisted in Table 2 showing their differential tissue-specific and developmental stage-specific expressions under chronic and transient N stresses or both. We have shown precursor miRNA (pre-miRNA) structures of 5 miRNAs (tae-miR156, tae-miR160, tae-miR169, tae-miR399 and the-miR160) from the list (Table 2). To deduce the two-dimensional (2D) secondary structures (Fig. 1), pre-miRNA sequences were retrieved from the updated wheat miRNA library available on miRBase 22.0 (http://www.mirbase.org/) and the obtained sequences were used as a query in UNAFold server (http://www.unafold.org/). Based on free energy methods and computational programming, the secondary structures are predicted by this server (Markham and Zuker 2008).

Fig. 1.

2D secondary structure prediction of nitrogen stress responsive precursor miRNAs using UNAFold. a tae-miR156, b tae-miR160, c tae-miR169, d tae-miR399, e ttu-miR160

To deduce the three-dimensional (3D) structures of pre-miRNAs (tae-miR156, tae-miR160, tae-miR169, tae-miR399 and ttu-miR160), the sequences obtained from miRBase 22.0 (http://www.mirbase.org/) were used as query in TamiRPred server (http://webtom.cabgrid.res.in/tamirpred/) and dot-bracket notations of pre-miRNA secondary structures were obtained which were further used as query in RNAComposer (http://rnacomposer.cs.put.poznan.pl/) to get the structure files (Antczak et al. 2016; Popenda et al. 2012). Finally, the 3D structures were retrieved using UCSF Chimera software (https://www.rbvi.ucsf.edu/chimera/) (Pettersen et al. 2004) (Fig. 2).

Fig. 2.

3D secondary structure prediction of nitrogen stress responsive precursor miRNAs using RNAComposer. a tae-miR156, b tae-miR160, c tae-miR169, d tae-miR399, e ttu-miR160

An interactive network of miRNAs, target genes and gene functions based on Table 2 has been devised using Cytoscape (Fig. 3). The candidate genes related to N stress response, N uptake, assimilation, remobilization and NUE were identified by Islam et al. (2021) and Zuluaga and Sonnante (2019). The identified candidates were searched against Triticum species and sub-species in the Ensembl Plants database (https://plants.ensembl.org/), and the whole gene, cDNA, exon, and intron sequences were retrieved for further analysis. Full-length genomic sequences of genes were used as a query against the updated wheat miRNA library available on miRBase 22.0 (http://www.mirbase.org/). The genomic sequences were pasted in FASTA format in the search box to retrieve the miRNAs of wheat based on sequence homology. The potential miRNAs targeting the candidate genes were predicted by aligning the miRNAs to target mRNA sequences by homology search-based psRNATarget (http://plantgrn.noble.org/psRNATarget/) server (Table 3). Based on in silico target prediction, it was found that the-miR160 targets ARFs, whereas nitrate reductase is targeted by the-miR1120c-5p, tae-miR1137b-5p, tae-miR1128 and tae-miR1130a. tae-miR9666b-3p and tae-miR9670-3p targets nitrite reductase, chalcone synthase bytae-miR1120b-3p and glutamine synthetase by tae-miR1137b-5p. tae-miR1120c-5p, tae-miR1130a and tae-miR9782 were having probability to target nitrate transporters (NRT1/ NPF). miRNAs targeting wheat N signalling genes were also identified. Increase in anthocyanin production under low N stress in wheat is well documented (Das et al. 2023), Low N induced changes in crop phenology and accelerated flowering (Padhan et al. 2023) is seen in rice, which could be due to modulation of associated miRNas. Low N content also resulted in increased formation of hydrogen peroxide and accumulation of thiobarbituric acid reactive substances (TBARS) in wheat (Jain et al. 2011; Padhan et al. 2020). Recently, we (Das et al. 2023) have reported a reprogramming of N assimilation, N remobilisation, and flavonoid biosynthesis associated miRNome in wheat.

Fig. 3.

Visualization of nitrogen stress responsive miRNA-miRNA and associated gene functions network using Cytoscape. The miRNAs, target genes and potential functions under nitrogen stress are represented in rounded rectangle, circle and hexagon shapes, respectively. The interaction is shown as nodes and edges to depict expressions of miRNAs in leaves (green), roots (orange), stem (blue), spikes (red) and flag leaf (pink) (Color figure online)

Table 3.

In silico analysis of miRNAs and the target genes associated with for nitrogen metabolism and nutrient use efficiency in wheat

Target name	miRNA Acc	Target Acc	Expectation	miRNA length	Target start	Target end	miRNA aligned_fragment	Alignment	Target
Nitrate reductase	tae-miR1120c-5p	TraesCS6A02G017500.1	1	21	1531	1551	UAAUAUAAGAACGUUUUUGAC	:::::::::::::::::::	DNA
	tae-miR1120c-5p	TraesCS6A02G017500.1	1	21	194	214	UAAUAUAAGAACGUUUUUGAC	:::::::::::::::::::	intron
	tae-miR1120c-5p	TraesCS6A02G017500.2	1	21	194	214	UAAUAUAAGAACGUUUUUGAC	:::::::::::::::::::	intron
	tae-miR1120c-5p	TraesCS6A02G017500.3	1	21	1531	1551	UAAUAUAAGAACGUUUUUGAC	:::::::::::::::::::	DNA
	tae-miR1137b-5p	TraesCS6B02G024900.1	0.5	21	3283	3303	UCCGUUCCAGAAUAGAUGACC	::::::::::.:::::::::	cDNA
	tae-miR1137b-5p	TraesCS6B02G024900.2	0.5	21	6007	6027	UCCGUUCCAGAAUAGAUGACC	::::::::::.:::::::::	DNA
	tae-miR1137b-5p	TraesCS6B02G024900.1	0.5	21	1904	1924	UCCGUUCCAGAAUAGAUGACC	::::::::::.:::::::::	exon
	tae-miR1128	TraesCS6B02G024900.1	1	21	822	842	UACUACUCCCUCCGUCCGAAA	:::::::::::::::::::	intron
	tae-miR1128	TraesCS6B02G024900.2	1	21	2201	2221	UACUACUCCCUCCGUCCGAAA	:::::::::::::::::::	DNA
	tae-miR1130a	TraesCS6B02G024900.3	1.5	23	2191	2213	CCUCCGUCUCGUAAUGUAAGACG	:::::.::::.:.::::::::	DNA
	tae-miR1130a	TraesCS6B02G024900.1	1.5	23	812	834	CCUCCGUCUCGUAAUGUAAGACG	:::::.::::.:.::::::::	intron
Glutamine synthetase	tae-miR1137b-5p	TraesCS2D02G500600.1	0.5	21	213	233	UCCGUUCCAGAAUAGAUGACC	::::::::::.:::::::::	intron
	tae-miR1137b-5p	TraesCS2D02G500600.2	0.5	21	3911	3931	UCCGUUCCAGAAUAGAUGACC	::::::::::.:::::::::	DNA
Nitrite reductase	tae-miR9666b-3p	TraesCS4B02G373400.1	2	22	2462	2483	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	DNA
	tae-miR9666b-3p	TraesCS4B02G373400.1	2	22	1422	1443	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	cDNA
	tae-miR9666b-3p	TraesCS4B02G373400.1	2	22	405	426	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	exon
	tae-miR9670-3p	TraesCS4D02G045800.1	2	21	1022	1042	AGGUGGAAUACUUGAAGAAGA	:::::..:::::::::::	cDNA
	tae-miR9670-3p	TraesCS4D02G045800.1	2	21	319	339	AGGUGGAAUACUUGAAGAAGA	:::::..:::::::::::	exon
	tae-miR9670-3p	TraesCS4D02G045800.2	2	21	2166	2186	AGGUGGAAUACUUGAAGAAGA	:::::..:::::::::::	DNA
	tae-miR9666b-3p	TraesCS4D02G045800.3	2	22	2412	2433	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	DNA
	tae-miR9666b-3p	TraesCS4D02G363900.1	2	22	1293	1314	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	cDNA
	tae-miR9666b-3p	TraesCS4D02G363900.1	2	22	405	426	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	exon
	tae-miR9666b-3p	TraesCS4D02G363900.2	2	22	2382	2403	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	DNA
	tae-miR9666b-3p	TraesCS4D02G363900.2	2	22	1491	1512	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	cDNA
	tae-miR9666b-3p	TraesCS4D02G363900.2	2	22	405	426	CGGUUGGGCUGUAUGAUGGCGA	:..::::::.::::::::.:	Exon
	tae-miR9660-5p	TraesCS1A02G091300.1	4.5	20	1632	1651	UUGCGAGCAACGGAUGAAUC	:::::::::::::::	cDNA
	tae-miR5384-3p	TraesCS1A02G091300.1	5	21	1681	1701	UGAGCGCGCCGCCGUCGAAUG	:::::.:::::.:::::	cDNA
AFB3	tae-miR9664-3p	TraesCS1A02G091300.1	5	21	648	668	UUGCAGUCCUCGAUGUCGUAG	::::::.:::::.::	cDNA
	tae-miR9674b-5p	TraesCS1A02G091300.1	5	21	1895	1914	AUAGCAUCAUCCAUCCUACCC	:::::::::::::::.:	cDNA
Chalcone synthase	tae-miR1120b-3p	TraesCS2B02G038700.1	2	21	75	95	UUCUUAUAUUGUGGGACAGAG	:::::..::::::::::::	intron
	tae-miR1120b-3p	TraesCS2B02G038700.2	2	21	355	375	UUCUUAUAUUGUGGGACAGAG	:::::..::::::::::::	DNA
Auxin response factors	tae-miR160	TraesCS2A02G567300.1	0.5	21	4271	4291	UGCCUGGCUCCCUGUAUGCCA	::::::.::::::::::::::	DNA
	tae-miR160	TraesCS2A02G567300.1	0.5	21	1296	1316	UGCCUGGCUCCCUGUAUGCCA	::::::.::::::::::::::	cDNA
	tae-miR160	TraesCS2A02G567300.1	0.5	21	216	236	UGCCUGGCUCCCUGUAUGCCA	::::::.::::::::::::::	exon
	tae-miR160	TraesCS2D02G577800.1	0.5	21	1255	1275	UGCCUGGCUCCCUGUAUGCCA	::::::.::::::::::::::	cDNA
	tae-miR160	TraesCS2D02G577800.1	0.5	21	216	236	UGCCUGGCUCCCUGUAUGCCA	::::::.::::::::::::::	exon
	tae-miR160	TraesCS2D02G577800.2	0.5	21	4345	4365	UGCCUGGCUCCCUGUAUGCCA	::::::.::::::::::::::	DNA
	tae-miR160	TraesCS7D02G436800.1	0	21	2263	2283	UGCCUGGCUCCCUGUAUGCCA	::::::::::::::::::::	DNA
	tae-miR160	TraesCS7D02G436800.1	0	21	246	266	UGCCUGGCUCCCUGUAUGCCA	::::::::::::::::::::	Exon
	tae-miR160	TraesCS7D02G436800.1	0	21	1910	1930	UGCCUGGCUCCCUGUAUGCCA	::::::::::::::::::::	cDNA
Nitrate transporter	tae-miR1120c-5p	TraesCS7B02G328700.1	0.5	21	181	201	UAAUAUAAGAACGUUUUUGAC	::::::::::::.::::::::	intron
	tae-miR1120c-5p	TraesCS7B02G328700.2	0.5	21	1512	1532	UAAUAUAAGAACGUUUUUGAC	::::::::::::.::::::::	DNA
	tae-miR1130a	TraesCS3A02G418700.1	1.5	23	506	528	CCUCCGUCUCGUAAUGUAAGACG	:::::.::::.:.::::::::	DNA
	tae-miR1130a	TraesCS3A02G418700.1	1.5	23	379	401	CCUCCGUCUCGUAAUGUAAGACG	:::::.::::.:.::::::::	intron
	tae-miR9782	TraesCS7A02G301700.1	0	24	2687	2710	GUAUUAGGUUGGUCAAAUUGACGA	:.:::::::::::::::::::::	intron
	tae-miR9782	TraesCS7A02G301700.2	0	24	4349	4372	GUAUUAGGUUGGUCAAAUUGACGA	:.:::::::::::::::::::::	DNA
SPL9	tae-miR156	TraesCS2A02G232400.1	1	21	786	806	UGACAGAAGAGAGUGAGCACA	::::::::::::::::::	cDNA
	tae-miR9780	TraesCS2A02G232400.1	5	21	460	480	CGGGUCGGCGCUGCACGCGGC	::::.:::::::::	cDNA
PAP1	tae-miR9658-3p	TraesCS1A02G021500.1	4	21	901	921	AUCGUUCUGGGUGAAUAGGCC	::::.:..:::::::.:::	cDNA
NLP7	tae-miR444a	TraesCS3D02G166900.2	5	21	1003	1023	UUGCUGCCUCAAGCUUGCUGC	:::.::::::::::.::	cDNA
TCP20	tae-miR444b	TraesCS3D02G166900.2	5	21	1003	1023	UUGCUGCCUCAAGCUUGCUGC	:::.::::::::::.::	cDNA
	tae-miR9666a-3p	TraesCS2A02G376000.1	4	22	116	137	CGGUAGGGCUGUAUGAUGGCGA	:::::::::::.::::::	cDNA
	tae-miR397-5p	TraesCS2A02G376000.1	5	21	222	241	UCACCGGCGCUGCACACAAUG	:.::::::.:.:::::::	cDNA
NLA	tae-miR9652-5p	TraesCS2A02G112800.1	5	22	945	966	CCUGUUUGUCAUUAAGUUUCUU	::.::.:::::.::::	cDNA
	tae-miR9776	TraesCS2A02G112800.1	5	21	1270	1290	UUGGACGAGGAUGUGCAACUG	:::::::.:.:::::…	cDNA
	tae-miR9780	TraesCS2A02G112800.1	5	21	113	133	CGGGUCGGCGCUGCACGCGGC	:::.:::::::::.:::	cDNA
ALBD37	tae-miR156	NM_126142.5	5	21	957	977	UGACAGAAGAGAGUGAGCACA	::.::::.:.::.::::	cDNA
	tae-miR9657b-5p	NM_126142.5	5	21	1607	1627	UUCGUCGGAGAAGCAUGUUGC	::::::::::::::	cDNA

Most miRNAs in plant cells cleave their target mature mRNAs in the cytoplasm. A recent study in rice, however, revealed that some of the 24-nt miRNAs linked to AGO4 complexes may be able to mediate DNA methylation in the rice nucleus (Wu et al. 2010). This suggests that a unique method of gene regulation may include certain AGO1-associated miRNAs cleaving nuclear-localized, intron-containing pre-mRNAs (Meng et al. 2013). MiRNAs (like tae-miR1120c-5p) that target intron may be involved in the regulation of miRNAs and long noncoding RNAs that are found there. It has been reported that some miRNAs and long noncoding RNAs are transcribed from the intron via sharing of the promoters with their host genes. It is still unclear how miRNAs and genomic DNA work together to control gene expression (Xun et al. 2019).

CRISPR/Cas editing of MIR genes and miRNA targets for crop trait improvement and NUE

Gene editing tools like CRISPR/Cas9 and other editing tools are important resources for gene knockout. The precise editing of repressor binding sites, sequences responsible for posttranscriptional regulation, editing of upstream ORFs (uORFS) and, most importantly, editing of miRNA target sites are promising strategies for crop improvement (Ferreira and Reis 2023; Sathee et al. 2022). Targeted editing of miRNA binding sites of target genes offers the advantage of non-specific derepression of unintended targets. Genome editing mediated knocking out of miRNAs (Deng et al. 2022) enhances target transcript abundance and associated phenotypic effects. As this strategy will de-repress all the targets of the knocked-out miRNA, the pleiotropic phenotypes are quite probable. In rice, another strategy was used by (Lin et al. 2021), editing of miR396 binding site of GROWTH REGULATING FACTOR 4 (OsGRF4) and OsGRF8 could enhance enhanced transcript abundance. In another attempt, the miR156 binding site at the 3ʹ-UTR of TaSPL13 in wheat was edited successfully, improving the gene expression (Gupta et al. 2023).

Conclusions

Nitrogen (N) is one of the major essential elements required for plant growth and development. Besides being a nutrient, N also acts as a signal regulating plant growth and metabolism. The green revolution and its effect maintained a balance between the overall supply and demand of foods globally. But during the last 2 decades, the increment in yield of crops has not shown considerable results to meet up food demand required by 2050. Hence improvement in nutrient uptake and assimilation capacity of plants remains in focus to date. However, with the advancement in genomics and transcriptomics, researchers have discovered regulatory components and their underlying pathways related to NUE and low N response in different plants. NUE being a complex trait, a simple transgenic approach cannot lead to better genotypes with desirable NUE. A comprehensive study of the gene pool across different species should be conducted. Major QTLs related to NUE are yet to be discovered to facilitate successful marker-assisted breeding. N metabolism-associated genes such as GS, GOGAT, NR, and NIR; transporter genes NRTs; N signalling genes such as NLA, PAP1, TCP, and NLP; auxin signalling-associated genes such as AFB, ARFs; anthocyanin biosynthetic genes such as CS-in wheat can be contributing factors for NUE QTL identification. We have identified and discussed miRNAs targeting this set of genes. The modulation of the expression of miRNAs resulting in the regulation of their target genes involved in plant adaptive responses to low N has already been studied. For example, the overexpression of miR169a results in the downregulation of nitrate transporters, NPF6.3 and NRT2.1 by down-regulating NFYA transcription factors, and plants accumulate less N. Similarly, another N-regulated miRNA, miR167 targets Auxin Response Factors ARF6 and ARF8 regulates lateral root growth in response to N. miR164 also regulates root growth by cleaving NAC1 transcripts. The identification of several N-responsive miRNAs has opened a parallel avenue of research in deciphering their regulatory roles, resulting in the potential to find target genes which were previously not known for their involvement in N response and NUE. The information on N-regulated miRNAs and the differentially expressed target transcripts are important resources for genetic improvement of NUE by genome editing.

Author contributions

SD and Ls wrote the manuscript. SD did the bioinformatics analysis. LS conceived the idea.

Data availability

All the data are included in the manuscript.

Code availability

Not applicable.

Declarations

Conflict of interest

The author(s) declare no competing interests.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Both authors have read and give consent for publication.