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Systematic characterization of Gossypium GLN family genes reveals a potential function of GhGLN1.1a regulates nitrogen use efficiency in cotton


The enzyme glutamine synthetase (GLN) is mainly responsible for the assimilation and reassimilation of nitrogen (N) in higher plants. Although the GLN gene has been identified in various plants, there is little information about the GLN family in cotton (Gossypium spp.). To elucidate the roles of GLN genes in cotton, we systematically investigated and characterized the GLN gene family across four cotton species (G. raimondii, G. arboreum, G. hirsutum, and G. barbadense). Our analysis encompassed analysis of members, gene structure, cis-element, intragenomic duplication, and exploration of collinear relationships. Gene duplication analysis indicated that segmental duplication was the primary driving force for the expansion of the GhGLN gene family. Transcriptomic and quantitative real-time reverse-transcription PCR (qRT-PCR) analyses indicated that the GhGLN1.1a gene is responsive to N induction treatment and several abiotic stresses. The results of virus-induced gene silencing revealed that the accumulation and N use efficiency (NUE) of cotton were affected by the inactivation of GhGLN1.1a. This study comprehensively analyzed the GhGLN genes in Gossypium spp., and provides a new perspective on the functional roles of GhGLN1.1a in regulating NUE in cotton.

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Nitrogen (N) plays a crucial role in plant development and growth, serving as a vital component of nucleic acids, proteins, chlorophyll, and other essential compounds. N levels also influence photosynthesis, carbon assimilation, and the regulation of endogenous hormones. Nitrate (NO3) and ammonium (NH4+) represent significant forms of inorganic N sourced from the environment, yet they cannot be directly utilized as substrates for protein production and the synthesis of various secondary metabolites [1]. Following absorption by plant roots from the soil, NH4+ or NO3 enters the cytoplasm, where it undergoes conversion into the organic N compound glutamine. This transformation occurs through the sequential action of the enzymes glutamine synthetase (GS) and glutamate synthase (GOGAT), collectively known as the GS/GOGAT cycle [2,3,4]. Therefore, GS is the major enzyme that assimilates N in higher plants.

GS in higher plants belongs to GSII, which can be divided into cytoplasmic GS (GLN1) and plasmid GS (GLN2) related to their subcellular localization [5]. GLN1 is primarily distributed in plant roots and mainly participates in the transport of sources of stored N during seed germination and completing the transfer and reuse of N during the senescence of leaves [6]. GLN2 is primarily distributed in the leaves and mainly assimilates the ammonia that is released by photorespiration and NO3 reduction [7].

Since the cloning and sequencing of the structural gene of the bacterial GLN from the cyanobacterium Anabaena in 1983, the cDNA and genomic DNA of GLN have been cloned in various plants, including barley [8], maize [9], rice [10] and pea [11]. Sakakibara et al. isolated 5 cDNA clones of GLN from the maize cDNA library [12]. Sakamoto et al. also isolated and sequenced three cDNA clones of GLN from a rice cDNA library [9]. In A. thaliana, six GLN genes were clearly expressed in specific tissue; for example, Gln1:1 is highly expressed in epidermal root cells and may play a role in sensing exogenous N and functioning to serve in the primary assimilation of NH4+ [1]. Gln1:2 is highly expressed in the leaves, and only GLN1 is expressed in mesophyll cells. Gln1:2 encodes an enzyme with a low affinity for NH4+ that is essential for its detoxification [13, 14]. Furthermore, the Gln1:3 genes are highly expressed in the roots and stems and involved in the formation of roots [15]. The GLN2 group exhibits the highest expression levels in green tissue and primarily serves in the re-assimilation of photorespiratory NH4+ [5, 16]. In maize, GLN1 is encoded by five nuclear genes. Among them, GLN1-1 exhibits the highest expression levels, particularly in the roots, whereas GLN1-2 is predominantly expressed in the stems. GLN1-3 and GLN1-4 show significant expression in the leaves. Specifically, GLN1-3 influences panicle number, while GLN1-4 governs grain weight regulation. Nevertheless, GLN1-5 was moderately expressed across all the tissues and organs [17]. In barley, GLN1 is encoded by three nuclear genes, and HvGS1-1 is highly expressed in vascular tissues of different organs. The HvGs1-2 is highly expressed in the epidermal cells of leaves, while HvGS1-3 is highly expressed in the ears of wheat [18].

GLN has also reported to be involved in the responses to several types of plant stress [19, 20]. Many different plants have been shown to regulate the expression and activity of their GLN isoforms in response to stressors, such as higher levels of N [21], drought [22, 23], cold [24, 25], salinity [20] and metal toxicity [26, 27]. Many studies have explored the GLN enzyme, and some hypothesized that it improves tolerance to stress. For example, a study that compared the levels of expression and activities of different GLN genes in rice under drought stress showed that a significantly maintained level of OsGS2 and the over-expression of OsGS1:1 might be contributing factors to the traits for drought resistance in the drought-tolerant rice cultivar Khitish [28]. Additionally, studies that compared gene expression examined various genotypes of durum wheat under salt and drought stress revealed that the most resilient genotype had the highest activity of GLN and increased levels of expression of GLN1 and GLN2 under stress conditions compared with the control plants [23]. Nagy et al. found that compared with the sensitive cultivars, the drought-tolerant wheat cultivars had increased GLN activity in the flag leaves [29]. Lothier observed that AtGLN1.2 was significantly expressed in the root and leaf tissues and the mesophyll cells of aging leaf tissues of A. thaliana under high N conditions [30].

Cotton (Gossypium spp.) is a significant economic crop that provides 35% of the natural fiber used throughout the world. Cotton requires higher levels of N for proper growth and development, and a lack of N in the soil may reduce the growth, yield, and high-quality fiber production of cotton. Therefore, it is critical to comprehend the molecular mechanisms of N use in cotton. The role of GLN family genes has been defined in various plants, however, little is known about the function of the GLN gene family in cotton. We examined the entire GLN gene family of four species, including two diploid species (G. raimondii and G. arboreum), and two tetraploid species (G. hirsutum and G. barbadense) to clarify the functions of cotton GLN genes. This study thoroughly investigated the phylogenetic distribution, chromosomal position, gene structure, preserved motifs, duplication pattern, and selective stress stimuli of the cotton GLN genes. In addition, the profiles of expression of the GhGLN genes were evaluated using the data from quantitative real-time reverse-transcription PCR (qRT-PCR). Virus-induced gene silencing (VIGS) was used to evaluate how the genes impacted the accumulation and N use efficiency (NUE) in cotton. The findings of this study provide a basis for the functional characterization of GhGLNs.

Materials and methods

Identifying identification of the GLN Genes

The genomic sequences of the four cotton species [G. arboreum (A2; CRI assembly), G. raimondii (D5; JGI assembly), G. barbadense (AD2; sea-island cotton; HAU assembly), and G. hirsutum (AD1; upland cotton; CRI assembly)] obtained from the CottonGen database ( were used to identify the GLN protein family members based on their homology with the sixGLN proteins from the A. thaliana TAIR database ( We used the GLN domain (PLN02284) as a multiple BLAST query against the cotton database to locatecandidate GLN sequences in the genome of the four cotton species using HMMERv 0.3.1. We checked the putative GLN members for the presence of fully or partially conserved motifs in more detail using the SMART and CDD databases. The genomic DNA, CDS, protein, and cDNA sequences of the GLNs were assembled using the Cotton Gen ( and Cotton FGD databases ( The search tool of the Ensembl Plants database was used to evaluate the size of the genes, the length of the proteins, and the number of introns ( Additionally, the molecular weight (MW) and isoelectric point (pI) values of the proteins were obtained using the ProtParam program ( TBtools was used to establish the structure of the GLN family genes based on their coding and genomic sequences [31].

Data retrieval and sequence analysis

The genomic fasta files and annotated gff3 files of G. arboreum, G. hirsutum, G. barbadense and G. raimondii were downloaded from the CottonFGD. The genomic sequences of A. thaliana were obtained from the TAIR 10 database ( MEGA 10 was used for the phylogenetic analysis of the GLN gene family in the four cotton species and A. thaliana. The neighbor-joining (NJ) method was used to create a phylogenetic tree at 1000 bootstrap iterations. The exon/intron structure information of the GLN gene family of cotton was obtained from CottonFGD, and the gene structures were visualized graphically using TBtools. The default parameters of the MEME tool were used to identify the conserved motifs of the protein sequences of cotton that contained GLN. Annotated gff3 files were used to determine where the GLN genes that were identified were located on the chromosomes. The putative regulatory elements were found in the 2000 bp 5'-upstream regions of the GLN genes using the default parameters of TBtools. TBtools was also used to extract information and conduct a preliminary regulatory-element analysis. ClustalX 1.83 was used to align the predicted protein sequences.

Evolutionary analysis of the GLN genes

The homologous GLN genes of the four cotton species were identified by contrasting their coding patterns. TBtools was used to retrieve the collinearity pairs from the GLN family and generate a collinearity map of the GLNs. Similarly, synonymous and nonsynonymous substitution rates (Ks and Ka, respectively) were calculated using TBtools. The Ka/Ks ratio > 1, Ka/Ks ratio = 1 and Ka/Ks ratio 1 indicated positive, neutral, and negative/purifying selection, respectively [32, 33]. Every pair of identical GLN genes was subjected to the predicted selection pressure.

Plant treatments and the qRT-PCR analysis

The experiment was conducted in the greenhouse at the Institute of Cotton Research of the Chinese Academy of Agricultural Science. Healthy seeds (G. hirsutum L. acc. TM − 1) were sown in a 1:1 mixture of sand and vermiculite for 1 week in a germinator. After the two cotyledons had fully opened, seedlings of uniform height were selected and transplanted into 8 L plastic containers and grown at 28℃ under a 16/8 h light/dark cycle with 60% relative humidity, as previously reported in our studies [34, 35]. During the first week after transplanting, all the seedlings were supplied with 1/2-strength Hoagland solution, followed by the full strength solution, until the seedlings had reached the three true leaves stage. The Hoagland culture medium was renewed every 5 days.

Based on the literature and previous research, we identified three different N concentrations for plant growth, which included low N (LN; 0.25 mM of the NO3 solution), normal N (NN; 5 mM of the NO3 solution) and high N (HN; 10 mM of the NO3 solution) [36, 37]. After 4 weeks of growth, three plants from each treatment were collected for qRT-PCR analysis. For the N induction treatment experiment, plants with three true leaves were cultured with no-N Hoagland solution for 5 d, and the leaf and root samples were collected at 0 h, 1 h, 3 h, 6 h, 12 h and 24 h after N resupply treatment. Three plants from each treatment were collected for qRT-PCR analysis. The plants were grown under normal N for 2 months to analyze the pattern of expression of the GhGLNs. The leaves, roots, stem, pistil, stamen, petals and calycle samples were collected for qRT-PCR analysis.

We used the Real-time PCR (TaqMan) Primer and Probe Design Tool (Real-time PCR Primer Design-Real-time PCR Probe Design [-GenScript Biotech, Piscataway, NJ, USA]) to generate the qPCR-specific primers for the 10 representative GhGLN1 family genes using the N treatment transcriptome data. Table S5 contains the list of the primer sequences used for the qRT-PCR analysis. We obtained the total RNA using an RNA prep Pure Plant kit (TianGen, Beijing, China) and measured the quantity and quality of the RNA samples with a spectrophotometer. The total RNA was extracted from the leaf samples using an EASYspin plus Plant RNA Kit (Aidlab Biotechnologies Co., Ltd., Beijing, China) and reversed-transcribed into cDNA using a TransStart® Top Green qPCR SuperMix (+ DyeII) [38]. The housekeeping gene, β-actin, served as an internal reference for the qRT-PCR analysis, and the delta-delta Ct (2−∆∆Ct) method was utilized to determine the relative levels of expression of the genes [39, 40].

VIGS treatment and measurement of the concentration nitrogen

To silence the expression of GhGLN1.1a, we cloned its 300-bp coding region into the CLCrV vector. Table S5 contains the cloning primer sequences. The created construct, recombinant CLCrV-GhGLN1.1a, was then combined in a 1:1 ratio with the helper vector (pCLCrV) strain at an OD600 of 1.5, and the recombinant and empty CLCrV vectors were transferred into Agrobacterium tumefaciens GV3101 for agroinfiltration of the plants. The infiltrated plants were kept at a constant temperature of 25 °C to facilitate efficient viral infection and transmission. The plants were grown in a 1:1 mixture of nutrient soil and vermiculite.

The contents of N in the leaf samples of the boll opening of cotton plants were determined using the Kjeldahl method [41]. The dried samples of all the functional leaves were crushed into a fine powder. Approximately 0.2 g of each sample powdered was weighed and digested with sulfuric acid-hydrogen peroxide (H2SO4-H2O2), and then analyzed for their N content using the AutoAnalyzer III (AA3; SEAL Analytical, Inc., Mequon, WI, USA). The accumulation of N and the NUE in the plants was calculated as described by Iqbal [36] The accumulation of N was determined as the product of the content of total N in the leaves and their total dry weight. The NUE was measured as the total leaf dry weight divided by the leaf total N content (Table S6). Each measurement was conducted in triplicate, and the mean and standard deviation (SD) of the three replicates was used to obtain the final measurement. A t-test was used to determine the significance of the differences between the samples.


Genome-wide characterization and chromosomal position analysis of the GLN genes in four cotton species

Members of the GLN protein family were identified in four species of cotton (G. arboreum, G. raimondii, G. barbadense and G. hirsutum) based on their similarity to the six GLN proteins from the A. thaliana TAIR database. Finally, 42 putative GLN genes were obtained from the genomes of the four cotton species, including seven each from G. raimondii and G. arboreum and 14 each from G. barbadense and G. hirsutum. The properties of these 42 GLN proteins are shown in Table S1. Moreover, the four cotton species had coding amino acid lengths that ranged from 266 to 441 and molecular weights that ranged from 29.293 and 48.559 kDa. Nine proteins had PI values higher than 7, and these included Ga03G0313.1 (7.521), Gh_A02G031900.1 (7.521), Gh_D02G037300.1 (7.521), Gh_A09G220300.1 (7.9), Gbar_A02G002530.1 (7.521), Gbar_D02G003200.1 (7.521), Gbar_A09G021170.1 (7.856), Gorai.005G035800.1 (7.521) and Gorai.006G218100.1 (7.234). The remaining proteins had pI values below 7, indicated that they were acidic, whereas those whose pI values above 7 were alkaline. Additionally, the grand average of hydropathy (GRAVY) scores of all 42 proteins were negative, which indicated that they were all hydrophilic.

A map of the gene location was created by TBtools to show the distribution of GLN genes in the chromosomes of the four cotton species (Figure S1). Each chromosome contained one GLN gene, and most of these genes were found near the ends of the chromosomes. Chromosomes 8 and 10 of all four cotton species had no GLN genes. There were seven GLN genes over all in subgenomes A and D of G. barbadense, and seven GLN genes in subgenomes A and D of G. hirsutum. This indicated significant conservation of the GLNs between the A and D genomes of these cotton species.

Gene structure, phylogenetic analysis and an examination of the conserved motifs

We obtained protein sequences from four different cotton species and A. thaliana that contained the GLN domain to create a phylogenetic tree to clarify the phylogenetic relationships of the GLN genes (Fig. 1A). Five A. thaliana sequences with the highest similarity with those of cotton were named AtGLN1.x (x denotes from 1–5). The GLN sequences matched the AtGLN1.1–5 and AtGLN2 sequences were denoted GLN1.1–5 and GLN2, respectively.

Fig. 1
figure 1

Comprehensive analysis of the GLN gene family traits of the four cotton species. a Phylogenetic analysis of the GLN proteins from four cotton species. A bootstrap analysis with 1000 iterations was performed after the phylogenetic tree was created using the neighbor-joining (NJ) technique. b Exon organization of the GLN genes. Yellow boxes represent exons. C The 15 conserved motifs of the GLN proteins of the four cotton species. The motifs are indicated by various colored boxes

We analyzed the conserved motifs and the gene structure of the GLN gene family in cotton in more detail (Fig. 1b, c). We identified 15 conserved motifs in the four cotton species using the MEME-MEME Suite ( and TBtools (Fig. 1C), and the different motifs occurred in varied combinations in the various subfamilies in varied combinations (Figure S2). The gene annotation gff3 files were used to evaluate the structure of the GLN genes, and most of the motifs in the GLN genes of the four cotton species showed comparable patterns. However, motifs 7, 12 and 13 were only found in the GLN2 group, while motif 15 was only found in GbGLN1.1c and AtGLN1.2.

TBtools was utilized to generate exon and intron structure plots, enhancing our comprehension of the diverse structural characteristics of the GLNs (Fig. 1B). We discovered that the number of exons/introns, exon length and motif information shared by all the paralogs found in the same branch of the phylogenetic tree were identical, which indicated that there had been no structural and functional changes after the gene pairs had formed.

Regulatory elements of the GhGLN1 genes

We analyzed the expression levels of the 10 GhGLN1 genes under abiotic stresses based on the already published RNA-seq data (accession number: PRJNA248163 [42]) and the regulatory components in the 5' upstream regions of G. hirsutum to determine the functions of the GLN gene family in G. hirsutum. GhGLN1.1 a, GhGLN1.3 c and GhGLN1.3d were highly expressed in various organs under abiotic stresses, compared with the other seven genes. GhGLN1.1 a, GhGLN1.3 c and GhGLN1.3d were highest under cold, heat, salt and drought (polyethylene glycol (PEG)-induced) stresses, which indicated that these genes may have some regulatory functions under cold, heat, salt and drought stresses (Fig. 2A). Moreover, GhGLN1.1 a, GhGLN1.3 c and GhGLN1.3d contained many anaerobic induction regulatory elements and phytohormone regulatory elements (abscisic acid, methyl jasmonate (MeJA) and salicylic acid (SA) responsiveness) (Fig. 2B). Moreover, putative regulatory elements were prevalent but not conserved in the 5'-upstream regions of the GhGLN family genes of G. hirsutum (Fig. 2). Furthermore, only a few GLN genes had certain regulatory elements (such as responsiveness to low-temperature), which suggested that some of these genes are triggered by different signals.

Fig. 2
figure 2

Regulatory elements of the GhGLN1 genes. A Expression levels of 10 GhGLN1 genes under abiotic stresses. The expression levels are shown as the log2FPKM values. FPKM; Fragments Per Kilobase of transcript per Million mapped reads. B The regulatory regions of 10 GhGLN1 gene members. The regulatory regions are located 2000 bp upstream of ATG. The position "0" in the figure corresponds to the ATG. The color blocks on the lines indicate various regulatory elements

Alignment of the GhGLN proteins

Figure S3 shows the identities of the GhGLN1 and AtGLN1 proteins and the percentage identity between the translated protein sequences of GhGLN1 and AtGLN1. High degrees of sequence similarity existed between the GhGLN1 protein sequences and each of the five AtGLN1 protein sequences. The GhGLN1 proteins were 80.8% to 90.4% identical to their AtGLN1 orthologous proteins. Two conserved Pfam domains (Pfam 03951 and Pfam 00120) specific to glutamine synthetase enzymes were found in all the GhGLN protein sequences (Figure S4). Based on previous research, some of the ammonium/glutamate-binding pocket residues (shown in short purple lines) were highly conserved [43], and some (shown in boxes) were associated with the characteristics of affinity for NH4+ [44]. The polar amino acids Q49 and S183 were identified as playing crucial roles in the highly specific binding properties of NH4+ to AtGLN1.1 and AtGL1.4. While S183 remained strictly conserved in GhGLN1.3c, GhGLN1.3d, and all GhGLN1.1 proteins, Q49 was not conserved in all GhGLN proteins. In the GhGLN1 sequences, the polar Q49 was transformed into basic glutamate K49 and R49. It could be that the properties for the affinity for NH4+ of these modified amino acids were maintained in GhGLN1.3c, GhGLN1.3d and all the GhGLN1.1 proteins. However, the residues K49, A183 and E49 found in the low-affinity enzymes AtGLN1.2, AtGLN1.3 and AtGLN2 were preserved in most of the GhGLN1.2, GhGLN1.3 and GhGLN2 protein sequences, which indicated that the low NH4+ affinity qualities of these three protein classes had not changed (Figure S4).

Analysis of GLN gene duplication and collinearity in the four cotton species

We examined the intraspecific duplication events of the GLN genes to understand the evolution of the GLN gene family in cotton. Gene expansion and the emergence of novel gene functions are often shaped by gene duplication events. In this study, we employed the TBtools MCScan package to conduct a homologous BLAST analysis of cotton amino acids. G. arboreum contained 16,143 collinear genes, 1235 collinear blocks and 2375 tandem repeat genes (Table S2). However, G. raimondii had 16,642 collinear genes, 707 collinear blocks and 909 tandem repeat genes (Table S2). G. barbadense contained 55,672 collinear genes, 3299 collinear blocks and 3304 tandem repeat genes (Table S2), while G. hirsutum had 3334 tandem repeat genes, 3242 collinear blocks and 55,454 collinear genes (Table S2). Paralogous pairings of the GLN gene families were produced owing to whole segmental duplication or genome duplication. Transpositions might have produced many paralogous genes in the four cotton species, with a minimal contribution from tandem repeat genes. Four scattered and three segment duplicates were discovered in G. arboreum (Table S3). Similarly, four genes that had undergone scattered duplications and that which had undergone segmental duplications were identified in G. raimondii. In tetraploid cotton species, G. barbadense exhibited 14 segmental gene duplications, which was similar to the findings in G. hirsutum (Table S3). Homologous BLAST findings demonstrated the collinearity of the four cotton species (Fig. 3). A-Gh At, A-Gb At, D-Gh Dt and D-Gb Dt gene pairs from the four cotton species were used for the collinearity test (Fig. 3). Unexpectedly, there were fewer similarities of duplication between the D genomes of G. arboreum, G. barbadense and G. hirsutum than between their A genomes. This suggested that the A genome contributed more to duplication during the evolutionary cycle, which generated more GLN gene family traits.

Fig. 3
figure 3

At sub-genomes GLN genes collinearity relationship and Dt sub-genomes GLN genes collinearity relationship in cotton. A Synteny and collinearity relationships between G. hirsutum At sub-genomes, G. barbadense At sub-genomes and G. arboretum. B Synteny and collinearity relationships between the G. hirsutum Dt sub-genomes, G. barbadense Dt sub-genomes and the G. raimondii. The collinearity of the GLN genes across several genomes is shown by blue lines

The Ka/Ks ratio reflects the evolutionary path of a gene or gene area. There were 3, 1, 18 and 21 pairs of gene duplication in G. arboreum, G. raimondii, G. barbadense and G. hirsutum, respectively (Figure S5). The GLN genes in G. arboreum acquired segmental duplication between 7.71 and 55.72 million years ago (Mya), while those in G. raimondii were duplicated between 7.26 and 42.29 Mya. Segmental duplication was observed between 0.44 and 26.04 Mya in G. barbadense and between 0.56 and 102.06 Mya in G. hirsutum (Table S4). Furthermore, we evaluated the Ka/Ks ratio of every duplicated gene pair to examine their rates of molecular evolution. The findings revealed that most intraspecific duplicated gene pairs had ratio values between 0.05 and 0.64 (Figure S5 and Table S4), and none had molecular evolution rates of greater than 1. To explore the evolution of the GLN genes in the four cotton species in more detail, we evaluated their collinearity and interspecific orthologous gene pairs. Only one orthologous gene pair (Gh_A11G178900.1_vs_Ga11G2230.1) exhibited positive selection, as shown by their Ka/Ks ratio which was greater than 1 (Figure S5 and Table S4b). Most orthologous gene pairs had a Ka/Ks ratio of less than 1, indicating that segmental duplication was the main driving force for the expansion of the GhGLN gene family.

A collinearity analysis was also performed between the sub-genomes of various cotton species (Fig. 4). Unorganized collinearity links existed between the chromosomes, with 27 collinear gene pairs between G. arboretum and G. hirsutum and 26 collinear gene pairs between G. raimondii and G. hirsutum. Considering the structural changes and lack of order of the chromosomes, the collinearity blocks were well-matched and covered most of the chromosomes. This was in line consistent with the fact that G. hirsutum originated through the hybridization of G. arboreum and G. raimondii, which was followed by their subsequent polyploidization [45]. There were 50 collinear gene pairings between the G. hirsutum and G. barbadense, and only one homologous gene pair was found in chromosomes Gh-A11 and Gh-D11, However, at least two homologous gene pairs were found in the other chromosomes. These four cotton species were found to have a close evolutionary relationship, although their chromosomal structures underwent major changes. TBtools were used to generate the Circos map and show the synteny of the GLN genes in G. hirsutum (Figure S6). There were 14 GhGLNs evenly distributed throughout 14 chromosomes of G. hirsutum. A complex collinearity relationship existed between the 14 GhGLNs, as shown in Figure S6. Each GhGLN in the At sub-genome matched at least one GhGLN in the Dt sub-genome. However, only GhGLN1.1b corresponded to GhGLN1.1a, and GhGLN1.1d to GhGLN1.1c. Five corresponding genes matched several GhGLNs across the entire genome; For example, GhGLN1.3b, GhGLN1.3d, GhGLN1.3f, GhGLN1.3a, GhGLN1.3c and GhGLN1.3e matched one another.

Fig. 4
figure 4

Collinearity relationship between the homologous GLN genes of the four cotton species. The lines in different colors connect collinear gene pairs. The chromosome numbers are shown in boxes and are denoted as GhA1–A13, GhD1‒D13, GbA1–A13, GbD1‒D13, GaChr01- Chr13 and GraiChr01- Chr13

Expression pattern analysis of GhGLN1s

Heatmaps of the expression levels of 10 GhGLN1 genes were created to further investigate the functions of the GhGLN family genes. We found that four genes (GhGLN1.1a, GhGLN1.1b, GhGLN1.3c and GhGLN1.3d) were highly expressed in the roots, stems and leaves of G. hirsutum. The expression levels of GhGLN1.1a and GhGLN1.1b were higher in the roots, while those of GhGLN1.3c and GhGLN1 0.3d were more highly expressed in the stems (Fig. 5A).

Fig. 5
figure 5

The pattern of expression the GhGLN1 family genes. A The differential expression of 10 GhGLN1 genes in different tissues. B The level of expression of the GhGLN1 genes in the roots and leaves after the N induction treatment by qRT-PCR. The mean value of expression value was calculated from three independent biological replicates. The raw data of the relative value of expression is provided in TableS6. qRT-PCR, quantitative real-time reverse-transcription PCR

The changes in the levels of expression of the 10 GhGLN1 genes were also analyzed in the roots and leaves 0 h, 1 h, 3 h, 6 h, 12 h and 24 h after the N induction treatment. The expression level of the GhGLN1.1a gene in the cotton roots increased gradually and stably with time under the N induction treatment. In particular, the expression level increased tenfold after 1 h, twofold after 3 h, and nearly 40 fold after 24 h of the N induction treatment. This indicated thatGhGLN1.1a was significantly induced by N in the cotton roots. Compared with the roots, GhGLN1.1a was expressed at lower levels in the cotton leaves after the N induction treatment (Fig. 5B).

To detect the expression of GLN gene under different N levels, a 4-week experiment was conducted, and three N treatments were set up, namely low N (LN), normal N (NN), high N (HN). After 4 weeks of growth under the N treatments, root and shoot samples were collected to measure the expression levels of the 10 GhGLN1 genes using qRT-PCR. The levels of expression GhGLN1.3a, GhGLN1.3b, GhGLN1.3e and GhGLN1.3f genes in the roots and shoots were very low under the three N treatments. The genes GhGLN1.3c and GhGLN1.3d exhibited high expression levels in both roots and shoots across the three N treatments, with their expression levels positively correlating with N concentration in shoots. Conversely, with rising N concentrations, the expression levels of GhGLN1.1a, GhGLN1.1b, GhGLN1.1c, and GhGLN1.1d increased in roots, with GhGLN1.1a showing the most pronounced increase in expression. In the roots, the expression of GhGLN1.1a was 2.47 under the LN treatment and increased to 14.78 under the HN treatment, representing a six-fold rise in expression level for this gene (Fig. 6). Among the three N concentration treatments, the expression changes of the other nine genes in roots were not as pronounced as the increase observed in GhGLN1.1a expression, suggesting that GhGLN1.1a in roots is particularly sensitive to N treatments.

Fig. 6
figure 6

A qRT-PCR analysis of the relative expression of GhGLN1 genes in the roots and shoots of cotton under different N concentrations. The error bars represent the mean standard deviations of three biological replicates. HN, high nitrogen; LN, low nitrogen; NN, normal nitrogen; qRT-PCR, quantitative real-time reverse-transcription PCR

Silencing of GhGLN1.1a

The cotton seedlings were transformed with the CLCrV-CLA1, CLCrV: 00 and CLCrV: GhGLN1.1a vectors. Subsequently, the efficacy of GhGLN1.1a silencing during cotton boll opening was assessed using qRT-PCR. The gene silencing induced by CLCrV: GhGLN1.1a was effective in the infiltrated leaves (Fig. 7A-B). The plant dry weight, plant fresh weight, GLN activity, N contents, N accumulation, and the NUE of the CLCrV:GhGLN1.1a-silenced plants were significantly lower compared with those of the CLCrV: 00 plants (Fig. 7C-H). This confirmed that the inactivation of GhGLN1.1a affected the activity of GLN, N accumulation, and NUE.

Fig. 7
figure 7

Silencing of the GhGLN1.1a gene by VIGS and plant growth and analyses of nitrogen use efficiency in cotton plants. A The phenotype of the control and gene-silenced plants. The gene-silenced plants have albino phenotypes. “CLCrV-CAL1”, chlorophyll-deficient plants; “WT”, the wild-type plants; “CLCrV:00”, the plants carrying the CLCrV empty vector; “CLCrV: GhGLN1.1a”, the GhGLN1.1a-silenced plants. B Relative expression level. C Plant dry weight. D Plant fresh weight. E Glutamine synthetase (GLN) activity. F N content of the leaves. G Accumulation of N in the leaves. H N use efficiency (NUE). VIGS, virus-induced gene sequency. Error bars show the standard deviations of the three replicate trials (*/**/*** denote significant differences between the empty vector and GhGLN1.1a-silenced plants, where * indicates p < 0.05, ** indicates p < 0.01 and *** suggests p < 0.001)


Glutamine synthetase (GLN) is an essential enzyme for the metabolism of N and the assimilation and remobilization of ammonium. GLN are complicated owing to their existence as two isoenzymes, one in the chloroplast and the other in the cytosol, and the fact that the cytosolic one has many isoforms. The six GLN genes of A. thaliana are anticipated to have various functions depending on the plant organs and the N availability in the soil. A multigenic family encodes the multiple isoforms [21]. Similarly, the functions of five GLN1 genes in maize depend on the N levels [46]. Nevertheless, GLN genes in cotton are still unclear, particularly under different N levels. This study purposed to analyze the expression of the GhGLN genes under different N levels and identify the entire GLN gene family in cotton.

GLN isoforms have been examined in various plants, including soybeans [47], potatoes [48] and tomato [37], thus, establishing a crucial foundation to study the functional GLN isoforms. However, the GLN family members and their functions have not yet been reported in cotton. This study employed bioinformatics analysis to investigate the structure and function of GLN family members in cotton. For the analysis of cotton GLN genes' functions, we utilized 42 identified GLN genes identified as potential candidates. These GLN genes were categorized into three lineages and named based on phylogenetic trees constructed using their amino acid sequences. A portion of the functional conservation of the proteins was represented by exon–intron and protein structural conservation. An analysis of gene structure and conserved motifs showed that the GLNs has a higher structural consistency. Most GLNs comprised 10 identical motifs, and no subfamily-specific motifs were found. We also found that other genes with close biological relationships in the same subfamily had the same motif eliminated. Additionally, the GLNs from the same subfamily shared similar gene structures and motifs, which indicated that the conserved motifs and gene structural changes may have greatly influenced the functional evolution of the GLN genes in cotton. The similar structures and patterns of the GLN genes also indicated the possibility of interactions between genes from the same subfamily.

PlantCARE is a database of the plant cis-regulatory elements, it has abundant important regulatory sequences, including cis-regulatory elements, enhancers and suppressors, and can provide important information to predict the molecular regulatory mechanism of genes [21]. Cis-elements and trans-acting factors can control the levels of expression of the genes by interacting with the transcription factors (TFs) of the targeted genes [49]. As a result, the expression of the targeted genes is differentially regulated by the cis-acting regions. An analysis of the promoter regions revealed that each member of the GhGLN1 gene family had a different number and arrangement of regulatory components. Each GhGLN1 gene may be subject to complex regulation, depending on the amount and types of regulatory elements in the GhGLN1 gene family. This indicates that the roles of these genes are not duplicated. This study used the PlantCARE database to analyze the 2000 bp nucleotide sequences upstream of ATG of the 10 GhGLN1 genes. The results showed that the 5’ terminal promoter region of the GhGLN1 gene contained binding elements specific to auxin response, low-temperature response, plant hormone response, and MYB TFs. An analysis of the gene sequences showed that most of the 10 members contained MYB binding sites, which might explain the regulation of MYB TFs in the GhGLN1 gene family (Fig. 2). EI- Kereamy et al. [22] found that the content of amino acids increased significantly in transgenic rice that overexpressed OsMYB55 because of the expression levels of synthetases of some amino acids, including OsGS1. 2 genes were changed, which indicated that e OsMYB55 could regulate the expression of OsGS1. 2 genes. In addition, our results showed that there were some important regulatory elements in the 2000 bp sequence upstream of the ATG of the GhGLN1 genes, and these included response elements specific to ABA, MeJA, SA, auxin, gibberellin and other response elements. Currently, there are few reports on the regulation of GLN genes by these response elements, thus necessitating further studies.

Polyploidy is a key factor in evolution and a crucial mechanism for the diversification of plants [50]. The hybridization of the G. raimondii-like D-genome ancestor (D5) and the G. arboreum-like A-genome ancestor (A2) yielded the all-tetraploid cotton (G. hirsutum), which then underwent chromosomal doubling [51]. As previously shown study, the At and Dt subgenomes evolved differently, with structural rearrangements and gene deletions occurring more frequently in the At subgenome [42]. However, we found that no GLN genes were lost in the At or the Dt subgenomes, and the GLN genes of the tetraploid cotton were identical to those in the diploid ones. It has been demonstrated that duplicated gene pairs regularly develop through various mechanisms, including pseudogenization, neo-functionalization and sub-functionalization [52]. These provide a testable hypothesis that the neo-functionalized gene copies exhibit positive selection (Ka/Ks > 1), whereas the sub-functionalized gene copies are susceptible to purifying selection (Ka/Ks = 1) [53]. In this study, the Ka/Ks ratio of the most duplicated gene pairs was less than one, which suggested that these genes mainly primarily their original functions and were subject to purifying selection pressure during evolution. Only one orthologous gene pair between G. arboretum and G. hirsutum (At) had the Ka/Ks ratio greater than one. These findings suggest that throughout the GLN genes of At sub-genomes may have undergone more positive selection than the Dt sub-genomes during the development of tetraploids from diploids.

Using pre-existing RNA-seq and qRT-PCR data, we constructed heat maps illustrating the expression levels of the 10 GhGLN1 genes. This allowed for a more detailed investigation into the functions of GLN family genes. The results showed that the GhGLN1.1a gene was highly and specifically expressed in the roots, and its expression in the cotton roots was significantly induced by N induction. Plants respond to abiotic stresses by activating numerous molecular, cellular and physiological mechanisms, which negatively impact their growth and development. Most GhGLN1 genes are associated with various environmental conditions, including cold, heat, salt and drought, and their patterns of expression depend on their responses to abiotic stimuli. The expression levels of 10 GhGLN1 genes were examined under cold, heat, saline and drought abiotic stresses. The expression of the GhGLN1.1a gene was significantly increased after 12 h of cold, heat, salt and drought stress, which indicating that the gene may have some regulatory roles under cold, heat, salt and drought stresses.

Since the 3–5 GLN1 members in plants show specificity in their expression in tissues, it is important to study the biological functions of different GLN1 genes to clarify the mechanism of the development of specific tissues or organs of plants [36]. The qRT-PCR results in this study showed that GhGLN1.1a, GhGLN1.1b, GhGLN1.1c and GhGLN1.1d were highly expressed and specifically expressed in the cotton roots. The qRT-PCR data analysis also showed that the GhGLN1.1a gene was specifically expressed in cotton roots and significantly induced by the N induction treatment. Therefore, GhGLN1.1a was selected as a representative gene for further functional analysis. Previous research showed that overexpression of the GLN1 gene can enhance the activity of GLN and significantly impact key agricultural variables, such as plant biomass and yield. Early studies in pine trees found that the growth characteristics of transgenic strains were improved by ectopic expression of the GS1a gene in pine trees under greenhouse and field conditions [41]. Studies in maize, wheat, rice, and A. thaliana also showed that the GLN1 gene greatly increased the grain yield. Thus, the phenotypic performance of various plants that overexpressed GLN1 homologous genes is inconsistent. This indicates that the upstream or downstream sequence of the GLN1 gene may affect the GLN activity, thereby affecting its biological function to some extent. Thus, it is necessary to study the molecular regulatory mechanism of the GLN gene to improve the NUE of plants [42, 43]. In this study, GhGLN1.1a was silenced using VIGS, and the silencing efficiency was approximately 50% during the spit stage, at which the GLN activity and NUE were significantly reduced compared with the wild-type plants. However, owing to the high homology of the GLN isoenzymes and the lack of effective specific antibodies, the localization, expression and functional analyses of GLN isoenzymes are mostly conducted at the transcription level. Moreover, the expression of GLN is also strictly regulated at the transcription, post-transcriptional and post-translational stages, which indicates that studying GLN at the transcriptional level alone does not fully reveal its role in N assimilation.

GLN is regulated at multiple levels, including during the transcription of GLN genes, polyadenylation for mRNA stability, peptide synthesis, post-translational modifications and protein transport. In addition, many other compounds affect GLN activity; for example, Takashi showed that the ACR11 protein promotes AtGLN2 activity in A. thaliana. Lima [42] showed that AtGLN2 is regulated by phosphorylation and interaction with 14–3-3 proteins. NLP7 TFs induce the expression of GS2. In this study, gene sequence analysis showed that the 5’ end promoter region of the GS gene contained elements that specifically bind the transcription factors such as MYB (v-myb avian myeloblastosis viral oncogene homolog) and Dof (DNA binding with one finger). Recently, El-Kereamy et al. found that the amino acid content in the rice trans-OsMYB55 gene had increased significantly owing to the altered expression of the synthases for some amino acids, including OsGS1:2, which indicated that OsMYB55 can regulate the expression of OsGS1:2 [48]. The initiator regions of the six GS genes in maize contained MYB binding sites, ZmGS1-2 and ZmGS1-2 genes had five MYB binding sites, ZmGS1-2 and ZmGS1-5 contained three each, while ZmGS1-3 and ZmGS2 contained two and one, respectively. The existence of multiple MYB binding sites also suggests their complex regulatory mechanisms [48]. Studies on pine Dof5 showed that Dof5 transcription factors can concurrently regulate the expression of GS1a and GS1b to promote the expression of GS1b while inhibiting the transcription of GS1a, thereby regulating the spatial distribution of GS1 isoenzymes in pine trees [49]. In addition, some members of the LBD (Lateral organ boundaries domain) gene family regulate N metabolism [50]. Rubin et al. found that the expression of some N metabolism genes and the content of amino acids (glutamate) were significantly reduced in the A. thaliana plants that overexpressed three LBD genes, including the GLN gene [51]. Therefore, GhGLN1 was studied at the post-transcriptional and post-translational levels in subsequent experiments to fully reveal its role in N assimilation.


The study identified 7, 7, 14, and 14 members of the GLN gene family from the genomes of G. raimondii, G. arboreum, G. hirsutum, and G. barbadense, respectively. These GLN genes were classified into three lineages based on their phylogenetic relationships, as well as their possession of similar gene structures and motifs. Genome localization revealed one GLN gene per chromosome, predominantly located at the distal ends. Whole-genome duplication significantly influenced the expansion of the GLN family in cotton. Notably, GhGLN1.1a exhibited the highest expression levels under various abiotic stresses and harbored regulatory elements responsive to anaerobic conditions and phytohormones. qRT-PCR analysis revealed root-specific expression of GhGLN1.1a, particularly sensitive to N induction, suggesting its significance for further functional analysis. VIGS experiments demonstrated that inactivation of GhGLN1.1a affected N accumulation and NUE. These findings provide a foundation for future research on the functionality of GLN proteins.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article and its additional files.


  1. Guan M, Moller IS, Schjoerring JK. Two cytosolic glutamine synthetase isoforms play specific roles for seed germination and seed yield structure in Arabidopsis. J Exp Bot. 2015;66(1):203–12.

    Article  CAS  PubMed  Google Scholar 

  2. Hirel B, Martin A, Terce-Laforgue T, Gonzalez-Moro MB, Estavillo JM. Physiology of maize I: A comprehensive and integrated view of nitrogen metabolism in a C4 plant. Physiol Plant. 2005;124(2):167–77.

    Article  CAS  Google Scholar 

  3. Lea PJ, Azevedo RA. Nitrogen use efficiency. 2. Amino acid metabolism. Ann Appl Biol. 2007;151(3):269–75.

  4. Tobin AK, Yamaya T. Cellular compartmentation of ammonium assimilation in rice and barley. J Exp Bot. 2001;52(356):591–604.

    Article  CAS  PubMed  Google Scholar 

  5. Thomsen HC, Eriksson D, Moller IS, Schjoerring JK. Cytosolic glutamine synthetase: a target for improvement of crop nitrogen use efficiency? Trends Plant Sci. 2014;19(10):656–63.

    Article  CAS  PubMed  Google Scholar 

  6. Harrison J. Pou de Crescenzo MA, Sene O, Hirel B: Does lowering glutamine synthetase activity in nodules modify nitrogen metabolism and growth of Lotus japonicus? Plant Physiol. 2003;133(1):253–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Swarbreck SM, Defoin-Platel M, Hindle M, Saqi M, Habash DZ. New perspectives on glutamine synthetase in grasses. J Exp Bot. 2011;62(4):1511–22.

    Article  CAS  PubMed  Google Scholar 

  8. Freeman J, Marquez A, Wallsgrove RM, Saarelainen R, Forde BG. Molecular analysis of barley mutants deficient in chloroplast glutamine synthetase. Plant Mol Biol. 1990;14(3):297–311.

    Article  CAS  PubMed  Google Scholar 

  9. Sakamoto A, Ogawa M, Masumura T, Shibata D, Takeba G, Tanaka K, Fujii S. Three cDNA sequences coding for glutamine synthetase polypeptides in Oryza sativa L. Plant Mol Biol. 1989;13(5):611–4.

    Article  CAS  PubMed  Google Scholar 

  10. Li MG, Villemur R, Hussey PJ, Silflow CD, Gantt JS, Snustad DP. Differential expression of six glutamine synthetase genes in Zea mays. Plant Mol Biol. 1993;23(2):401–7.

    Article  CAS  PubMed  Google Scholar 

  11. Tingey SV, Tsai FY, Edwards JW, Walker EL, Coruzzi GM. Chloroplast and cytosolic glutamine synthetase are encoded by homologous nuclear genes which are differentially expressed in vivo. J Biol Chem. 1988;263(20):9651–7.

    Article  CAS  PubMed  Google Scholar 

  12. Sakakibara H, Kawabata S, Takahashi H, Hase T, Sugiyama T. Molecular cloning of the family of glutamine synthetase genes from maize. Expression of genes for glutamine synthetase and ferredoxin-dependent glutamate synthase in photosynthetic and non-photosynthetic tissues. Plant Cell Physiol. 1992;33(1):49–58.

    CAS  Google Scholar 

  13. Guan M, Schjoerring JK: Peering into the separate roles of root and shoot cytosolic glutamine synthetase 1;2 by use of grafting experiments in Arabidopsis. Plant Sign  Behav. 2016;11(11):e1245253.

  14. Ji YY, Li Q, Liu GS, Selvaraj G, Zheng ZF, Zou JT, Wei YD. Roles of cytosolic glutamine synthetases in Arabidopsis development and stress responses. Plant Cell Physiol. 2019;60(3):657–71.

    Article  CAS  PubMed  Google Scholar 

  15. Konishi N, Ishiyama K, Beier MP, Inoue E, Kanno K, Yamaya T, Takahashi H, Kojima S. Contributions of two cytosolic glutamine synthetase isozymes to ammonium assimilation in Arabidopsis roots. J Exp Bot. 2017;68(3):613–25.

    CAS  PubMed  Google Scholar 

  16. Moreira E, Coimbra S, Melo P. Glutamine synthetase: an unlikely case of functional redundancy in Arabidopsis thaliana. Plant Biol. 2022;24(5):713–20.

    Article  CAS  PubMed  Google Scholar 

  17. Martin A, Lee J, Kichey T, Gerentes D, Zivy M, Tatout C, Dubois F, Balliau T, Valot B, Davanture M, et al. Two cytosolic glutamine synthetase isoforms of maize are specifically involved in the control of grain production. Plant Cell. 2006;18(11):3252–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Goodall AJ, Kumar P, Tobin AK. Identification and expression analyses of cytosolic glutamine synthetase genes in barley (Hordeum vulgare L.). Plant Cell Physiol. 2013;54(4):492–505.

    Article  CAS  PubMed  Google Scholar 

  19. Goel P, Singh AK. Abiotic stresses downregulate key genes involved in nitrogen uptake and assimilation in Brassica juncea L. Plos One. 2015;10(11):e0143645.

  20. Wang H, Zhang M, Guo R, Shi D, Liu B, Lin X, Yang C. Effects of salt stress on ion balance and nitrogen metabolism of old and young leaves in rice (Oryza sativa L.). BMC Plant Biol. 2012;12:1–11.

  21. Lothier J, Gaufichon L, Sormani R, Lemaitre T, Azzopardi M, Morin H, Chardon F, Reisdorf-Cren M, Avice JC, Masclaux-Daubresse C. The cytosolic glutamine synthetase GLN1;2 plays a role in the control of plant growth and ammonium homeostasis in Arabidopsis rosettes when nitrate supply is not limiting. J Exp Bot. 2011;62(4):1375–90.

    Article  CAS  PubMed  Google Scholar 

  22. Cheng LX, Wang YP, He Q, Li HJ, Zhang XJ, Zhang F. Comparative proteomics illustrates the complexity of drought resistance mechanisms in two wheat (Triticum aestivum L.) cultivars under dehydration and rehydration. Bmc Plant Biol. 2016;16:1-23.

  23. Yousfi S, Marquez AJ, Betti M, Araus JL, Serret MD. Gene expression and physiological responses to salinity and water stress of contrasting durum wheat genotypes. J Integr Plant Biol. 2016;58(1):48–66.

    Article  CAS  PubMed  Google Scholar 

  24. Kwon SJ, Kwon SI, Bae MS, Cho EJ, Park OK. Role of the methionine sulfoxide reductase MsrB3 in cold acclimation in Arabidopsis. Plant Cell Physiol. 2007;48(12):1713–23.

    Article  CAS  PubMed  Google Scholar 

  25. Lu BB, Yuan YZ, Zhang CF, Ou JQ, Zhou W, Lin QH. Modulation of key enzymes involved in ammonium assimilation and carbon metabolism by low temperature in rice (Oryza sativa L.) roots. Plant Sci. 2005;169(2):295–302.

    Article  CAS  Google Scholar 

  26. Chaffei C, Pageau K, Suzuki A, Gouia H, Ghorbel MH, Masclaux-Daubresse C. Cadmium toxicity induced changes in nitrogen management in Lycopersicon esculentum leading to a metabolic safeguard through an amino acid storage strategy. Plant Cell Physiol. 2004;45(11):1681–93.

    Article  CAS  PubMed  Google Scholar 

  27. Rana NK, Mohanpuria P, Yadav SK. Cloning and characterization of a cytosolic glutamine synthetase from Camellia sinensis (L.) O. Kuntze that is upregulated by ABA, SA, and H2O2. Mole Biotechnol. 2008;39(1):49–56.

    Article  CAS  Google Scholar 

  28. Singh KK, Ghosh S. Regulation of glutamine synthetase isoforms in two differentially drought-tolerant rice (Oryza sativa L.) cultivars under water deficit conditions. Plant Cell Rep. 2013;32(2):183–93.

    Article  CAS  PubMed  Google Scholar 

  29. Nagy Z, Nemeth E, Guoth A, Bona L, Wodala B, Pecsvaradi A. Metabolic indicators of drought stress tolerance in wheat: Glutamine synthetase isoenzymes and Rubisco. Plant Physiol Biochem. 2013;67:48–54.

    Article  CAS  PubMed  Google Scholar 

  30. Lothier J, Gaufichon L, Sormani R, Lemaître T, Azzopardi M, Morin H, Chardon F, Reisdorf-Cren M, Avice J-C, Masclaux-Daubresse C. The cytosolic glutamine synthetase GLN1; 2 plays a role in the control of plant growth and ammonium homeostasis in Arabidopsis rosettes when nitrate supply is not limiting. J Exp Bot. 2011;62(4):1375–90.

    Article  CAS  PubMed  Google Scholar 

  31. Chen CJ, Chen H, Zhang Y, Thomas HR, Frank MH, He YH, Xia R. TBtools: An integrative toolkit developed for interactive analyses of big biological data. Mol Plant. 2020;13(8):1194–202.

    Article  CAS  PubMed  Google Scholar 

  32. Rehman A, Peng Z, Li HG, Qin GY, Jia YH, Pan Z, He SP, Qayyum A, Du XM. Genome wide analysis of IQD gene family in diploid and tetraploid species of cotton (Gossypium spp.). Int J Biol Macromole. 2021;184:1035–61.

    Article  CAS  Google Scholar 

  33. Zhu SH, Wang XY, Chen W, Yao JB, Li Y, Fang ST, Lv YJ, Li XX, Pan JW, Liu CY, et al. Cotton DMP gene family: characterization, evolution, and expression profiles during development and stress. Int J Biol Macromol. 2021;183:1257–69.

    Article  CAS  PubMed  Google Scholar 

  34. Asif I, Dong Q, Wang X, Gui H, Zhang H, Pang N, Zhang X, Song M. Genotypic variation in root morphology, cotton subtending leaf physiology and fiber quality against nitrogen. J Cotton Res. 2021;4:1–14.

    Article  Google Scholar 

  35. Iqbal A, Qiang D, Xiangru W, Huiping G, Jing N, Leilei L, et al. N-efficient cotton genotype grown under low nitrogen shows relatively large root system, high biomass accumulation and nitrogen metabolism. Agron J. 2022;114(1):582–600.

    Article  CAS  Google Scholar 

  36. Iqbal A, Dong Q, Wang Z, Wang XR, Gui HP, Zhang HH, Pang NC, Zhang XL, Song MZ. Growth and nitrogen metabolism are associated with nitrogen-use efficiency in cotton genotypes. Plant Physiol Biochem. 2020;149:61–74.

    Article  CAS  PubMed  Google Scholar 

  37. Jiang SY, Sun JY, Tian ZW, Hu H, Michel EJS, Gao JW, Jiang D, Cao WX, Dai TB. Root extension and nitrate transporter up-regulation induced by nitrogen deficiency improves nitrogen status and plant growth at the seedling stage of winter wheat (Triticum aestivum L.). Environ Exp Botany. 2017;141:28–40.

    Article  CAS  Google Scholar 

  38. Iqbal A, Dong Q, Wang X, Gui H, Zhang H, Zhang X, Song M. Transcriptome analysis reveals differences in key genes and pathways regulating carbon and nitrogen metabolism in cotton genotypes under N starvation and resupply. Int J Mol Sci. 2020;21(4):1500.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Iqbal A, Qiang D, Xiangru W, Huiping G, Hengheng Z, Xiling Z, Meizhen S. Integrativephysiological, transcriptome and metabolome analysis reveals the involvement of carbon and flavonoidbiosynthesis in low phosphorus tolerance in cotton. Plant Physiol Biochem. 2023;196:302–17.

    Article  CAS  PubMed  Google Scholar 

  40. Iqbal A, Huiping G, Xiangru W, Hengheng Z, Xiling Z, Meizhen S. Genome-wide expression analysis reveals involvement of asparagine synthetase family in cotton development and nitrogen metabolism. BMC Plant Biol. 2022;22(1):122.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Li B, Xin W, Sun S, Shen Q, Xu G. Physiological and molecular responses of nitrogen-starved rice plants to re-supply of different nitrogen sources. Plant Soil. 2006;287(1–2):145–59.

    Article  CAS  Google Scholar 

  42. Zhang TZ, Hu Y, Jiang WK, Fang L, Guan XY, Chen JD, Zhang JB, Saski CA, Scheffler BE. Stelly DM et al: Sequencing of allotetraploid cotton (Gossypium hirsutum L. acc. TM-1) provides a resource for fiber improvement. Nat Biotechnol. 2015;33(5):531-U252.

    Article  CAS  PubMed  Google Scholar 

  43. Eisenberg D, Gill HS, Pfluegl GMU, Rotstein SH. Structure-function relationships of glutamine synthetases. BBA-Protein Struct M. 2000;1477(1–2):122–45.

    Article  CAS  Google Scholar 

  44. Ishiyama K, Inoue E, Yamaya T, Takahashi H. Gln49 and Ser174 residues play critical roles in determining the catalytic efficiencies of plant glutamine synthetase. Plant Cell Physiol. 2006;47(2):299–303.

    Article  CAS  PubMed  Google Scholar 

  45. Chen ZJ, Sreedasyam A, Ando A, Song QX, De Santiago LM, Hulse-Kemp AM, Ding MQ, Ye WX, Kirkbride RC. Jenkins J et al: Genomic diversifications of five Gossypium allopolyploid species and their impact on cotton improvement. Nat Genet. 2020;52(5):525-+.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hirel B, Le Gouis J, Ney B, Gallais A. The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches. J Exp Bot. 2007;58(9):2369–87.

    Article  CAS  PubMed  Google Scholar 

  47. Miao GH, Hirel B, Marsolier MC, Ridge RW, Verma DP. Ammonia-regulated expression of a soybean gene encoding cytosolic glutamine synthetase in transgenic Lotus corniculatus. Plant Cell. 1991;3(1):11–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Teixeira J, Pereira S. High salinity and drought act on an organ-dependent manner on potato glutamine synthetase expression and accumulation. Environ Exp Bot. 2007;60(1):121–6.

    Article  CAS  Google Scholar 

  49. Imagawa M. Negative regulation of gene expression in eukaryotes. Neurochem Int. 1996;29(6):565–72.

    Article  CAS  PubMed  Google Scholar 

  50. Soltis PS, Marchant DB, Van de Peer Y, Soltis DE. Polyploidy and genome evolution in plants. Curr Opin Genet Dev. 2015;35:119–25.

    Article  CAS  PubMed  Google Scholar 

  51. Paterson AH, Wendel JF, Gundlach H, Guo H, Jenkins J, Jin DC, Llewellyn D, Showmaker KC, Shu SQ. Udall J et al: Repeated polyploidization of Gossypium genomes and the evolution of spinnable cotton fibres. Nature. 2012;492(7429):423-+.

    Article  CAS  PubMed  Google Scholar 

  52. Lynch M, Conery JS. The evolutionary fate and consequences of duplicate genes. Science. 2000;290(5494):1151–5.

    Article  CAS  PubMed  Google Scholar 

  53. Roulin A, Auer PL, Libault M, Schlueter J, Farmer A, May G, Stacey G, Doerge RW, Jackson SA. The fate of duplicated genes in a polyploid plant genome. Plant J. 2013;73(1):143–53.

    Article  CAS  PubMed  Google Scholar 

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We are thankful to all the staff of Cotton Research Institute for their valuable assistance in maintaining the experiments.


This work is supported by the National Engineering Research Center of Cotton Biology Breeding and Industrial Technology /Institute of Cotton Research of CAAS (No. NERC010109). In addition, this research was co-funded by the National Key Laboratory of Cotton Bio-breeding and Integrated Utilization (No. CB2023C07).

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X.L: Conceptualization, Methodology, Software, Writing – original draft. Y.G: Methodology, Software. M.K: Investigation. N.M: Data curation. X.R.W: Software, Visualization. H.G: Methodology, Software. T.L: Visualization, Investigation. Q.W: Visualization, Investigation. X.W: Data curation. S.R: Data curation. A.I.: Methodology, Investigation. X.Z.: Resources, Validation, Project administration. M.S.: Supervision, Project administration, Resources. Q.D.: Conceptualization, Methodology, Supervision, Writing—review & editing. All authors reviewed the manuscript.

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Li, X., Gu, Y., Kayoumu, M. et al. Systematic characterization of Gossypium GLN family genes reveals a potential function of GhGLN1.1a regulates nitrogen use efficiency in cotton. BMC Plant Biol 24, 313 (2024).

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