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Article

Morphological and Transcriptomic Analyses Provide New Insights into Linseed (Linum usitatissimum L.) Seedling Roots Response to Nitrogen Stress

by
Braulio J. Soto-Cerda
1,2,3,*,
Giovanni Larama
4,5,
Bourlaye Fofana
6,* and
Izsavo Soto
1,3
1
Departamento de Ciencias Agropecuarias y Acuícolas, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile
2
Núcleo de Investigación en Producción Alimentaria, Facultad de Recursos Naturales, Universidad Católica de Temuco, Rudecindo Ortega 02950, Temuco 4781312, Chile
3
ANID—Millennium Nucleus in Data Science for Plant Resilience (PhytoLearning), Santiago 8370186, Chile
4
Genomics and Bioinformatics Unit, Scientific and Technological Bioresource Nucleus, Universidad de La Frontera, Temuco 4811230, Chile
5
Biocontrol Research Laboratory, Universidad de La Frontera, Temuco 4811230, Chile
6
Charlottetown Research and Development Centre, Agriculture and Agri-Food Canada, 440 University Avenue, Charlottetown, PE C1A 4N6, Canada
*
Authors to whom correspondence should be addressed.
Plants 2025, 14(18), 2920; https://doi.org/10.3390/plants14182920
Submission received: 16 June 2025 / Revised: 29 August 2025 / Accepted: 17 September 2025 / Published: 19 September 2025
(This article belongs to the Special Issue Genetic Analysis of Plant Adaptation to Abiotic Stresses)
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Abstract

Nitrogen (N) is the most important macro-nutrient for plant growth and development, which not only results in the highest cost in crop production but may also lead to environmental pollution. Hence, there is a need to develop N and use efficient genotypes, a prerequisite for which is a better understanding of N stress adaptation. Here, responses of two contrasting linseed accessions at the seedling stage were assessed for N stress-induced changes in twelve phenotypic traits and for gene expression profiling in the roots. The results showed that nine out of twelve phenotypic traits were affected under N stress conditions, and include total root length (TRL), root tips (RT), shoot dry weight (SDW), root dry weight (RDW), root-to-shoot ratio (R/S), plant nitrogen content (PNC), shoot nitrogen content (SNC), root nitrogen content (RNC), and nitrogen use efficiency (NUE). For example, under N stress, the TRL, RDW, SDW, PNC, SNC, and RNC showed reductions of 7.1, 7.6, 16.0, 43.7, 43.3, and 38.7%, respectively. The N-efficient (NE) genotype outperformed the N-inefficient (NI) genotype for all root and shoot traits and NUE under N stress and N normal conditions. Transcriptome analysis identified 1034 differentially expressed genes (DEGs) under the contrasting N conditions and uncovered the opposite responses of the two linseed genotypes to N starvation at the gene expression level. DEGs included 153 transcription factors distributed in 27 families, among which ERF, MYB, NAC, and WRKY were the most represented. In addition, DEGs involved in N absorption and transport, root development, amino acid transport, and antioxidant activity were found to be differentially expressed. The candidate genes identified in the current study are purported for their roles in N metabolism in other crops and might also play a pivotal role in N stress adaptation in linseed, and therefore could be useful for further detailed research on N stress response in linseed, paving the way toward developing N-efficient linseed cultivars with improved root system architecture.

1. Introduction

Nitrogen (N) fertilizers have played an essential role in feeding a growing global population [1]. It is estimated that around 50% of the people alive today are dependent on synthetic N fertilizers for crop production (https://ourworldindata.org/fertilizers accessed on 5 May 2025). For example, in 1965, the global nitrogen fertilizer consumption was nearly 46.3 million metric tons, and by 2021, this amount increased to 195.4 million metric tons, with N fertilizers accounting for 56% of the total fertilizer uses worldwide [2].
Although N has the highest direct impact on crop production, modern crop varieties show low nitrogen use efficiency (NUE) and can only uptake and use barely 40–50% of the applied N [3,4]. Hence, current agronomic practices are prone to an over-application of N, which not only increases the input cost for farmers but also increases greenhouse gas emissions, soil acidification, and water eutrophication [5]. Therefore, it has become of strategic importance to unveil and understand the molecular mechanisms of low N tolerance in plants and to breed crop varieties with improved NUE [6,7].
To evolve and overcome N-starved soil conditions, plants have developed adaptive strategies, including morphological, physiological, and molecular mechanisms [8,9,10]. Root development and root architecture plasticity are pivotal processes in N stress responses. Nitrogen deficiency promotes root growth, including root length, diameter, and volume, and lateral root length depending on soil environment and N distribution [4,6,8]. Plants also tuned their transport activity to compensate for N variations [7]. Plants uptake N from the soil mainly as nitrate (NO3−), ammonium (NH4+), or as amino acids under specific soil conditions [11]. In plants that have been deprived of nitrate for long periods of time, a constitutive high-affinity nitrate transport system was shown to be responsible for initial nitrate uptake [9]. In Arabidopsis, four families of nitrate transporters have been identified and characterized, including Nitrate Transporter 1 (NRT1) and NRT2, while Chloride Channel (CLC) and Slow Anion Channel-associated homologues (SLAC/SLAH) are involved in vacuolar nitrate storage and efflux [12]. Once NO3− is absorbed by roots in the soil, it is first reduced to nitrite (NO2−) by a cytosolic nitrate reductase (NR) and then to NH4+ by a nitrite reductase (NiR) [13]. Glutamine synthetase (GS), together with glutamate synthase (GOGAT), participates as a key enzyme in N assimilation and remobilization [13]. These root morphological and molecular adaptations to N variations are at least partially explained by changes in gene expression patterns [3,7,14].
Linseed (Linum usitatissimum L.) is grown worldwide as a source of high-quality oil and functional dietary metabolites, including alpha linolenic acid (55–60%), proteins (18–25%), mucilage (1–10%), cyclolinopeptides (189–303 µg/g of oil), and, in particular, secoisolariciresinol diglucoside (SDG, 294–700 mg/100 g of seeds) and lignans [15,16,17], that have proven beneficial effects on coronary heart disease, prostate cancer, hormonal disorder, and atherosclerosis [18,19,20]. The presence of such a wide range of biomolecules in linseed ensures a high nutritional profile as an oilseed crop, while other linseed components have been utilized for the development of food additives because of their unique functional properties [21]. These attributes make linseed a multipurpose and cash crop [22]. However, achieving higher linseed yield potential is hindered under the current climatic fluctuations due to the exacerbated negative effects caused by biotic and abiotic stresses.
Currently, nutrient management practices are key to maximizing yield in linseed, and reducing environmental pollution is a highly sought-after target. High-yielding linseed production is achieved with up to 200 kg N ha−1, accounting for 40–55% of its total production costs [23]. Therefore, increasing linseed NUE is likely to be the key strategy for reducing production costs and environmental footprint while enhancing its profitability within the rotation cycle. However, linseed adaptation to N stress is not currently well studied and understood.
In recent years, transcriptome profiling using next-generation sequencing technologies has been used to study gene transcription and transcriptional regulation at the overall plant’s level under various abiotic stresses [3,24,25]. RNA sequencing (RNA-seq) is a highly sensitive and powerful transcriptomic tool for the identification of differentially expressed genes (DEGs) [3,7]. In Oryza sativa, RNA-seq of root tissues under low N conditions has identified 2937 and 10,427 DEGs between N-contrasting genotypes [3,26]. In Indian wheat genotypes (Triticum aestivum), 903 and 63 root-specific DEGs were identified in the N-efficient and N-inefficient genotypes, respectively [14,27]. In root tissues of diverse genotypes of Zea mays, 4510 and 1908 DEGs have been reported under low N conditions [7,28]. In oil crops such as Brassica napus, 1184 and 12,900 root-specific DEGs have been reported in N-deficient treatments, and some of them have co-located with N stress quantitative trait loci [6,29]. These studies revealed common DEGs between species involved in N uptake, N assimilation, and metabolism, as well as common transcription factor families such as Myeloblastosis (MYB), WRKY, DNA binding with One Finger 1 (DOF1), and APETALA2/Ethylene Responsive Factor (AP2/ERF), showing that RNA-seq is a suitable genomic tool to unveil key genes and key gene networks modulating N stress responses in plants [3,6,7,14,26,27,28,29].
Currently, seven L. usitatissimum genome assemblies are available in the databases (National Center for Biotechnology Information and Zenodo) [30,31,32,33,34,35,36] and have paved the way for accelerated development of omics tools for the potential application of genomic-assisted breeding. For example, RNA-seq technology has been applied in linseed to understand the differential gene expression patterns and for the discovery of key genes/gene networks involved in disease resistance [37,38], drought, aluminum, and salinity stresses [24,39,40], seed quality traits [41,42], stem fiber development [43], agronomic traits [44], and plant morphotypes [45]. However, RNA-seq technology has not been used to elucidate the molecular responses of roots to nitrogen stress in linseed.
The objectives of this present study were to characterize the root and shoot morphological changes induced by N stress at the seedling stage in two linseed genotypes contrasting with NUE and to identify differentially expressed genes associated with root responses under starved and normal N conditions using transcriptome sequencing and data analysis. Our results potentially will provide genetic and molecular resources to improve NUE in linseed.

2. Results

2.1. Phenotypic Performance of Linseed Genotypes

Under N stress (N-) conditions TRL, RDW, SDW, PNC, SNC, and RNC showed reductions of 7.1, 7.6, 16.0, 43.7, 43.3, and 38.7% (p < 0.05) (Table 1, Figure 1), respectively, while RT, R/S, and NUE increased significantly in both genotypes by 8.7, 11.8, and 53.5% (p < 0.05). The TRL of the nitrogen-efficient (NE) genotype was longer by 10% when it was grown under N-, whereas the nitrogen-inefficient (NI) genotype could not sufficiently expand its root system under N stress condition showing a shorter TRL by 17.8% (Table 2). Under N normal (N+) conditions, the values of the root and shoot traits of the NE genotype were smaller than the trait values under N-, while the NI accession showed the opposite pattern with higher trait values for most of the traits, such as TRL, SDW, and RDW (Figure 1, Table 2). The N content in root and shoot tissues was higher in the NI accession compared to the NE genotype under both N+ and N- conditions, whereas the NE genotype had 224% and 184% higher NUE under N+ and N-, respectively, as compared to the NI accession (Table 2). Hence, under N- conditions, it was found that the NE accession accumulates higher shoot and root biomass and can significantly expand its root system by optimizing N use (Figure 2).

2.2. Transcriptome Analysis

A total of 16 libraries, representing two genotypes, two treatments, and four biological replicates, were sequenced on the Illumina NovaSeq 6000 platform using 150 bp paired-end read mode, yielding 411,296,419 raw reads. After removing low-quality reads with Trimmomatic, 19.59 to 33.15 million high-quality reads per sample were obtained. Of the total clean reads from the 16 samples, 90.25% to 92.63% were successfully mapped to the Linum usitatissimum reference genome [30] (Table 3).
Root transcriptome differences between NE and NI genotypes after 14 days of N treatments were determined by performing comparisons between the aligned reads of N- and N+ conditions. A total of 1034 differentially expressed genes (DEGs) were identified, of which 66 and 42 were up- and downregulated in the NE genotype, respectively, whereas the NI genotype showed 285 and 702 up- and downregulated DEGs, respectively (Figure 3). Among the up- and downregulated DEGs, 33 and 29 were common for both linseed genotypes, correspondingly.
KEGG enrichment analysis of the NI genotype revealed 104 and 223 significantly enriched pathways associated with the up- and downregulated genes, correspondingly. Among the most enriched pathways, metabolic pathways (map01100), biosynthesis of secondary metabolites (map01110), plant–pathogen interaction (map04626), MAPK signaling pathway–plant (map04016), plant hormone signal transduction (map04075), diterpenoid biosynthesis including gibberellin biosynthesis (map00904), and nitrogen metabolism (map00910) were more represented among the upregulated DEGs (Figure 4A). The KEGG metabolic pathways (map01100), biosynthesis of secondary metabolites (map01110), MAPK signaling pathway–plant (map04016), plant–pathogen interaction (map04626), plant hormone signal transduction (map04075), microbial metabolism in diverse environments (map01120), and starch and sucrose metabolism (map00500) were more represented among the downregulated DEGs (Figure 4B). KEGG enrichment analysis of the NE genotype revealed 12 and 38 significantly enriched pathways associated with the up- and downregulated genes, respectively. The most enriched pathways among the upregulated DEGs were biosynthesis of secondary metabolites (map01110), MAPK signaling pathway–plant (map04016), plant hormone signal transduction (map04075), metabolic pathways (map01100), and biosynthesis of cofactors (map01240) (Figure 4C). Similarly, the KEGG metabolic pathways (map01100), plant–pathogen interaction (map04626), biosynthesis of secondary metabolites (map01110), plant hormone signal transduction (map04075), and nitrogen metabolism (map00910) were the most represented categories among the downregulated DEGs (Figure 4D). Among the top KEGG categories, biosynthesis of cofactors (map01240) and nitrogen metabolism (map00910) were specific for the NE genotype.
Among the 1034 genes differentially expressed, 153 corresponded to transcription factors (TFs) grouped into 27 TF families. In total, 99 TFs were found upregulated and 54 downregulated (Supplementary Tables S1 and S3). The NE accession showed 4 and 7 up- and downregulated TFs, respectively, while the NI genotype showed 86 and 40 up- and downregulated TFs, respectively. The two genotypes showed 9 and 7 common up- and downregulated TFs for NE and NI, respectively. Among the 27 TF families, ERF (n = 43), MYB (n = 16), NAC (n = 15), and WRKY (n = 14) were the most represented. Among the upregulated TFs, the majority belonged to the ERF (n = 28), NAC (n = 11), and WRKY (n = 10) families. The TF-encoding genes involved in root development included ERF12 (Lus10003740), ERF13 (Lus10016210), ERF71 (Lus10003601), MYB73 (Lus10010055), MYB77 (Lus10010238), NAC021 (Lus10024908), and WRKY75 (Lus10011346) (Supplementary Figures S1 and S2; Supplementary Table S3). Sixteen transcription factors involved in abiotic stress responses through the abscisic acid and ethylene signaling pathways, including bZIP29 (Lus10024314), ZAT9 (Lus10004724), AZF2 (Lus10032848), and C3H29 (Lus10028970), were identified.
The identified DEGs involved in N metabolism include nitrate regulatory gene2 (NRG2, Lus10029683) and NITRATE TRANSPORTER1/PEPTIDE TRANSPORTER3.1 (NPF3.1, Lus10041466). Genes encoding nitrate transporters included NITRATE TRANSPORTER1/PEPTIDE TRANSPORTER1.1 (NPF1.1/NRT1.12, Lus10014537) and NITRATE TRANSPORTER1/PEPTIDE TRANSPORTER6.3 (NPF6.3/NRT1.1, Lus10032252). Ammonium transporters such as ammonium transporter 1 member 2 (AMT1;2, Lus10004760) were also induced along with several genes involved in amino acid transporters, including gamma-glutamyl cyclotransferase 2.1 (GGCT2.1, Lus10020181) and amino acid permease BAT1 (BAT1, Lus10029533), also showed differential expression patterns (Supplementary Figure S2, Supplementary Table S2). A high percentage of the DEGs (71%) were downregulated in the root transcriptome of the NI genotype, in agreement with its poor capacity to use the absorbed N and generate higher biomass and NUE as observed in the NE genotype (Table 2, Supplementary Figures S1 and S2).

3. Discussion

Linseed is one of the founder crops in agriculture and has provided high-quality oil, antioxidants, and natural fiber to human civilization for more than 10,000 years [46]. However, linseed production is constrained by low yield under limited N conditions [47]. Therefore, high N inputs are common practices to make this crop competitive at the expense of farmers’ profits and leading to environmental pollution [47]. Up to date, little is known about the phenotypic and molecular responses induced by N stress in linseed roots, which is a prerequisite for designing high-NUE linseed cultivars with appropriate root system architecture (RSA). In recent years, crop breeders have focused on improving RSA because of its importance in water and nutrient acquisition, which is predicted to lead to a new green revolution in crop production. Here, using two contrasting linseed accessions, we evaluated 12 traits, including shoot, RSA, and N content traits under N- and N+ conditions at the seedling stage, and combined an RNA-seq strategy to decipher the linseed N stress responses at the gene expression level.
Under N stress, the NI genotype showed reduced TRL, SDW, RDW, PNC, and SNC, while the NE accession showed increased TRL, SDW, and RDW, but lower levels of N in PNC, SNC, and RNC. These results are in agreement with previous studies in rice, maize, and rapeseed [6,7,48], where higher TRL and RDW and lower N content were reported in aerial and root tissues of N-efficient plants, indicating their higher ability to transport carbon to promote root development and efficient N absorption, transport, and use to construct new biomass and, hence, a higher NUE. The developmental plasticity of the RSA is crucial for the adaptation of crops to unfavorable environments with a limited supply of N. In rice and maize, root growth is influenced in a dose-dependent manner by N and the phytohormone cytokinin, where low N promotes the degradation of cytokinin for rapid root growth [6,7]. Therefore, factors that control RSA plasticity under N stress can vary greatly depending on N dosage, growth stage, duration of the experiment, and parameters evaluated. In linseed, an orphan oil crop, such studies, including phenotypic, physiological, metabolic, and molecular evaluations for N stress, need to be realized, and, in general, little progress has been achieved to elucidate the mechanisms of abiotic stress responses in linseed [24,41,49,50,51]. Because the NE genotype showed superior growth stability under both N conditions, this could translate into superior yield stability, which is one of the main goals in plant breeding. However, field trials need to be carried out to validate this hypothesis.
Transcriptome analysis is a robust approach for the identification of differentially expressed genes and their regulatory mechanisms under specific environmental conditions and development stages. Between 2020 and 2025, more than 2460 research articles related to the “crop transcriptome analysis under stress” term have been published in PubMed (https://pubmed.ncbi.nlm.nih.gov/ accessed on 10 May 2025), including those focused on linseed [24,41,49,50,51].
This present study identified 1034 root-specific DEGs in two linseed genotypes contrasting for NUE. KEGG pathway analysis showed that both linseed genotypes shared 70% of the KEGG categories for up- and downregulated DEGs. Similar KEGG results were reported for linseed genotypes contrasting for salt tolerance [52], which suggests that these metabolic pathways may play crucial roles as a general abiotic stress response mechanism. For example, tryptophan metabolism is involved in plant responses to N stress, and this aromatic amino acid has been reported to regulate root growth and enhance tolerance to low N conditions [53]. In wheat, TRYPTOPHAN AMINOTRANSFERASE RELATED 2 (TaTAR2) gene functions in the tryptophan-dependent pathway of auxin biosynthesis and is expressed mainly in roots and is upregulated by low N availability [52]. Under low N, TaTAR2 modulates lateral root branching, lateral root number, and primary root length [52]. Here, TAR4 (Lus10028695) was found upregulated in the roots of the NI genotype and may play a similar role as TaTAR2 in root development. MAPK signaling pathways are involved in plant stress responses, including nitrogen deficiency, drought, and heavy metal stress, and the inhibition of MAPK signaling increases the effects of nitrogen deficiency on cell wall regeneration and mortality due to reduced expression of antioxidant enzymes [54]. In linseed, reports of MAPK signaling pathway-associated genes regulated under abiotic stresses are limited. Two genes, Lus10012962 and Lus10001832, both orthologs of the Arabidopsis ABSCISIC ACID INSENSITIVE 1 (ABI1), were induced under drought stress only in the sensitive genotype, and both regulate ABA responses, such as stomatal closure and osmotic water permeability of the plasma membrane [52]. Hence, TAR4 (Lus10028695) could be a novel, interesting gene to explore its variant in flax germplasm and its association with different RSA phenotypes.
In Arabidopsis, vegetative storage proteins (VSPs) play a role as temporary nitrogen storage proteins and regulate responses to copper stress through the MAPK signaling pathway [55]. Our root transcriptome analysis revealed that genes Lus10011774 and Lus10017060 encoding VSPs were up- and downregulated, respectively, in the NI genotype but unaltered in NE, which could partially explain NI’s inability to cope with oxidative stress caused by low N availability. Nowadays, VSPs are capturing more attention due to their role in abiotic stress responses. For instance, in maize, the overexpression of the VSP ZmLOC6, annotated as a lipoxygenase, improves drought tolerance and yield [56]. Similarly, in white clover (Trifolium repens) cultivated under drought stress, the VSP encoding for a lipid transfer protein was upregulated and associated with drought tolerance [57].
The phenylpropanoid biosynthesis pathway is known to be activated in response to oxidative stress, triggered by drought, heat, heavy metals, and nitrogen deficiency, and produces secondary metabolites that help plants to cope with stress [58]. In Petunia hybrida (petunia), isoeugenol, a floral volatile secondary metabolite, protects plants against abiotic stresses like drought, and it is synthesized by the coniferyl alcohol acyltransferase (CFAT) enzyme [58]. CFAT catalyzes the conversion of coniferyl alcohol into coniferyl acetate, and it plays a role in stress defense and metabolic homeostasis [58]. In linseed, Lus10033327, the ortholog of the petunia CFAT gene, was upregulated in the NI genotype and remained unaltered in the NE accession. In Vitis vinifera, genes related to phenylpropanoid metabolism have been found to be less induced and/or more repressed in drought-sensitive rootstocks [59]. The expression patterns of DEGs involved in these pathways are in line with the phenotypic changes observed in the NI genotype while the NE accession showed unaltered patterns of expression, suggesting that NE can better tolerate N stress conditions by modifying its plant architecture, and more specifically, the RSA through the upregulation of pathways involved in antioxidant defense and N metabolism, storage, and reutilization. To our knowledge, however, DEGs and metabolic pathways induced by N stress have not yet been established in linseed, and this research provides the first insight into this complex polygenic trait.
Interestingly, one of the KEGG categories downregulated under N- in both linseed genotypes was plant–pathogen interaction. Plant defense is an active and energetically costly response mechanism, and the metabolic state of the plant plays a fundamental role in the outcome of the plant–pathogen interaction. Therefore, under nitrogen stress, plants activate specific defense-related genes to cope with the nutrient deficiency and potential pathogen attacks [60,61]. However, the up- or downregulation of defense-related genes is species and genotype dependent. In tomato (Solanum lycopersicum), the defense response to the necrotrophic fungus Botrytis cinerea was reduced with higher susceptibility in nitrate-limiting conditions [61]. Similarly, in Australian bread wheat cultivars, one of the top downregulated KEGG categories in N- was plant defense [60], and nitric oxide (NO) seems to work as a signaling molecule in plant immune response, defense-related gene expression, and the hypersensitive response mechanism. Our results are in line with the growing evidence that supports crosstalk mechanisms between pathogen defense response and N status in plants [60,61].
Transcription factors are essential for the regulation of gene expression and act as a convergence point for crosstalk of abiotic and biotic stress responses [62]. Notably, certain transcription factors have shown the ability to modulate plant tolerance to a spectrum of abiotic and biotic stresses and include NAC, MYB, WRKY, bHLH, and ERF/DREB [62]. The linseed genome contains 2481 TFs classified into 57 families, with the most represented being MYB (206), bHLH (195), ERF (193), and NAC (191) (https://planttfdb.gao-lab.org/index.php?sp=Lus accessed on 17 April 2025). The MYB family of TFs is one of the largest families in plants and is involved in ABA signaling, which plays an important role in regulating the transcription of genes responsive to drought stress [3]. Root transcriptome analysis of 20 diverse flax accessions under drought stress identified 434 MYB family members involved in root development, starch degradation, stomatal closure, and other biological functions [63]. This study revealed that different cultivars harbored different numbers and combinations of MYB TFs, which affected their level of drought tolerance. For instance, MYB93 was highlighted because it modulates lateral root development and was upregulated among the drought-tolerant flax genotypes [63]. However, the MYB2 and MYB73 TFs identified in our study were not found in the roots of the 20 flax genotypes; hence, it can be speculated that these MYB TFs might be specifically induced in response to N stress. In our study, various MYB TFs were involved in root development under N stress, such as MYB2 (Lus10037818), and were found here upregulated in the NE genotype. In rice, MYB2 of the ABA signaling pathway mediates the expression of the gene encoding the AAT aromatic and neutral AAT 1 (ANT1), which positively regulates root growth and salt tolerance [64]. In Arabidopsis, MYB73 regulates auxin responses and lateral root development under UV-B stress [65], and linseed MYB73 (Lus10010055) was found to be expressed in the NI linseed accession under N- conditions.
APETALA2/ethylene-responsive element (AP2/ERF) binding factors are critical for regulating plant responses to abiotic stress and plant development, including root initiation and development, leaf size, floral patterning, floral meristem establishment, and seed development (reviewed by [66]). The Arabidopsis ERF13 TF modulates lateral root development by inhibiting the expression of 3-ketoacyl-CoA synthase16 (KCS16) encoding a fatty acid elongase which is involved in very-long-chain fatty acid (VLCFA) biosynthesis [67]. Transcriptome analysis identified many ERF TF-encoding genes including ERF12 (Lus10003740), ERF13 (Lus10016210), and ERF71 (Lus10003601) [65]. For instance, ERF12 (Lus10003740), ERF13 (Lus10016210) were upregulated in the NI genotype, while ERF71 (Lus10003601) was downregulated under N stress. These three ERF TFs have all been reported to be involved in root development through different mechanisms [67], and could contribute to shape the differences in RSA phenotypes observed between linseed genotypes.
The WRKY TF family is known for its involvement in various stress responses, including drought and nitrogen signaling [68]. In Arabidopsis, WRKY1 TF has been shown to mediate transcriptional regulation in response to light and nitrogen signals [69]. Loss of WRKY1 function affects genes involved in nitrogen uptake and assimilation and light energy resources, suggesting its role in integrating various environmental cues to optimize nitrogen metabolism [69]. Diverse studies have been conducted on the WRKY TF family [70,71]. For example, WRKY15 (Lus10006261), WRKY33 (Lus10001265), and WRKY40 (Lus10002309) were expressed under saline–alkaline stress [70]. Under polyethylene glycol (PEG) treatment, the expression of WRKY40 in flax seedlings increased, which helped flax plants to decrease the adverse effects of drought stress [70]. The orthologous genes of Arabidopsis WRKY46 (Lus10012870), WRKY54 (Lus10012870), and WRKY70 (Lus10030517) are related to the osmotic resistance of flax. Moreover, when flax grew under unbalanced nutrient conditions, WRKY33, WRKY40, and WRKY70 were significantly expressed, and it was considered that WRKY TFs are also involved in the nutritional stress response of flax [71]. Similarly, the gene Lus10011346, the ortholog of Arabidopsis WRKY75 TF, is known to regulate nutrient starvation responses and lateral root development [68] and was found here with a reduced expression in the NI genotype but unaltered in the NE genotype. Overall, WRKY TFs are interesting multifunction targets to deepen research on their role in flax response to abiotic stresses.
The NAC family comprises numerous members implicated in developmental processes and stress responses [72]. In Arabidopsis, NAC056 is mainly expressed in the root system and promotes nitrate assimilation and lateral root development under N deficiency [72]. Lus10024908, the ortholog of the Arabidopsis NAC021, mediates auxin signal downstream of TIR1 to promote lateral root development, where its overexpression results in a higher number and longer lateral roots than the wild type [73]. Like our study, in rice and perennial ryegrass, the same TF families (MYB, ERF, WRKY, and NAC) were reported as the most represented under different levels of N, suggesting that these TFs play a crucial role in the transcriptional regulation in response to nitrogen [3,74]. Understanding the functions of these TFs provides valuable insights into the complex regulatory networks governing NUE and could be potential targets for genetic improvement of crops. Here, our study shows that TFs like MYB73, ERF13, WRKY75, and NAC021 are involved in the main responses to N stress (root development, N absorption, and transport), and deciphering their allelic variation could be useful to enhance NUE in linseed germplasm.
Understanding the mechanisms of nitrate uptake from the soil and distribution through the plant is an important step on the way to improving plant growth and productivity [75]. In Arabidopsis, high affinity nitrate transporter 2.5 (NRT2.5) is predominantly expressed in the epidermis and the cortex of roots at the root hair zone of nitrate-deprived plants, and collectively with NRT2.1, NRT2.2, and NRT2.4, it ensures the efficient uptake of nitrate [75]. The NRT2.5 (Lus10030902) was found upregulated in the root system of both linseed genotypes under N-deprived conditions. In line with the important role of nitrate transporters, Lus10041466, the ortholog of rice NPF3.1, a member of the NRT1/PTR family, causes superior NUE in cultivated rice compared to wild germplasm [76], and in our study its expression was unaltered in NE and downregulated in NI under N limited conditions.
Plants absorb two primary inorganic N forms, nitrate and ammonium, from the soil [77,78]. In Arabidopsis, there are three functional ammonium transporters (AMT1-1, AMT1-2, and AMT1-3) for constitutive, diurnally regulated, and starvation-induced uptake of ammonium into roots [77]. Here, Lus10004760, the ortholog of Arabidopsis AMT1-2, showed 5.5-fold higher expression under N- in the roots of both linseed genotypes as compared to the N+ condition, suggesting that linseed may have a preferential uptake of the reduced nitrogen form as observed in Arabidopsis [77].
When nitrogen becomes scarce in the soil, plants can absorb amino acids as a source of N [79]. Various genes involved in amino acid transport showed differential expression patterns. These genes include gamma-glutamyl cyclotransferase 2.1 (GGCT2.1, Lus10020181), amino acid transporter AAP3 (AAP3, Lus10042740), and cationic amino acid transporter 8 (CAT8, Lus10005574). GGCT2.1 catalyzes the formation of 5-oxoproline from gamma-glutamyl dipeptides and plays a significant role in glutathione (GSH) homeostasis [78]. AAP3 shows high affinity transport of cationic amino acids with a broad specificity for GABA and tryptophan and is exclusively expressed in roots [79]. CAT8, along with CAT3 and CAT6, is involved in the transport of cationic, neutral, or acidic amino acids, and CAT8 is preferentially expressed in young tissues such as leaves and root apical meristem [80]. Therefore, these three amino acid transporters found differentially expressed in our study could influence the allocation of the amino acids glutamine and glutamic acid to root and shoot meristems as precursors for the synthesis of other amino acids under N starvation in linseed, as previously reported in plant species like Arabidopsis and V. vivifera [80].
Taken together, the root transcriptome analysis provided a valuable catalog of DEGs, allowing a better understanding of the association between the observed phenotypic changes in roots and altered candidate gene expression patterns under contrasting N conditions in the two contrasting linseed genotypes, as also reported in Brassica juncea [81], Solanum tuberosum [82], Brassica napus [6], and Glycine max [83]. This study also uncovered the opposite responses of the NE and NI genotypes to N starvation. This might be explained by their extreme contrasting phenotypes, where NE showed 2.8-fold higher NUE than NI as well as superior root traits. These results highlight the importance of exploring broad genetic diversity in germplasms to select contrasting genotypes for molecular genetic studies.

4. Materials and Methods

4.1. Plant Material and Phenotyping

Two linseed accessions, O_IRL_C_CN98192 and O_IND_C_CN98982, were used in this study. These lines were selected based on a previous screening carried out in our laboratory in August 2023 using the same methodology described below to maintain equivalence and representativeness of results between experiments and included 150 diverse flax accessions from the Canadian flax core collection [84]. Hence, O_IRL_C_CN98192 was identified as N-efficient (NE), while O_IND_C_CN98982 was found to be N-inefficient (NI). During springtime in September 2024, one hundred seeds of each genotype were surface-sterilized with 70% ethanol for 2 min and then washed four times in distilled water. Subsequently, the seeds were germinated in wet germination paper in an artificial climate incubator at 24 °C for 72 h in the dark. Two uniform 7-day-old seedlings were transplanted into pots (648 cm3) filled with sterile sifted silver sand. Seedlings were watered daily with 30 mL of modified Hoagland’s nutrient solution. Briefly, the nutrient solution contained 2.5 mM K2SO4, 2 mM MgSO4, 1 mM KH2PO4, 1 mL L−1 Hoagland micronutrients, and 2 mL L−1 FeEDTA solution [78]. Two treatments were evaluated with nitrate added to the solution in the form of 500 mM Ca(NO3)2 to obtain NO−3 final concentrations of 2.5 mM, referred to as nitrogen normal (N+), or not (0 mM N), referred to as nitrogen stress (N-). To maintain permeability and functions of the cell membrane, Ca2+ concentration was adjusted to the same values in both N treatments by adding 0.9 mM CaSO4 to the N- treatment. Pots were moved to a greenhouse facility maintained at 18–25 °C, with an 18/6 light/dark hours and 40–50% relative humidity. The photosynthetically active radiation (PAR) was approximately 400 µmol m−2 s−1. The experiment was laid out as a completely randomized design with seven biological replicates. Three replicates were used immediately for measuring root and shoot parameters, while the remaining four were frozen in liquid nitrogen, stored at −80 °C, and later used for root RNA isolation. After 14 days, pots were immersed in water to loosen the soil and release the roots. Roots were washed manually to carefully remove the sand that was not removed by water. The seedlings of both N treatments and genotypes were collected and separated into root and shoot sections.
Root samples were scanned twice in grayscale at 400 dpi using a calibrated optical scanner LA2400 (Epson 11000XL, Long Beach, CA, USA). Root images were analyzed using the WinRHIZO software v. 15 (Regent Instruments, Montreal, QC, Canada), and the mean of the two images per sample was used to determine total root length (TRL; cm), root volume (RV; cm3), root diameter (RD; mm), and root tips (RT). Thereafter, plant tissues (roots and shoots) were placed in an oven at 60 °C for two days, after which plant dry weight (PDW; mg), root dry weight (RDW; mg), and shoot dry weight (SDW; mg) were determined, and the root/shoot ratio calculated. Shoot and root N contents were determined using the Dumas combustion method in a Gerhardt DUMATHERM® N Pro analyzer (Gerhardt Analytical Systems, Königswinter, KG, Germany) as described by [85] and used to calculate the nitrogen use efficiency (NUE) of each genotype using the formula: Plant dry weight (mg)/Plant N content (mg).

4.2. Statistical Analysis of Phenotypic Data

Statistical differences between treatments, genotypes, and genotype x treatment interactions for shoot and root traits were analyzed using a Restricted Maximum Likelihood (REML) analysis implemented in GenStat v.18 [86] at a significance of p < 0.05. Best linear unbiased estimates (BLUEs) were obtained for each trait under both N treatments.

4.3. Isolation of Total RNA, Illumina Sequencing and Mapping of Reads

Total RNA was extracted from the root tissue of each of the 16 biological sample units obtained from the previous N stress experiment in silver sand. Hence, four out of the seven biological replicates were collected per genotype (n = 2) and treatment (n = 2), totaling 16 experimental units laid out as a completely randomized design using the Spectrum Plant Total RNA kit (Sigma-Aldrich, St. Louis, MO, USA). RNA was DNase-treated, and its integrity was examined on a 1% (w/v) agarose gel (Invitrogen, CA, USA). RNA yield and quality were determined using a Nanodrop spectrophotometer (Thermo Scientific, Madison, WI, USA), and RNA QC for all samples was ensured by RNA integrity number (RIN) ≥ 7.0 using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The 16 RNA libraries were constructed by outsourcing to Novogene Corporation Inc. and paired-end sequenced using a NovaSeq 6000 platform (Illumina, Inc, San Diego, CA, USA) through 150 cycles. The raw RNA-seq data were deposited in the NCBI Sequence Read Archive under the bioproject PRJNA921700 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA921700 accessed on 7 January 2023).
The raw sequences were assessed for quality using FastQC [87]. Adaptor clipping and quality trimming of raw reads were performed using Trimmomatic [88]. Low quality reads with a Phred score < 30 and read length < 50 bp were removed. The high-quality transcriptome reads were mapped to the flax reference genome [30] using HISAT2 [89]. The statistical differences in gene expression were assessed with the R package DESeq2 v- 1.48 [90] with the threshold set as |log2(Fold change)| ≥ 1 and false discovery rate (FDR)-adjusted p value < 0.05.

4.4. Functional Annotation and Identification of Transcription Factors

Functional annotation of the DEGs was carried out against the curated KEGG GENES database using the KEGG Automatic Annotation Server (KAAS, https://www.genome.jp/kegg/ accessed on 10 May 2025). KEGG Orthologs (KO) were assigned using the KofamKOALA software [91] (https://www.genome.jp/tools/kofamkoala/ accessed on 10 May 2025).
To determine the biological significance of the DEGs, L. usitatissimum genes were annotated by BLASTP against the SwissProt database using the threshold criteria of identity ≥ 50%, sequence coverage ≥ 70%, and E-value ≤ 1 × 10−10. Transcription factors among DEGs were identified using the PlantTFDB database v. 5.0 (https://planttfdb.gao-lab.org/ accessed on 17 April 2025). The functional roles of DEGs were further examined by searching literature reports for their functional characterization in other plant species.

5. Conclusions

In the present study, under N- conditions, the NE accession produced higher shoot and root biomass and significantly expanded its root system through optimized N use, suggesting that NE can better tolerate N stress conditions by modifying its RSA. These phenotypic changes were reflected by gene transcriptomic changes in genes associated with N absorption and transport, root development, and antioxidant response, uncovering the opposite response of the two linseed genotypes to N starvation at the gene expression level. The 1034 DEGs under contrasting N conditions and the 153 transcription factors identified in this study would be useful resources to characterize allele variants and their association with root phenotypes in diverse linseed germplasm and wild relatives. The gene expression study focused on RNAseq; further studies using qPCR on key candidate genes would provide more confirmation of the transcriptional changes between the two genotypes under N stress. Nonetheless, the current data are the first reported in linseed and will serve as a baseline for elucidating the contribution of these candidate genes in linseed NUE, root system architecture responses to N stress, and, ultimately, to a more sustainable linseed production.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/plants14182920/s1, Table S1: Transcription factor families identified in linseed DEGs under nitrogen stress. Table S2: Annotated differentially expressed genes under contrasting N conditions in linseed roots. Table S3: FPKM values of 1034 differentially expressed genes under N contrasting conditions in linseed genotypes. Figure S1: Graphics of expression patterns observed in genes associated with root development, nitrogen acquisition, nitrogen transport, and amino acid transport of linseed genotypes under N stress. Figure S2: Examples of differentially expressed genes and their roles under N- in root development, N metabolism, and amino acid transport biological processes identified in two contrasting linseed genotypes.

Author Contributions

Conceptualization, B.J.S.-C. and B.F.; Formal analysis, G.L. and I.S.; Funding acquisition, B.J.S.-C.; Writing—original draft, B.J.S.-C. and G.L.; Writing—review and editing, B.J.S.-C. and B.F. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) project No. 1200241. ANID—Millennium Science Initiative Program—NCN2024_047. Universidad Católica de Temuco acknowledges the collaboration of Agriculture and Agri-Food Canada (AAFC) and the Total Utilization Flax GENomics (TUFGEN) project formerly funded by Genome Canada and other stakeholders of the Canadian flax industry.

Data Availability Statement

The raw RNA-seq data were deposited in the NCBI under the bioproject PRJNA921700 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA921700, (accessed on 11 June 2025)).

Acknowledgments

The authors B.J.S.-C, G.L., B.F., and I.S. also acknowledge the supercomputing infrastructure of Soroban (SATREPS MACH—JPM/JSA1705) at Centro de Modelación y Computación Científica at Universidad de La Frontera.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
TRLTotal Root Length (cm)
RVRoot Volume (cm3)
RDRoot Diameter (mm)
RTRoot Tips
PDWPlant Dry Weight (mg)
SDWShoot Dry Weight (mg)
RDWRoot Dry Weight (mg)
R/SRoot-to-Shoot Ratio (%)
PNCPlant Nitrogen Content (mg)
SNCShoot Nitrogen Content (mg)
RNCRoot Nitrogen Content (mg)
NUENitrogen Use Efficiency
NENitrogen-Efficient
NINitrogen-Inefficient
DEGDifferentially Expressed Gene
KEGGKyoto Encyclopedia of Genes and Genomes
TFTranscription Factor
RSARoot System Architecture

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Plants 14 02920 g001
Figure 1. Comparison of N treatment effects on morphological traits of two linseed genotypes contrasting for NUE. NE: N-efficient genotype; NI: N-inefficient genotype. TRL: total root length (cm); RT: Root tips; SDW: shoot dry weight (mg); RDW: root dry weight (mg); R/S: root-to-shoot ratio (%); PNC: plant nitrogen content (mg); SNC: shoot nitrogen content (mg); RNC: root nitrogen content (mg); NUE: nitrogen use efficiency. * Statistically significant p < 0.05. Error bars represent the standard error of the mean. n = 3 biological replicates per genotype and treatment. ns: non-significant.
Figure 1. Comparison of N treatment effects on morphological traits of two linseed genotypes contrasting for NUE. NE: N-efficient genotype; NI: N-inefficient genotype. TRL: total root length (cm); RT: Root tips; SDW: shoot dry weight (mg); RDW: root dry weight (mg); R/S: root-to-shoot ratio (%); PNC: plant nitrogen content (mg); SNC: shoot nitrogen content (mg); RNC: root nitrogen content (mg); NUE: nitrogen use efficiency. * Statistically significant p < 0.05. Error bars represent the standard error of the mean. n = 3 biological replicates per genotype and treatment. ns: non-significant.
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Figure 2. Root architecture in contrasting genotypes with (N+) and without (N-) N application. NE: nitrogen-efficient genotype; NI: nitrogen-inefficient genotype. Vertical black line indicates 1 cm scale.
Figure 2. Root architecture in contrasting genotypes with (N+) and without (N-) N application. NE: nitrogen-efficient genotype; NI: nitrogen-inefficient genotype. Vertical black line indicates 1 cm scale.
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Figure 3. (A) Hierarchical clustering of 1034 differentially expressed genes (DEGs) identified in two N contrasting linseed genotypes, NI: nitrogen-inefficient genotype and NE: nitrogen-efficient genotype, that exhibited altered expression levels in response to N stress. The colors in the scale—blue (low), white (medium), and red (high)—represent the normalized expression levels of the DEGs. (B) Venn diagram showing overlap or genotype-specific up- or downregulated genes in response to N treatment.
Figure 3. (A) Hierarchical clustering of 1034 differentially expressed genes (DEGs) identified in two N contrasting linseed genotypes, NI: nitrogen-inefficient genotype and NE: nitrogen-efficient genotype, that exhibited altered expression levels in response to N stress. The colors in the scale—blue (low), white (medium), and red (high)—represent the normalized expression levels of the DEGs. (B) Venn diagram showing overlap or genotype-specific up- or downregulated genes in response to N treatment.
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Figure 4. KEGG pathway annotation for the DEGs identified in root tissue for the NE and NI genotypes (NE: nitrogen-efficient genotype; NI: nitrogen-inefficient genotype). (A) The twenty top KEGG enrichment pathways of upregulated DEGs in NI genotype. (B) The twenty top KEGG pathways of downregulated DEGs in the NI genotype. (C) The twelve top KEGG enrichment pathways of upregulated DEGs in the NE genotype. (D) The twenty top KEGG pathways of downregulated DEGs in the NE genotype.
Figure 4. KEGG pathway annotation for the DEGs identified in root tissue for the NE and NI genotypes (NE: nitrogen-efficient genotype; NI: nitrogen-inefficient genotype). (A) The twenty top KEGG enrichment pathways of upregulated DEGs in NI genotype. (B) The twenty top KEGG pathways of downregulated DEGs in the NI genotype. (C) The twelve top KEGG enrichment pathways of upregulated DEGs in the NE genotype. (D) The twenty top KEGG pathways of downregulated DEGs in the NE genotype.
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Table 1. Restricted maximum likelihood analysis of root and shoot traits in N contrasting linseed genotypes.
Table 1. Restricted maximum likelihood analysis of root and shoot traits in N contrasting linseed genotypes.
TraitTreatmentGenotypeTreatment × Genotype
TRL0.024<0.0010.013
RV0.315<0.0010.084
RD0.605<0.0010.713
RT0.017<0.001<0.001
PDW0.0600.0040.035
SDW0.0180.0180.019
RDW0.012<0.0010.161
R/S0.048<0.0010.572
PNC<0.001<0.001<0.001
SNC<0.001<0.001<0.001
RNC<0.001<0.0010.002
NUE0.012<0.0010.009
TRL: total root length (cm); RV: root volume (cm3); RD: root diameter (mm); RT: Root tips; PDW: plant dry weight (mg); SDW: shoot dry weight (mg); RDW: root dry weight (mg); R/S: root-to-shoot ratio (%); PNC: plant nitrogen content (mg); SNC: shoot nitrogen content (mg); RNC: root nitrogen content (mg); NUE: nitrogen use efficiency.
Table 2. Morphological measurements of linseed genotypes under N contrasting conditions.
Table 2. Morphological measurements of linseed genotypes under N contrasting conditions.
GenotypeTreatmentTRLRTR/SSDWRDWPNCSNCRNCNUE
NEN+680.86670.40128.951.84.61.90.5538.9
N-749.06970.44129.655.83.71.40.5050.2
NIN+585.22760.28128.735.413.76.10.5012.0
N-481.03190.3087.728.86.73.10.6417.7
TRL: total root length (cm); RT: Root tips; R/S: root-to-shoot ratio (%); SDW: shoot dry weight (mg); RDW: root dry weight (mg); PNC: plant nitrogen content (mg); SNC: shoot nitrogen content (mg); RNC: root nitrogen content (mg); NUE: nitrogen use efficiency. NE: N-efficient; NI: N-inefficient.
Table 3. Summary of read numbers and mapped reads from the RNA-Seq analysis.
Table 3. Summary of read numbers and mapped reads from the RNA-Seq analysis.
Sample IDRaw ReadsHQ Reads%HQNumber of Mapped Reads% Mapped
(from HQ Reads)
NE-N-(R1)26,186,61225,634,56898.0724,026,63891.75
NE-N-(R2)31,440,35730,754,94397.9829,123,04492.63
NE-N-(R3)31,591,37330,902,31397.9828,951,66891.64
NE-N-(R4)23,958,56423,444,60297.9722,092,44992.21
NE-N+(R1)30,771,04630,125,08398.0328,168,43191.54
NE-N+(R2)33,547,42132,808,87997.9630,490,53690.89
NE-N+(R3)33,866,99833,158,61098.0630,784,14590.90
NE-N+(R4)21,871,13321,448,33398.2319,980,89391.36
NI-N-(R1)22,384,87221,953,58798.2220,731,80492.62
NI-N-(R2)25,810,40725,196,53797.7923,513,53091.10
NI-N-(R3)21,399,23520,955,64798.1119,551,67091.37
NI-N-(R4)22,296,99621,870,22298.2420,458,32091.75
NI-N+(R1)21,309,01420,826,78497.8819,387,17090.98
NI-N+(R2)21,864,09221,470,86998.3619,844,81890.76
NI-N+(R3)22,994,95522,583,20898.3521,266,39592.48
NI-N+(R4)20,003,34419,599,26298.1118,052,45290.25
NE: N-efficient accession O_IRL_C_CN98192, NI: N-inefficient accession O_IND_C_CN98982. N-: zero nitrogen treatment, N+: normal nitrogen treatment. HQ: high quality.
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Soto-Cerda, B.J.; Larama, G.; Fofana, B.; Soto, I. Morphological and Transcriptomic Analyses Provide New Insights into Linseed (Linum usitatissimum L.) Seedling Roots Response to Nitrogen Stress. Plants 2025, 14, 2920. https://doi.org/10.3390/plants14182920

AMA Style

Soto-Cerda BJ, Larama G, Fofana B, Soto I. Morphological and Transcriptomic Analyses Provide New Insights into Linseed (Linum usitatissimum L.) Seedling Roots Response to Nitrogen Stress. Plants. 2025; 14(18):2920. https://doi.org/10.3390/plants14182920

Chicago/Turabian Style

Soto-Cerda, Braulio J., Giovanni Larama, Bourlaye Fofana, and Izsavo Soto. 2025. "Morphological and Transcriptomic Analyses Provide New Insights into Linseed (Linum usitatissimum L.) Seedling Roots Response to Nitrogen Stress" Plants 14, no. 18: 2920. https://doi.org/10.3390/plants14182920

APA Style

Soto-Cerda, B. J., Larama, G., Fofana, B., & Soto, I. (2025). Morphological and Transcriptomic Analyses Provide New Insights into Linseed (Linum usitatissimum L.) Seedling Roots Response to Nitrogen Stress. Plants, 14(18), 2920. https://doi.org/10.3390/plants14182920

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