Arabidopsis thaliana (ecotype Col-0) plants were transformed using the floral dip method (Clough and Bent, 1998) with Agrobacterium tumefaciens strain ‘GV3101’ harboring the 1,920 bp coding sequence of AsTIR19 from A. stenosperma cloned in the binary vector pPZP-BAR (Guimaraes et al., 2022). Transformed plants were maintained in a controlled growth chamber (21°C with a 12 h photoperiod and light intensity of 200 μmols.m⁻².s⁻¹) and T0 glufosinate-resistant and eGFP-positive transformants were selected to produce the T1 generation. Transformants were screened repeatedly for glufosinate ammonium herbicide resistance to obtain homozygous AsTIR19 overexpressing (OE) lines, at the T2 generation, as described previously (Vinson et al., 2020). The transgenic status of OE-lines was confirmed by the presence of the selection marker gene bar in glufosinate-resistant seedlings at T1 generation by PCR analysis, with the relative expression of the AsTIR19 transgene further determined in OE lines at T2 generation by qRT-PCR analysis, as described below, using specific primers ( Supplementary Table S1 ). To assess the germination rate of the AsTIR19-OE seeds, T2 seeds were sown in 80 mL pots containing soil substrate (Carolina Soil, CSC, Brazil) and monitored daily for germination over a 12-day period. The germination rate was determined in relation to total sown seeds, in each OE line.

Seeds from wild-type (WT) plants and AsTIR19-OE T2 lines were ethanol-disinfected, sown in 200 mL pots containing sterilized substrate (Carolina Soil, CSC, Brazil) and maintained in a growth chamber as described above. F. oxysporum f.sp. conglutinans PHW 699-3 (ATCC 58110) (FOC) (Hou et al., 2014) was grown on a plate containing Potato Dextrose Agar (PDA) medium and incubated for two days at 28°C, then transferred to a liquid Potato Broth Culture (PBC) and incubated for additional three days on a rotary shaker (110 rpm) at 28°C. The culture was filtered using sterilized filter paper, centrifuged, and diluted to 10⁶ conidiospores/mL in sterile water.

Four-week-old plants (AsTIR19-OE and WT) were inoculated at four equidistant points per individual on the substrate with 5 mL of the diluted FOC suspension. The non-inoculated control plants underwent the same treatment but were inoculated only with autoclaved distilled water. Following FOC inoculation, plants were maintained in a growth chamber (light/dark cycle of 8/16 h, 23°C) and arranged in a randomized design. Assessment of FOC infection was conducted at 7 and 14 days after inoculation (DAI) using the disease index (DI) according to the scale proposed by Diener and Ausubel (2005). The symptoms score applied was as follows: 0- plants are dead; 1- older leaves are dead and young leaves severely stunted; 2- older leaves are chlorotic, yellow, or dead and younger leaves are stunted; 3- older leaves have vascular chlorosis and the rosette appears compact because leaves are stunted; 4- leaf petioles are stunted; and 5- plants are indistinguishable from non-inoculated plants. Three biological replicates of five plants from each OE line and WT were evaluated at three time points (0, 7, 14 DAI) for symptom development. A mean DI was used to conduct a Tukey test to evaluate the significance of the results.

Total RNA was extracted from three pools of root tissues from five T2 seedlings of AsTIR19-OE-11 line and WT plants, submitted to FOC inoculation (7 DAI) and corresponding non-inoculated controls. Extraction was performed using the TRIzol^® Reagent (Ambion^®, Foster City, CA, USA), and purified using the RNeasy Plant Mini Kit (Qiagen, Hilden, Germany). RNA integrity and quantity were verified using gel electrophoresis and a 2100 Bioanalyzer system (Agilent Technologies, Santa Clara, CA, USA). Twelve cDNA libraries, consisting of triplicates of AsTIR19-inoculated (OE-11-I), AsTIR19-non-inoculated (OE-11-NI), Wild-type-inoculated (WT-I) and Wild-type-non-inoculated (WT-NI) were prepared with the “TruSeq Stranded mRNA Library Prep Kit” (Illumina Inc., San Diego, CA, USA) and sequenced on an Illumina HiSeq-4000 at Macrogen Inc. (Seoul, South Korea). Transcriptomic raw data is available in the Sequence Read Archive (NCBI-SRA) repository under the Bioproject ID PRJNA1125443.

The A. thaliana reference genome (TAIR10; https://www.arabidopsis.org/) was used for analysis of the sequence data. Sequence analysis and processing were conducted using FASTp (Chen et al., 2018), STAR (Dobin and Gingeras, 2016), and HTSeq (Anders et al., 2015). Preprocessed data were statistically validated using ClustVis (Metsalu and Vilo, 2015). Differential gene expression analysis was performed with the edgeR package (Robinson et al., 2010).

Genes were classified as differentially expressed (DEGs) if the adjusted p-value was <0.05, as determined by the False Discovery Rate (FDR) method following the Benjamini-Hochberg procedure (Haynes, 2013), and exhibited a minimum 4-fold change in expression (log2FC > 2 or < -2) between samples. DEGs were identified by comparing the following conditions: (i) OE-11-NI vs. WT-NI, (ii) OE-11-I vs. OE-11-NI, (iii) WT-I vs. WT-NI, and (iv) OE-11-I vs. WT-I.

Volcano plots of DEGs were graphically represented using the R package ggplot2 (Wickham, 2016) and BioRender (BioRender.com). To analyze the overlap of DEGs between samples, a Venn diagram was created using the InteractiVenn tool (www.interactivenn.net; Heberle et al., 2015).

A cluster heatmap was generated using ClustVis (https://biit.cs.ut.ee/clustvis/) to visualize the expression profiles of differentially expressed genes (DEGs). All genes identified as DEGs in at least one category were included to compare gene expression patterns across samples. The average correlation was used as the clustering distance metric for rows, while the average Euclidean distance was used for clustering columns.

Manhattan plots were used to summarize the positions and frequencies of DEGs across the five A. thaliana chromosomes. Each identified DEG was mapped to its specific genomic location (TAIR10; https://www.arabidopsis.org/). The p-values were transformed using the negative logarithm base 10 (-log10) to enhance the visualization of statistical significance, with higher -log10 (p-values) indicating greater significance. To account for multiple testing, the Bonferroni correction was applied, setting a significance threshold of p < 0.00001. Graphical representation was created using the R package qqman (Turner, 2014).

To identify significant associations between gene sets and ontological annotations, we employed the hypergeometric test available in the FUNC package (Prüfer et al., 2007). This test was used to assess the overrepresentation of GO terms among the DEGs, following established procedures (Vinson et al., 2018). Only terms showing a family-wise error rate (FWER) < 0.05 were included in the analysis.

For pathway analyses, the KEGG Orthology (KO) identifiers were assigned to the significant DEGs using the blastKOALA option (https://www.kegg.jp/blastkoala/) and the pathways for responsive Arabidopsis root genes were visualized by the online program KEGG Mapper–Color (https://www.genome.jp/kegg/mapper/color.html). Pathways were graphically represented using the SRplot platform (Tang et al., 2023). Functional classification of DEGs was inferred using the tool MapMan v. 3.5.1.R2 (https://MapMan.gabipd.org/) (Thimm et al., 2004).

MapMan visualizations were employed for PageMan enrichment analysis. Log2fold change values of all the up-regulated and down-regulated DEGs were used as input for the PageMan analysis. Over-Representation Analysis (ORA) coupled with Fisher’s exact test was used to detect over- or underrepresented functional categories among different DEGs. A threshold of 1 was set, corresponding to at least a two-fold change in expression. Categories within the dataset that exhibited more or fewer genes than expected, and that surpassed this threshold were highlighted. The degree of deviation from the expected values was represented by varying intensities of colour. Transcription factor (TF) encoding genes were predicted using a similarity search against the PlantTFDB 5.0 database (Tian et al., 2020) with an E-value cut-off of 1E-10. The protein interaction network of Arabidopsis TFs was predicted by GeneMAINA (http://genemania.org/; accessed on 4th June 2024) and String (https://www.string-db.org/; medium confidence 0.400; accessed on 16th June, 2024), based on Arabidopsis proteins.

The same pools of total RNA from the AsTIR19 OE-11.1 line (hereafter OE-11) and WT plants used for the construction and sequencing of the cDNA libraries (above) were used for qRT-PCR expression analysis of 15 selected stress marker genes. Genomic DNA contaminants were removed from total RNA (2 µg) by DNAse treatment, with cDNA synthesis carried out in the same tube as previously described (Morgante et al., 2013) and used as the template for qRT-PCR reactions. Specific primer pairs for Arabidopsis genes related to stress, defense response and hormonal pathways were designed using the Primer3 on-line tool (Untergasser et al., 2012) ( Supplementary Table S1 ).

qRT-PCR reactions were conducted in three biological replicated and technical duplicates for each sample on a StepOne Plus Real-Time PCR System (Applied Biosystems, Foster City, USA), according to Morgante et al. (2013). Primer efficiencies and optimal cycle quantification (Cq) values were estimated using the online real-time PCR Miner tool (Zhao and Fernald, 2005). Transcript expression ratios were calculated and statistically analyzed using the SATqPCR web tool (http://satqpcr.sophia.inra.fr/cgi/home.cgi/, accessed in February 2024) (Rancurel et al., 2019), with normalization against Arabidopsis reference genes GAPDH and EF-1α (Czechowski et al., 2005).

To assess the effects of AsTIR19 overexpression on FOC infection, we generated five Arabidopsis overexpressing (OE) lines named AsTIR19-OE lines (OE1.4, OE2.6, OE6.4, OE8.2, and OE-11.1). Transformation confirmation was conducted via PCR for the marker gene BAR (Phosphinothricin N-acetyl transferase) ( Supplementary Figure S1 ). Confirmation of AsTIR19 transgene overexpression in these lines at the T2 generation was conducted via qRT-PCR, revealing slight variations in transgene expression levels among the lines ( Supplementary Figure S2 ). AsTIR19 expression was not detected in wild-type (WT) plants. Importantly, none of the OE lines exhibited discernible differences in vegetative or reproductive traits compared to WT plants, indicating that varying levels of AsTIR19 overexpression did not lead to visible phenotypic changes in transgenic Arabidopsis plants.

For the FOC bioassay analysis, disease symptoms were evaluated in inoculated Arabidopsis OE lines and WT plants according to the scale proposed by Diener and Ausubel (2005). Initial Fusarium wilt symptoms appeared in WT plants at 7 DAI, characterized by yellowing of older leaves ( Figure 1A ). At this stage, none of the other four OE lines exhibited symptoms, except for OE-2.6 line, which showed mild symptoms. By the 14th DAI, typical FOC symptoms, such as foliar chlorosis, progressing to necrotic lesions and plant death, were prominent in most of the WT plants ( Figure 1A ). In contrast, disease progression was notably slower in all OE lines, with OE-6.4 and OE-11.1 showing no signs of disease, and OE-1.4 and OE-8.2 displaying very mild symptoms or chlorosis on older leaves ( Figure 1A ).

Assessment of FOC disease progression was conducted at 7 and 14 DAI. All five AsTIR19-OE lines showed significant differences (p<0.05) in the disease index score in comparison to WT, with 0 (zero) representing the lowest (dead plants) and 5 (five) the highest (no visible symptoms) scores ( Figure 1C ). At 7 DAI, all OE lines exhibited a higher disease index score when compared to WT plants, with increases of up to 1.6-fold. By 14 DAI, the difference between OE lines and WT plants became even more pronounced, with a maximum increase of 4-fold ( Figure 1B ). Notably, OE-11.1 and OE-6.4 displayed the highest disease indices ( Figure 1C ). Here, we showed that AsTIR19 overexpression caused a significant reduction in FOC infection in all Arabidopsis OE lines tested, as demonstrated by a reduction in the disease index and a delay in the appearance of the disease symptoms such as chlorosis and leaf stunting.

To further investigate transcriptional changes underlying the increased resistance to FOC due to AsTIR19 overexpression, we conducted a comprehensive analysis comparing the overall transcriptional behavior of AsTIR19 OE-11.1 (OE-11) line and WT plants. Additionally, we explored the impact of pathogen-challenge on both transgenic and non-transgenic WT plants. The OE-11 line was selected for transcriptional analysis due to its high disease indexes at 7 and 14 DAI, displaying a healthy phenotype without any signs of disease throughout the bioassay.

To elucidate the molecular mechanisms underlying AsTIR19-modulated resistance to FOC in Arabidopsis, we conducted a comprehensive analysis comparing the whole transcriptome of AsTIR19 overexpressing line (OE-11) and WT roots and their non-inoculated control counterparts. By comparing these conditions, we aimed to identify differentially expressed genes and regulatory pathways involved in the enhanced resistance conferred by AsTIR19 in response to pathogen challenge. Overall, 12 cDNA libraries, encompassing three biological replicates of each condition, produced 152,872,554 Mb of HiSeq-4000 raw reads, of which an average of 96.3% of the total reads was successfully mapped to A. thaliana reference genome (version 10) ( Supplementary Table S2 ). PCA (principal component analysis) analysis of the RNASeq data from the 12 cDNA libraries showed that, based on the number of counts per gene, FOC-inoculated samples (red and green) clustered together and were clearly separated from the non-inoculated samples (blue and purple), regardless of the transgene insertion ( Supplementary Figure S3 ), suggesting a core infection response in OE-11 line and WT plants. Nonetheless, transgenic and WT samples each clustered together in subclusters, suggesting that, in addition to the core infection-responsive genes, specific FOC-responsive genes were regulated in the transgenic plants.

The overall transcriptional profile of DEGs between the OE-11 line and WT plants, inoculated and non-inoculated with FOC, is represented by volcano plots in Figure 2A . For all comparisons, the number of upregulated DEGs (red) exceeded the number of downregulated (blue), with DEGs identified in the FOC-inoculated OE-11 line compared to non-inoculated plants (OE-11-I vs OE-11-NI) showing the highest expression magnitude ( Figure 2A ). The largest number of DEGs (778) was observed between non-inoculated OE-11 and WT plants (OE-11-NI vs WT-NI), comprising 455 up and 323 downregulated genes affected by the transgene expression ( Figure 2B ; Supplementary Table S3 ). This corresponds to approximately 2.88% of the entire A. thaliana genome (https://www.arabidopsis.org/).

FOC inoculation significantly altered the expression of numerous DEGs in both the OE-11 line (316 up- and 118 downregulated) and WT plants (324 up- and 304 downregulated) in comparison to non-inoculated control plants, with 179 DEGs found exclusively in the inoculated transgenic line ( Figure 2B ; Supplementary Table S3 ).

Figure 2C shows the overall transcriptional profile of DEGs identified between the four conditions studied. We found that the majority of DEGs due to the transgene overexpression (OE-11-NI vs WT-NI) (a) show an opposite expression behavior to those incited by FOC inoculation (OE-11-I vs OE-11-NI) in the transgenic plants (d). This overall contrasting expression behavior suggests that in Arabidopsis, the majority of DEGs regulated due to AsTIR19 overexpression are not the same as those incited by FOC inoculation ( Figures 2B, C ), and different genes and metabolic pathways are triggered in response to the pathogen in the transgenic OE plants in comparison to those in the WT plants.

Manhattan plots were created to visualize the distribution of significantly expressed DEGs across the Arabidopsis genome, using Bonferroni correction with an FDR threshold of <0.000001 ( Supplementary Figure S4 ; Supplementary Table S4 ). Using this stringent criterion, we found 29 DEGs (labelled orange dots) that are regulated due to the transgene expression (OE-11-NI vs WT-NI) ( Supplementary Figure S4A ), of which various are related to membrane receptor and signaling, such as transmembrane and amino acid transporter proteins, expansins and RLKs, as well as to reactive oxygen species (ROS) detoxification and production of defense related metabolites ( Supplementary Table S4 ).

From the 14 DEGs identified due to the fungal infection in the OE-11 line (OE-11-I vs OE-11-NI) ( Figure 3B ), several were associated with stress responses. These include genes involved in membrane perception (expansins) (Brasileiro et al., 2021), and genes that interfere with the accumulation of defense gene transcripts (glutamate racemase) (Kwaaitaal et al., 2011). Pathogen defense proteins identified included jacalin (Esch and Schaffrath, 2017), arginase, myrosinase (Chhajed et al., 2020) and acethyl-ornithine lectins (Kalamaki et al., 2009). Additionally, genes responsive to defense-related hormones including jasmonic (JA) and abscisic acids (ABA) were upregulated ( Supplementary Figure S4B ; Supplementary Table S4 ). Diversely, the 23 DEGs identified in the WT response to the fungal pathogen (WT-I vs WT-NI) included those related to broad stress responses, such as chitinases, wall-associated kinases (WAK) and osmotin ( Supplementary Figure S4C ; Supplementary Table S4 ). DEGs shared between both genotypes when inoculated with FOC (OE-11-I vs WT-I) included TFs such as WRKY and bHLH which have been previously associated with stress responses in Arabidopsis (Abe et al., 2003; Pandey and Somssich, 2009) ( Supplementary Figure S4D ; Supplementary Table S4 ).

We did not identify genomic regions or clusters of genes that were significantly differentially expressed (FDR < 0.000001) among the four conditions applied in this study, with evidenced for an even distribution of significant genes across the five A. thaliana chromosomes ( Figure 3 ).

In a more detailed comparative analysis of the OE-11 line and WT transcriptomes, we found that the effects of the overexpression of this truncated NLR led to an enrichment of functional GO categories linked to general stress defense mechanisms, such as stress response and oxidoreductase activity. The global transcriptional reprogramming observed in the AsTIR-OE line mirrors that triggered by endogenous plant NLRs, which, after being activated by receptors that recognize the pathogen, increase ROS production, defense hormone production, and immune signaling (Lolle et al., 2020). Moreover, the enrichment in the carbohydrate metabolic process observed in the transgenic plants is also crucial in plant defense against pathogens. Carbohydrates provide the necessary energy and resources for immune response activation and regulate the expression of PR proteins in response to pathogens (Rojas et al., 2014).

The overexpression of AsTIR19 also significantly affects cellular metabolic pathways, immune response mechanisms, and specialized biosynthetic processes. Accordingly, upregulated DEGs in the enriched KEGG pathways are related to phenylpropanoid biosynthesis, including flavonoids, monolignols, phenolic acids, stilbenes, and coumarins. These compounds are essential components of cell walls, protectants against high light and UV radiation, and phytoalexins against herbivores and pathogens (Deng and Lu, 2017). We also observed the enrichment in the biosynthesis of secondary metabolites category in the transgenic plants, including propanoates. These are known precursors of propionic acid, which has been demonstrated to inhibit the mycelial growth of various fungi, including B. cinerea, S. sclerotiorum and F. oxysporum (Şehirli and Saydam, 2016).

In addition to triggering defense genes and associated pathways, the overexpression of AsTRI19 also induced several genes associated with primary metabolic pathways in Arabidopsis, such as those involved in the synthesis or degradation of carbohydrates, amino acids, and lipids. Sugars constitute a primary substrate providing energy and structural material for plant defense responses in plants and can also act as signal molecules interacting with hormonal signaling networks in plant tissues (Morkunas and Ratajczak, 2014). Here, an increase of upregulated DEGs associated with alanine, aspartate, and glutamate metabolism, as well as those involved in the degradation of the valine, leucine, and isoleucine was also observed in transgenic AsTIR19 plants. This is in accordance with studies in Arabidopsis showing that higher levels of sugars and accumulation of amino acids in pathogen-infected plant tissues can lead to enhanced plant resistance (Rojas et al., 2014; Ward et al., 2010).

The transcriptome analysis of transgenic AsTIR19-OE plants in response to FOC inoculation revealed a significant increase in the number of upregulated DEGs in GO categories related to plant defense responses. This included chitinases, thaumatin-like pathogenesis-related proteins (PRs), and peroxidase genes previously associated with the early stages of the plant defense response to SA treatment in Arabidopsis (Agrawal et al., 2010). This suggests that the transgenic plants are activating a comprehensive defense response involving both direct antimicrobial actions and signaling pathways. Such reprogrammed transcriptional networks induced by biotic and abiotic stresses in transgenic plants has previously been observed in Arabidopsis overexpressing heterologous Transcription Factors (TFs), in poplar overexpressing multiple resistance genes, and in transgenic wheat overexpressing GmDREB for enhanced tolerance to drought and salt (Quan et al., 2019; Fu et al., 2021; Zhang et al., 2014; Jiang et al., 2014).

Chitinases and thaumatin-like proteins are PR proteins involved in both direct and indirect defense reactions (Dong et al., 2017; Wang et al., 1996). While chitinases play a dual role, both inhibiting pathogen growth, and releasing Pathogen-Associated Molecular Patterns (PAMPs) that induce defense response in the host (Zhang et al., 2016), thaumatin-like proteins (PR5) are involved in systemically acquired resistance (SAR) and stress responses in plants. In addition, accumulation of ROS and the activation of plant defense enzymes, such as peroxidases, helps to maintain cell integrity and remove accumulated peroxide. The higher expression of PR and peroxidase coding genes in the FOC-inoculated compared to non-inoculated OE plants, suggests that the cues from the pathogen trigger a more robust defense response in OE plants.

Accordingly, the enrichment of KEGG pathways related to the biosynthesis of secondary and phenylpropanoid metabolites, including the mitogen-activated protein kinase (MAPK) signaling pathways, was also highly enriched in the FOC-inoculated transgenic line. MAPK cascades are activated by a variety of stress stimuli leading to changes in gene expression and hormone responses (Romeis et al., 1999; (Taj et al., 2010). The functional analysis of DEGs between FOC-inoculated and non-inoculated OE line suggests that fungal infection can trigger defense responses mediated by SA and JA pathways through MAPK signaling. This activation subsequently incites the production of ROS and their scavenging enzymes, as well as the expression of defense genes (Jagodzik et al., 2018).

It is important to note that many of the rapid changes in gene expression observed during the OE-line responses to FOC infection also occur in the susceptible interaction. Accordingly, DEGs identified between FOC-inoculated and non-inoculated WT plants were also found in stress-responsive GO categories, such as plant defense and secreted proteins, although with a smaller fold enrichment than those observed in the transgenic line. In contrast, while KEGG pathway enrichment analysis revealed that upregulated DEGs in biosynthesis of secondary metabolites pathways, including flavonoid biosynthesis and propanoate metabolism, were enriched in the transgenic line, downregulated DEGs were observed in these categories in the WT plants.

Overall, the comparative functional analysis between the FOC-inoculated transgenic line and WT plants highlight the effects of AsTIR19 overexpression on the induction of defense pathways linked to the biosynthesis of secondary metabolites and phenylpropanoids. These pathways are further enriched by genes involved in biosynthesis of terpenoids, phenolic compounds, and cyano amino acids, which likely lead to an enhanced disease resistance in the transgenic line (Häusler et al., 2014; Zaynab et al., 2018).

TFs are integral to plant defense mechanisms, primarily through their roles in regulating secondary metabolism, activating defense-related genes, and interacting with hormonal signaling pathways. Their cooperative interactions are crucial for mounting an effective defense response against a range of stresses (Buscaill and Rivas, 2014; Wani et al., 2021).

Here, we found that TFs from four families that play an important role in immune responses, such as bHLH, WRKY, NAC and MYB were significantly upregulated in the FOC-inoculated transgenic line in comparison to the control. bHLH TFs are involved in the activation of genes related to stress responses, including those encoding antimicrobial peptides and enzymes, such as those involved in the regulation of JA pathways and biosynthesis of flavonoids and anthocyanin (Li, 2014; Naik et al., 2022). WRKY proteins interact with other TFs and regulatory proteins to modulate crucial biological processes, helping to perceive external stress stimuli through signaling molecules. These TFs are also involved in the SA pathway and the activation of primary genes associated with stress responses, including specific defense responses to F. oxysporum (Jiang et al., 2017; Aamir et al., 2018; Li et al., 2021). In this study, we found that bHLH and WRKY TFs form part of a complex regulatory network that integrate multiple signaling pathways in the AsTIR19-OE plants. This network has the potential to modulate defense responses to pathogens. Specifically, WRKY TFs, which are involved in SA pathway, can interact with bHLH TFs that regulate the JA pathway. Such interactions enable a coordinated modulation of defense mechanisms, potentially enhancing the plant’s ability to respond effectively to diverse pathogenic threats.

Additionally, NAC TFs, which are known to play a functional role in regulating responses to multiple stresses (Nuruzzaman et al., 2013; Saidi et al., 2022; Srivastava et al., 2022), were upregulated in the OE-line. The overexpression of a NAC gene in wheat led to significant transcriptional reprogramming in response to F. graminearum, potentially enhancing defenses primarily involved in the hormone-mediated signaling pathways of JA and abscisic acid (ABA) (Vranić et al., 2023).

The cooperative interaction among TFs observed in AsTIR-OE plants during interaction with FOC also seems to contribute to the resistance in the transgenic plants against the pathogen. This has previously been demonstrated by studies that highlight protein-protein interactions between TFs regulating the expression of specific PR genes in response to disease and contributing to SA and JA-induced pathogen resistance (Tran et al., 2007; Shan et al., 2016; Nuruzzaman et al., 2013).

Marker genes associated with specific biological pathways have been frequently used as indicators for the positive/negative regulation of their respective signaling cascade (Zhang et al., 2020b). In our study, we observed via qRT-PCR a significant upregulation in the expression of a subset of 15 commonly used defense marker genes in the transgenic line, following FOC inoculation in comparison to non-inoculated plants. Overall, the FOC-inoculated OE-line exhibits a complex and multi-faceted defense response. This is characterized by the upregulation of various marker genes in the SA signaling pathway, indicating a robust SA-dependent defense mechanism, in concurrency with upregulated genes in the JA-ET pathway, indicating a coordinated defense response. Additionally, the upregulation of marker genes in the IAA hormone pathway and ROS scavenging suggests their additional role in modulating the defense response. These findings collectively highlight a complex and integrated defense mechanism activated in the OE-line against FOC infection.

By acting as a central regulator of the SA-mediated defense pathway, NPR1 ensures a robust and effective immune response by activating the transcription of PR genes (Spoel et al., 2009; Cao et al., 1997). Here, the strong upregulation of NPR1 and PR5 (fold change>40 and >16 respectively) in inoculated transgenic plants underscores the importance of the SA pathway in providing strong defense against FOC, corroborating the potential benefits of genetic modifications that enhance endogenous NPR1 expression for improving disease resistance in transgenic plants.

In addition to the increased production of PR proteins, two previously studied Arabidopsis NLR genes, NLR (At1g72910) and the truncated TIR (At1g72930) (Nasim et al., 2020; Chen et al., 2021), were also upregulated after FOC infection in the transgenic plants. This suggests that AsTIR19 may work in concert with such other NLRs as recently shown by Ngou et al. (2022). In these cooperative networks, beyond the role of individual NLRs, an intricate receptor network requires multiple NLRs to function together for recognizing diverse pathogen effectors and triggering immune signaling. However, further research is required to elucidate the interaction between AsTIR19 and these NLRs, and to clarify their molecular relationships.

The subtilase SBT3 gene was also upregulated in the FOC-inoculated transgenic line. SBT3 is known to contribute to the activation of defense-related pectin methylesterases (PMEs), influencing the expression of specific defense genes and the structure of pectin (Coculo et al., 2023). Its expression initiates a durable auto-induction mechanism that promotes chromatin remodeling and activates a SA-dependent mechanism of priming of defense genes for amplified response (Ramírez et al., 2013).

Activation of the JA pathway in the transgenic line during interaction with FOC was denoted by the upregulation of two genes involved in pathogen perception, namely MD-2-like and ML3. These genes are implicated in immune responses to pathogenic cell components, such as lipopolysaccharides and other PAMPs, as well as to molecules associated with herbivory (HAMPS), that can trigger immune responses via JA –mediated pathways (Fridborg et al., 2013; Song et al., 2022). Additionally, JA signaling and production of antimicrobial compounds is demonstrated by the upregulation of VSP2. This gene product contributes to the plant’s ability to resist pathogens by enhancing the production of secondary metabolites, other defense-related compounds and PR6, with their associated antimicrobial properties contributing to either death or inhibition of pathogens, including fungi and bacteria (Myagmarjav et al., 2017).

As previously observed in tobacco plants infected by S. sclerotiorum (Guimaraes et al., 2022), and in our current study with A. thaliana infected by F. oxysporum, overexpression of the NLR AsTIR19 driven by a constitutive promoter led to an ubiquitous transgene expression, with the activation of common primary SA and JA-ET defense pathways in these two pathosystems which involved necrotrophic and hemibiotrophic fungal pathogens and two distinct plant host species.

In addition to SA and JA signaling pathways, the ethylene pathway was triggered in the FOC-inoculated OE line, as demonstrated by the upregulation of the TFs EIN3 and ERF, which are central to mediation of the plant’s response to ethylene (Zhao et al., 2021). Additionally, a member of the PADRE gene family, which is involved in the regulation of pathogen-induced stress responses (Didelon et al., 2020), was also slightly upregulated in the transgenic FOC-inoculated OE line.

In parallel with the primary regulated defense hormones pathways described above, we also observed a potential enhancement of the auxin signaling pathway and ROS signaling, as evidenced by the upregulation of IAN and APX genes, respectively. Auxin signaling can modulate various defense responses, including the activation of PR genes and the reinforcement of the plant cell wall (Remans et al., 2006). This hormone can also influence the plant’s overall defensive capacity by regulating growth and developmental processes in response to stress. ROS are crucial plant defense molecules that serve multiple functions. They are known to act as signaling molecules that trigger defense-related genes and proteins, exert direct antimicrobial actions on microorganisms, contribute to cell wall reinforcement through oxidative cross-linking, and are involved in programmed cell death to restrict pathogen spread (Ali et al., 2018). Together, the triggering of these various defense pathways in the AsTIR-OE line highlights a complex network of plant defense mechanisms that work synergistically to enhance resistance in the transgenic plant against FOC.

Persistence of Fusarium wilt disease can be attributed to the complex genetics of host resistance, constituting a difficult trait to confer by breeding, together with the persistence of the pathogen in the field for extended periods (Gordon, 2017). Enhanced resistance against Fusarium wilt disease in different plant species has been achieved with variable success through the engineering of host genes involved in resistant interactions and defense responses (Hao et al., 2020; Zhang et al., 2020a; Chitwood-Brown et al., 2021; Sadhu et al., 2023), and through host-induced gene silencing (HIGS) via RNAi (Singh et al., 2020). In this study, we demonstrated that the overexpression of AsTIR19, a truncated NLR from wild A. stenosperma, enhanced tolerance to FOC in transgenic Arabidopsis. Transcriptome profiling revealed that the transgene overexpression alone affected certain defense genes and regulators, and metabolic pathways, affected by the transgene overexpression. We also identified genes and their related regulation networks that were altered in transgenic plants in response to FOC. These results thus contribute to elucidating the mechanisms by which, after fungal effector recognition, the amplification of the immune response and the regulation of key genes occurs due to AsTIR19 overexpression.

AsTIR19 is, therefore, a potential candidate for plant improvement through biotechnology approaches and constitutes a promising tool for resistance against FOC. Moreover, our previous studies showed that AsTIR19 overexpression in transgenic tobacco also enhanced resistance against the necrotrophic pathogen S. sclerotiorum (Guimaraes et al., 2022). Together, these findings suggested that a broader resistance towards plant pathogenic fungi may be achieved by overexpressing this truncated NLR gene in different host plants. AsTRI19 gene, therefore, has the potential to be explored in a range of susceptible crops, and plant breeding programs can profit through the development of tightly linked molecular markers, enabling precise selection and introgression of this transgene into elite cultivars. Additionally, the pyramiding of AsTIR19 with other resistance genes offers a robust strategy to manage pathogen variability and reduce the likelihood of resistance breakdown over time. Such a multi-gene approach can ensure sustained protection against a broad spectrum of F. oxysporum strains, contributing to more resilient crop varieties and improved agricultural productivity.