Identification of genes involved in the tomato root response to Globodera rostochiensis parasitism under varied light conditions

Identification of genes involved in the tomato root response to Globodera rostochiensis parasitism under varied light conditions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identification of genes involved in the tomato root response to Globodera rostochiensis parasitism under varied light conditions Mateusz Matuszkiewicz, Magdalena Święcicka, Marek Koter, Marcin Filipecki This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3982446/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Aug, 2024 Read the published version in Journal of Applied Genetics → Version 1 posted 4 You are reading this latest preprint version Abstract Understanding the intricate interplay between abiotic and biotic stresses is crucial for deciphering plant responses and developing resilient cultivars. Here, we investigate the combined effects of elevated light intensity and nematode infection on tomato seedlings. Chlorophyll fluorescence analysis revealed significant enhancements in PSII quantum yield and photochemical fluorescence quenching under high light conditions. qRT-PCR analysis of stress-related marker genes exhibited differential expression patterns in leaves and roots, indicating robust defense and antioxidant responses. Despite root protection from light, roots showed significant molecular changes, including down-regulation of genes associated with oxidative stress and up-regulation of genes involved in signalling pathways. Transcriptome analysis uncovered extensive gene expression alterations, with light exerting a dominant influence. Notably, light and nematode response synergistically induced more differentially expressed genes than individual stimuli. Functional categorization of differentially expressed genes upon double stimuli highlighted enrichment in metabolic pathways, biosynthesis of secondary metabolites, and amino acid metabolism, whereas the importance of specific pathogenesis related pathways decreased. Overall, our study elucidates complex plant responses to combined stresses, emphasizing the importance of integrated approaches for developing stress-resilient crops in the face of changing environmental conditions. cyst nematodes stress combination abiotic stress biotic stress RNA-seq Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Plants have evolved to thrive in environmental conditions which vary within the range of variability characteristic of a given climatic zone and ecosystem. Moreover they try to endure more or less regular pression of biotic threats such as diseases and pests. On top of this there is a pressure of climate changes including recent anthropogenic global warming and environment pollution. All of these factors, usually acting simultaneously, affect crop plant growth development and yield making the study of adaptation mechanisms increasingly important (Zandalinas & Mittler 2022). The ability to detect and adjust reactions applies to both abiotic (drought, salinity, heat, cold, chilling, freezing, nutrient deficiency, varying light intensities, UV radiation, ozone exposure, and anaerobic conditions caused by flooding) and biotic stimuli (bacteria, fungi, viruses, oomycetes, and a multitude of herbivorous animals) (Zandalinas et al., 2023). Hans Selye (1936) postulated conception of stress response for living organisms, which can be synthetized to: “All agents can serve as stressors, inducing both stress and specific actions. These caused coexistence of stressor-specific and general non-specific responses”. “True stress” occurred when a specific threshold of a stressor surpasses the compensatory capacity of the plant. The stress tolerance threshold is contingent not solely upon the plant species but also on the nature of applied stressors and the conditions of the plant. Additionally, variations exist among plants in terms of their capacity to cope with stress. Is mean that stress is a dose-dependent and species-specific type of plant response (Lichtenthaler 1998; Georgieva & Vassileva 2023). Consequently, plants constantly confront diverse combinations of several stimuli or stressors (Anwar et al., 2021). Zandalinas and colleagues (2021) introduced the term “multifactorial stress combination” (MFSC) to characterize situations where three or more stress-inducing factors co-occur. Even the number of MFSC is very high, the number of physiological and molecular responses tend to integrate towards relatively limited repertoire of adaptive or defense mechanisms. Consequently the individual impact of a given stressor may be different than their collective effect showing synergy or antagonism. Importantly the molecular outcome of underlaying mechanisms is distinctly discernible at the level of the plant's transcriptome, proteome, or metabolome being the source of potential targets to enhance crop performance via e.g. genome editing (Zandalinas et al., 2023). Most of studies with combined stress conditions indicate that there is a negative impact of abiotic stress (mainly drought and salinity stress) on pathogen resistance (Suzuki et al., 2014). There are however some exceptions such as the beneficial role of salt-related stress on the powdery mildew resistance of barley (Wiese et al., 2004). Such unpredictable reaction may depend on the dual role of ROS and the specific and local interplay of ROS stoichiometry and pathogen effectors (Gadjev et al., 2006; Siddique et al., 2014). Plant parasitic nematodes are among the most significant pests, with those belonging to the genera Globodera and Heterodera , known as cyst-forming nematodes, ranking at the top of the list, and causing annual losses ranging from US $ 80 to 358 billion (Jones et al., 2013). These nematodes infect roots, suppressing the defense response and inducing plant cells to form syncytia specialized in sustaining the nutrition of developing larvae. During syncytium formation, numerous morphological, ultrastructural, physiological, and molecular changes occur in the infected plant. Particularly, the initial syncytial cell undergoes significant enlargement, the nucleus swells and the central vacuole is replaced by smaller ones. Mitochondria, plastids, endoplasmic reticulum, lipid bodies, and ribosomes proliferate, causing the cytoplasm to become denser. The syncytium gradually enlarges through partial dissolution of cell walls and fusion of neighbouring protoplasts (Matuszkiewicz & Sobczak, 2023). All these changes are accompanied by local or systemic alterations in the expression of genes related to various processes such as the cell cycle, cell wall modification, ROS homeostasis, and defense. Additionally, there is a shift in the expression of genes involved in signal transduction and hormonal regulation (Matuszkiewicz et al., 2018; Siddique et al., 2022). Despite advancements in understanding plant responses to various stimuli, there remains a limited number of studies examining the concurrent effects of biotic or abiotic stressors alongside plant-parasitic nematodes. Kutyniok et al. (2014a) conducted a study investigating the impact of nematode ( H. schachtii ) parasitism on Arabidopsis plants concurrently attacked by aphids ( Myzus persicae ). Their findings indicated that the sequence of parasite feeding on a host plant reciprocally affected their fitness and reproductive success. Notably, the effect of beet cyst nematode on aphid performance was found to be modified by nitrate fertilization (Kutyniok & Müller, 2013). Additionally, the researchers presented microarray transcriptome data illustrating that aphid infestation influenced nematode-induced transcription in roots, but not vice versa (Kutyniok et al., 2014b). Kammerhofer et al. (2015) further explored the communication between roots and leaves subjected to biotic stimuli. They simultaneously infested Arabidopsis roots with H. schachtii and leaves with Frankliniella occidentalis or Tetranychus urticae . The study revealed that H. schachtii triggered hormone-related systemic responses, leading to elevated levels of JA, SA, and IAA in aboveground parts of plants. These findings elucidated the altered susceptibility and/or attraction of shoot invaders to these plants. Interestingly, while shoot-feeding herbivores (thrips and spider mites) modified Arabidopsis phytohormone homeostasis, only F. occidentalis increased susceptibility to H. schachtii by altering JA and its active conjugate JA-Ile in the roots. Several studies have also investigated the combined effects of abiotic stress and nematode parasitism. For example, in-depth physiological studies on upland rice led to the conclusion that the presence of plant-parasitic nematodes exacerbates the detrimental effects of drought (Audebert et al., 2000). Yang et al. (2015) discovered that night time irradiation of tomato and watermelon plants with different light qualities influenced susceptibility to the root knot nematode – Meloidogyne incognita . Notably, treatment with red light significantly boosted immunity, correlating with increased expressions of PR1 (a marker gene of SA signalling activation) and PI1 (a marker gene of JA signalling). Moreover, this treatment improved plant growth and leaf CO 2 assimilation. The molecular investigation of the combination of drought stress and H. schachtii infection was conducted by Atkinson et al. (2013) in Arabidopsis roots. Detailed transcriptome analysis showed that 47% of genes expressed differentially during drought stress, and 85% of the genes involved in the response to H. schachtii parasitism did not undergo differential expression under cumulative stress. Further studies focused on selected genes - RAPID ALKALINIZATION FACTOR-LIKE8 ( AtRALFL8 ), METHIONINE GAMMA LYASE ( AtMGL ), and AZELAIC ACID INDUCED1 ( AtAZI1 ) - highlighting the intricate interplay among various stress responses in plants, affirming the significance of investigating combined stress factors. Similar to other abiotic stresses, substantial changes in light intensity and quality have negative effects on plant growth due to the deregulation or damage of photosynthetic machinery by excess energy. Plants have therefore evolved various protective and compensating mechanisms that monitor the intensity, wavelength, duration, and direction of light, and respond to mitigate the negative effects of harsh conditions (Roeber et al., 2021). Chloroplasts seem to play a central role not only in sensing and responding to environmental stresses but also in orchestrating immune reactions against plant pathogens. They are well-adapted for this role as they are the primary source of reactive oxygen species (ROS) and the starting point of salicylic acid (SA) biosynthesis in plants (Trotta et al., 2014; Lefevere et al., 2020). Consistently, light stress induces systemic acclimatization, enhancing tolerance to virulent bacteria through local and systemic changes in the pool of ROS, SA, and ethylene (Szechyńska-Hebda et al., 2010). The data mentioned clearly indicate numerous points of intersection in the responses to biotic stress and light stress. We conducted this study to enhance the understanding of how different light intensities influence the molecular response of tomato ( Solanum lycopersicum ) roots to parasitism by the potato cyst nematode ( Globodera rostochiensis ). 2. Materials and methods 2.1. Plant material Seeds of tomato ( Solanum lycopersicum ) cv. Moneymaker were used in experiments. Seeds were surface-sterilized in 1.5% sodium hypochlorite for 10 min and subsequently rinsed three times in distilled water. Two seeds per Petri dish (100 mm in diameter) were sowed on medium containing 1.5% (w/v) B5 medium (Gamborg’s basal salt mixture, 2% (w/v) sucrose, and 1.5% (w/v) agar, pH 6.2) and subsequently grown at a long day regime (16 : 8 h light/dark, 22 : 20°C, 70% HR). Light intensity was between 50–60 µmol m − 2 s − 1 – low light conditions (LL) and 350–400 µmol m − 2 s − 1 – high-light conditions (double stimuli; HL). Petri dishes were sealed with gas permeable medical adhesive tape (3M™ Micropore™). To avoid root system illumination Petri dishes were covered in black envelopes. 2.2. Nematode assay Cysts of potato cyst nematode ( G. rostochiensis Woll.) pathotype Ro1 were surface sterilized in 90% (v/v) ethanol for 15 s following a 10 min incubation in 1.3% (w/v) sodium hypochlorite. Then cysts were washed 3 times in sterile water, and rehydrated in sterile potato root diffusates in the dark at 20°C for one week. The potato root diffusate was made according to method established by Evans (1983). Hatched pre-parasitic J2s were sterilized by 0.05% HgCl 2 for 5 min and immediately washed five times in distilled water. After sterilization suspended in sterile distilled water nematodes were check for their vitality and concentration. Fourteen-day-old tomato seedlings were inoculated with 200–250 J2s under sterile conditions. Inoculated plates were kept in the dark for 6 h, and subsequently transferred into a growth chamber under high-light conditions. Two plants were used in one Petri dish and the experiments were repeated three times with 10 plants per genotype in one replicate. The numbers of induced syncytia per root system were counted at 14 dpi and the data were analyzed by a t-test (p < 0.05). 2.3. Chlorophyll a fluorescence measurement Chlorophyll a fluorescence was determined using a pulse amplitude-modulated FluorCam 800 MF PSI device (Brno, Czech Republic) on whole S. lycopersicum leaves. Before taking measurements, the plants underwent a 30-minute period of dark adaptation to determine the initial fluorescence (F o ) and the maximum fluorescence (F m ). Accordingly to methodology established by Baker (2008) the maximum quantum efficiency of PSII – F v /F m =(F m –F o )/F m , non-photochemical quenching – NPQ=(F m –F mʹ )/F mʹ , photochemical quenching – qp=(F mʹ –F t )/(F mʹ –F 0ʹ ), and the operating quantum efficiency of PSII known as PSII quantum yield – ΦPSII=(F mʹ −F s )/F mʹ were calculated. The plant vitality index R fd was calculated by the FluorCam 7.0 software. Data were further statistically analyzed using two-way ANOVA with Bonferroni test for correction for multiple comparisons (p < 0.05). 2.4. RNA Extraction for Transcriptomic Analysis Total RNA was isolated from uninfected plants (both leaves and roots) at 1st and 3rd days post transfer (dpt), and infected root segments, along with appropriate controls, were collected 14 days post-infection. The isolation was performed using the Universal RNA Purification Kit (Eurx, Gdańsk, Poland) following the manufacturer's protocol, which included on-column digestion of DNA. RNA integrity was evaluated on 1% agarose gel. However RNA yield and purity were estimated using the NanoDrop ND-1000 (NanoDrop Products, Wilmington, DE, United States), and the Experion (Bio-Rad, Miasto, CA, United States). Total RNA with RQI values ≥ 9.0 and 28S:18S ratios ≥ 1.2 was used in the RNA-sequencing analysis. 2.5. RNA-Sequencing Analysis The Illumina HiSeq2500 platform (Illumina Inc., San Diego, CA, United States) was used for RNA-sequencing (RNA-seq) analysis. To obtain a comprehensive overview of the tomato root transcriptome and transcript profiles in response to G. rostochiensis parasitism under increased light intensity, three biological replicates were used to construct the libraries. Genomed SA (Warsaw, Poland) conducted paired-end sequencing. In all analytical procedures, the ITAG4.1 Tomato Genome Annotation Release file, obtained from Solgenomics ( https://solgenomics.net ), was employed. Initially, the ITAG4.1_gene_models.gff file was subjected to conversion into the ITAG4.1_gene_models.gtf file format, utilizing the gffread software version 0.11.7 (Pertea & Pertea 2020). The quality assessment and trimming of fastq files were executed with Trim Galore version 0.6.4 (Krueger et al., 2023). Subsequently, the STAR aligner version 2.7.3a (Dobin et al., 2013) was utilized to index the genome and align reads to the tomato genome assembly build 4.00. Mapped reads or fragments, in the case of paired-end data, were associated with genomic features, generating bam files, through the featureCounts function from the Rsubread package version 2.14.2 (Liao et al., 2019), integrated into R software version 4.3.0. The resulting count matrix was then subjected to the identification of Differentially Expressed Genes (DEGs) employing the DESeq2 package version 1.40.2 (Love et al., 2014) within R software version 4.3.0. The criteria for DEG selection were set at |log2-fold change (FC)| > 1.0 and adjusted P-value < 0.05. Finally, DEGs were annotated by referencing the ITAG4.1_descriptions.txt file from Solgenomics ( https://solgenomics.net ) with the aid of the dplyr package version 1.1.3 (Wickham et al., 2023) within R software version 4.3.0. The software tools, namely gffread, Trim Galore, and STAR, were executed on an operating system environment running Ubuntu 20.04.5 LTS (GNU/Linux 4.4.0-19041-Microsoft x86_64). Gene ontology enrichment analysis was performed with ShinyGO v.0.77 (Ge et al. 2020) The sequencing data are accessible in SRA database (PRJNA1078223). 2.6. Quantitative Real-Time RT-PCR (qRT-PCR) RNA was isolated using the Universal RNA Purification Kit (Eurx, Gdansk, Poland) according to the manufacturer's protocol with on-column digestion of DNA. RNA integrity was assessed using a 1% agarose gel, while RNA yield and purity were determined using the NanoDrop ND-1000 (NanoDrop Products, Wilmington, DE, USA). A total of 1 µg of RNA was reverse transcribed using (N) 6 random hexamer primers and following the conditions specified in the QuantiTect Reverse Transcription Kit (Qiagen). Quantitative RT-PCR was performed in triplicate using the QuantiTect SYBR Green PCR Kit (Qiagen) with the Bio-Rad CFX96 Touch™ Real-Time PCR Detection System (Bio-Rad, Niasto, CA, USA). The reaction conditions were as follows: denaturation at 95°C for 3 min, and 40 cycles of 95°C for 10 s and 60°C for 30 s. The reaction mixture, with a total volume of 20 µL, consisted of 8 µL of cDNA (2.5 ng/µL), 1 µL for each gene-specific primer (10 mM), and 10 µL of the 2× Ready Fast Green Mix reagent (from Biochem Development, Gdańsk, Poland). Two tomato genes, SAND (SGN-U316474) and RPL8 (NM_001247186), were used as internal reference genes. The transcript level of the selected genes was normalized to that of SAND and RPL8 using the ΔΔ Ct method (Livak and Schmittgen, 2001). The significance of differences from the control was revealed by REST (Pfaffl et al., 2002). After the PCR, product melting curves were generated to verify the purity of the amplicons. The same methodology as described above was used for validation of the RNA-seq data (Supplementary Table 1). The list of primers used in qRT-PCR are included in the supplementary materials (Supplementary Table 2). 3. Results 3.1. Effects of elevated light intensities on photosynthetic performance and molecular response in tomato seedlings Commonly employed non-invasive assessments of a plant's physiological state rely on measuring chlorophyll a fluorescence. In this study, we aimed to investigate the combined reaction to high light intensity and nematode infection therefore the conditions typically used in tomato/potato cyst nematode experiments were slightly modified (Dąbrowska-Bronk et al., 2015; Święcicka et al., 2017). Tomato seedlings were exposed to elevated light intensities being placed on a medium in a plastic Petri dish sealed with permeable medical adhesive tape. The shoots remained uncut, while the roots were shielded with a black envelope. The maximum light intensity was adjusted to a level that did not cause temperature shifts. The impact of transferring tomato plants from low light (LL) to high light (HL) conditions on photosystem II (PSII) photochemistry was assessed using various chlorophyll fluorescence-related parameters, including maximum quantum efficiency of PSII (F v /F m ), non-photochemical quenching (NPQ), photochemical fluorescence quenching (qP), PSII quantum yield (ΦPSII), PSII quantum yield in light-adapted leaves (F v ’/F m ’), and plant vitality (R fd ) (Baker, 2008). Measurements were taken at two time points: 1 day post-transfer (dpt) and 3 dpt, with appropriate LL controls on two-week-old tomato seedlings. Two parameters exhibited statistically significant increases after transferring plants to elevated light conditions at both time points: PSII quantum yield and photochemical fluorescence quenching (Fig. 1 C and E). The other parameters showed insignificant fluctuations (Fig. 1 A, B, D and F). These results indicate that seedlings cultured under higher light intensities had greater efficiency of PSII, consistent with previous literature (Takagi et al., 2019). To track the activation of signaling pathways, we evaluated the expression of several stress-related marker genes using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. The expression was checked in leaves (organs subjected to HL stimuli) and roots (remote, shaded organs) at 1 and 3 dpt. Cyst nematodes migrate along the roots to find the initial syncytial cell (ISC) before inducing the feeding structure. Upon initial penetration, the root cells undergo localized damage, triggering the plant's defense response. Additionally, cyst nematodes secrete effector proteins into the plant root to manipulate host cell functions and modulate plant hormone levels to promote syncytium formation and alter root development. Therefore, the first few days are crucial for parasite success (Matuszkiewicz & Sobczak, 2023). The selected genes played a role in the interaction of other nematode/host species, as well as in response to light stress (Huang et al., 2019). In leaves, the strongest up-regulation at 1 dpt was observed in the ACO1 , NPR1 , Pr1a4 , APX1 , and DHAR genes, while down-regulation was observed for ISC , HY5 , PHYA , and PHYB2 transcripts (Fig. 2 A). Changes in gene expression at 3 dpt were less widespread, with up-regulation of NPR1 , APX1 , and DHAR and down-regulation of ACCase and HY5 . The observed changes in leaves may be attributed to the activation of defense and antioxidant pathways to counteract oxidative stress and damage caused by excessive light. Simultaneously, down-regulation of ACCase , ICS , and HY5 may aim to conserve energy, possibly due to ACCase's role in lipid metabolism and fatty acid synthesis, while also reducing susceptibility to light-induced stress. Interestingly, the tomato root system was more sensitive to applied conditions, even when protected from light. We observed down-regulation of RBOHD and RBOHF and up-regulation of APX1 , SOD , and DHAR among oxidative stress-sensitive genes. Genes involved in SA, JA, and ET signaling were up-regulated. Notably, both PHYA and PHYB2 were strongly down-regulated in roots (Fig. 2 B). At 1 dpt, all the mentioned gene expression changes were observed, while at 3 dpt, only NCED1 (involved in ABA biosynthesis) exhibited statistically significant alterations in roots, suggesting effective adaptation to unfavorable conditions and moderation of stress-related responses. 3.2. Higher light intensities modify PSII photochemistry during G. rostochiensis parasitism The introduction of a second stress factor can significantly alter the plant's response across various dimensions, including physiological, biochemical, and molecular aspects. Therefore, our objective was to investigate how changes in light conditions might impact the susceptibility of tomatoes and whether these alterations would affect the efficiency of the photosynthetic apparatus. Among the six parameters measured, three showed differences associated with the combination of nematode parasitism and the transfer of plants to different light regimes: PSII yield, qP, and R fd . In plants infected with G. rostochiensis and cultivated in low light (LL) conditions, the PSII yield decreased. However, when infected plants were transferred to high light (HL) conditions, their PSII yield levels were similar to those of both control groups of plants. A similar trend was observed for photochemical fluorescence quenching and the parameter representing plant vitality. Infected plants acclimated to LL conditions exhibited a photoinhibition-like response, as evidenced by a decrease in the aforementioned parameters (see Fig. 3 ). 3.3. Light intensity variation is irrelevant to nematodes The interplay between plant roots and cyst nematodes is a highly complex and extended process involving developmental and metabolic changes of plant cells, along with responses to damages, molecular patterns, and effectors associated with parasite activity (Matuszkiewicz & Sobczak, 2023). The observed changes in photosynthetic efficiency and gene expression in non-infected plants may translate into the susceptibility level of the tomato (see Figs. 1 and 2 ). To test this hypothesis, we quantified the number of induced syncytia on tomato root systems in plants that were either continuously grown in low light (LL) conditions or transferred to high light (HL) intensities, and we did not observe any differences (see Fig. 4 ). It is worth mentioning that we did not observe changes in the morphology of the root system in both comparisons, which could potentially interfere with the level of susceptibility. 3.4. Transcriptome analysis reveals DEGs in response to different light conditions during G. rostochiensis parasitism in tomato Transcriptome profiling has become the fundamental diagnostic tool for monitoring plant reactions to stress, with RNA-seq being increasingly favoured over microarrays, systematic RT-qPCR, SAGE, or cDNA-AFLP due to its advantages. Despite the importance of the tomato/PCN interaction, there is still a lack of RNA-seq perspective. In this study, we employed RNA-seq to investigate the regulatory networks active in nematode-infected roots subject to varying light conditions. Our investigation involved analyzing RNA-seq data derived from plants persistently grown under both low light (LL) and high light (HL) conditions, as well as plants subjected to a transition from LL to HL intensities. This comparative analysis aimed to elucidate the complexity of the response to dual stimuli. We also included non-infected plants subjected to an increase in light intensity, characterizing this scenario as a “light response”. An initial noteworthy observation was that, despite the absence of variances in tomato susceptibility to G. rostochiensis across distinct light conditions, we detected substantial alterations in the abundance of differentially expressed transcripts. The smallest number of DEGs, 173, was observed when comparing transcriptomes of infected LL-grown roots to control samples. In HL conditions, this comparison yielded nearly twice as many DEGs (303). The highest number of DEGs emerged in the double stimuli comparison – 2979, while the light response alone resulted in 1746 DEGs (Fig. 5 A). In all comparisons, up-regulated DEGs constituted the predominant group, with the exception of the LL comparison, where down-regulated genes accounted for 68% of the total DEGs (Fig. 5 A). This indicates that, despite relatively small differences observed in DEGs between LL and HL conditions, light exerts a dominant influence on the regulation of gene expression. Moreover, light and nematode response synergistically interact, yielding more DEGs than the sum of individual stimuli. The overlap of the aforementioned groups of DEGs would indicate more general mechanisms of plant reaction to biotic and abiotic stimuli (Fig. 5 B). For example, in the group common for all four comparisons (9 DEGs), we found genes such as Zinc finger protein ( Solyc08g006470.5 ), Peroxidase ( Solyc10g078890.2 ), Glutathione S-transferase ( Solyc09g011540.2 ), and Defensin protein ( Solyc07g007750.3 ). Interestingly, in the common pool of DEGs for nematode-related response (11 DEGs), genes involved in secondary metabolism such as O-methyltransferase ( Solyc06g064510.2 ), Flavin-containing monooxygenase ( Solyc08g068160.2 ), Glycosyltransferase ( Solyc11g007460.1 ), 2-oxoglutarate ( Solyc11g072110.2 ), and ABA 8'-hydroxylase ( Solyc04g078900.3 ) were present. Additionally, the analysis of DEGs revealed transcripts unique for each treatment, indicating specific processes related to the tested variables and their synergy. The smallest number of exclusive DEGs was found in the LL comparison, while the highest number was observed under double stress conditions, totalling 1641 DEGs. Here, we found genes involved in defense response, hormone homeostasis, ROS signalling, and regulation of primary and secondary metabolic processes (Fig. 5 B). Our analysis of DEGs uncovered a remarkable dynamic range of FC-value for several genes throughout the comparisons. However, as usual, the highest changes were detected for genes with very low expression. For a more detailed description, see Supplementary Table 3. 3.5. Categorization of Differentially Expressed Genes Screening large datasets of DEGs encounters problems with drawing more general conclusions; therefore, we employed ShinyGO v.0.77 software for functional categorization of DEGs and gene ontology (GO) enrichment analysis. Genes were classified accordingly to four groups of GO terms: KEGG pathways, biological process (BP), molecular function (MF), and cellular component (CC) (see Fig. 6 and Supplementary Table 4). This approach allowed us to dissect processes being preferentially targeted upon potato cyst nematode parasitism in combination with environmental stimuli. In all analyzed DEG groups, the most general category, “Metabolic Pathways” and also quite capacious “Biosynthesis of Secondary Metabolites” were consistently enriched. Specifically, among the LL-inf DEGs, notable enrichment was observed in “Valine, Leucine, and Isoleucine Degradation” as well as the “MAPK Signaling Pathway” categories (when KEGG pathways define the category) (see Fig. 6 ). Among other categories, the highest enrichment was evident in “Glutamine Family Amino Acid Catabolic Process” and ”Negative Regulation of Hydrolase Activity” categorized accordingly to BP, and in “Fatty Acid Binding” and “Water Channel Activity” when MF determines functional category (refer to Supplementary Table 4). As expected, the HL-inf DEGs were enriched in pathways associated with “Photosynthesis”. Moreover, two additional categories, “Sulfur Metabolism” and “Phenylpropanoid Biosynthesis” were highly enriched (see Fig. 6 ). These findings were consistently supported across both GO terms for BP and MF (refer to Supplementary Table 4). The most pronounced KEGG pathway overrepresentation among the double stimuli DEGs was “Photosynthesis” followed by “Alanine, Aspartate, and Glutamate Metabolism”. Notably, the “Valine, Leucine, and Isoleucine Degradation” pathway also showed enrichment among double stimuli DEGs, highlighting the significance of amino acid metabolism in plants exposed to a complex environment (see Fig. 6 ). Additionally, “Gamma-Aminobutyric Acid Metabolic Process” emerged as a highly enriched category for BP, while “Cytidine Triphosphate (CTP) Synthase Activity” stood out for MF. Moreover, in both category groups – BP and MF, we found expected functional enrichments related to plant-nematode interaction, such as stress response, phytohormone regulation, defense response, cell wall remodelling, and ROS signalling. The association of a gene product with a gene ontology term does not always proportionally reflect its engagement in a given molecular function, cellular component, or biological process. Therefore, dissecting domains from complex multidomain arrangements and conducting enrichment analysis could provide valuable supplementary insights needed for understanding large candidate lists. We found the Analysis of Motif Enrichment (AME; McLeay & Bailey, 2010) particularly helpful in interpreting our DEGs lists (refer to Table 1 ). Among LL-inf DEGs, five significantly enriched motifs were identified. Among them, three were unique for LL-inf: “Hydroxymethylglutaryl-coenzyme A reductases signature 2” (PS00318), “cysteine-rich secretory proteins - CRISP family” (PS01009), and “nitrite and sulfite reductases iron-sulfur/siroheme-binding site” (PS00365). The Hydroxymethylglutaryl-coenzyme A (HMG-CoA) reductase is a key enzyme in the mevalonate pathway, responsible for biosynthesizing isoprenoids including sterols (Friesen & Rodwell, 2004). Both LL-inf and HL-inf DEGs share the enriched motif named “Soybean trypsin inhibitor (Kunitz) protease inhibitors family” (PS00283). Three DEGs groups, the LL-inf, double stimuli, and light response share the enriched signature “Zinc finger RING-type” (PS00518), describing a conserved RING domain pivotal in the ubiquitination pathway. The potential role of proteins with this motif in stress responses could be linked to modulating protein abundance or turnover via ubiquitin-mediated protein degradation (Sun et al., 2019). Among HL-inf DEGs, the “Cytochrome P450 cysteine heme-iron ligand signature” (PS00086) is enriched, while among the double stimuli DEGs, three significantly enriched motifs were found: “Eukaryotic and viral aspartyl proteases active site” (PS00141), “Serine/Threonine protein kinases active-site” (PS00108), and “2Fe-2S ferredoxin-type iron-sulfur binding region” (PS00197). These results were partially confirmed by a similar, recently published tool - Simple Enrichment Analysis (SEA; Bailey & Grant, 2021; refer to Supplementary Table 5). The presence of the aforementioned motifs within protein sequences may be linked to particular condition-specific functions and regulatory roles in plant-biotic interactions. Table 1 The regulatory protein motifs enriched in analyzed datasets . The Analysis of Motif Enrichment (AME) method was employed to identify over-represented motifs within the proteins encoded by DEGs from G. rostochiensis attacked tomato roots under different light conditions. DEG group motif ID (prosite) motif alternative ID consensus p-value adj_p-value E-value LL-inf PS00318 HMG_COA_REDUCTASE_2 LGXLGGGT 5.01e-4 2.50e-3 2.45e0 PS01009 CRISP_1 GRFSALLWXXS 1.44e-3 2.89e-3 2.82e0 PS00365 NIR_SIR SGCXXXCXXXXXXELGL 1.44e-3 2.89e-3 2.82e0 PS00283 SOYBEAN_KUNITZ LXDXNGKXLXXXXXYXL 1.44e-3 2.89e-3 2.82e0 PS00518 ZF_RING_1 CXHXLCXXCL 1.44e-3 4.33e-3 4.23e0 HL-inf PS00283 SOYBEAN_KUNITZ LXDXEGKXLXXXXXYXL 2.34e-4 7.03e-4 6.88e-1 PS00086 CYTOCHROME_P450 FSXGXKXCLG 3.85e-3 7.69e-3 7.52e0 double stimuli PS00518 ZF_RING_1 CXHXLCXXCL 1.75e-6 2.27e-5 2.22e-2 PS00141 ASP_PROTEASE LLSDSGSSXSXL 1.48e-4 1.18e-3 1.16e0 PS00108 PROTEIN_KINASE_ST LXYXDLKXXNLLL 1.48e-4 1.48e-3 1.44e0 PS00197 2FE2S_FER_1 CXXGXCSSC 1.48e-4 1.62e-3 1.59e0 light response PS00518 ZF_RING_1 CXHXLCXXCL 7.42e-6 9.64e-5 9.43e-2 PS00198 4FE4S_FER_1 CXXCXXCXXXCG 9.56e-4 4.77e-3 4.67e0 3.6. Consistency of RNA-seq results with other transcriptomic studies Meta-analyses of transcriptomic results obtained by different methods help identify strong candidates for further research. Despite our RNA-seq data reflecting gene expression changes in whole nematode-infected root systems 14 days post inoculation (since syncytia initiation was not synchronized, root samples contained 10–14 days old feeding structures), we compared the DEGs list to earlier studies on the same species, where cDNA-AFLP was used to monitor transcriptome changes at 1, 3, 7 and 14 days post infection (dpi) with dissected syncytia (Swiecicka et al., 2009; Święcicka et al., 2017). Thirty-four DEGs overlapped between these two approaches − 19 up-regulated, 13 down-regulated, and 2 were stable in the RNA-seq study (refer to Fig. 7 ; Supplementary Table 6). Notably, 65% of the DEGs found in both analyses (22 genes) confirmed expression trends (up- or down-regulation upon nematode infection at any time point), while 35% (12 DEGs) demonstrated an inconsistent expression pattern. Among transcripts with a consistent expression pattern, there are several intriguing candidates for future research. The highly up-regulated gene, Solyc11g021060.2 , encodes the TOMARPIX proteinase inhibitor (with a 3.09 log2FC in the double stress comparison). Conversely, a strongly down-regulated gene observed in the double stress response was Solyc08g014130.3 , which encodes Isopropylmalate synthase (with a -1.44 log2FC). 4. Discussion The divergence in plant responses to the co-occurrence of abiotic and biotic stresses is well known. The variability in these responses is influenced by factors such as the magnitude and duration of the applied stress, the specific plant species involved, and the developmental stage of the plant (Zandalinas & Mittler 2022; Georgieva & Vassileva 2023). Examining the plant's response to a combination of factors involves an assessment of whether a physiological and molecular response is induced. In our study, we identified genes that exhibit differential expression in response to the combination of simultaneous action of environmental stimuli in tomato plants – nematode pest attacking roots and higher light intensity applied to leaves. 4.1. The impact of elevated light intensities on tomato seedlings Plants depend on light for their survival, yet excessive light can have detrimental effects. Beyond a critical threshold, high light (HL) intensity not only directly impairs the photosynthetic apparatus but also induces oxidative stress, leading to photodamage and photoinhibition. Moreover, elevated light levels trigger the generation of reactive oxygen species, increasing the risk of widespread cellular damage (Li et al., 2009; Roeber et al., 2021). To monitor the physiological state of tomato seedlings, we measured chlorophyll a fluorescence. To induce a HL response, we transferred plants from low light intensities (50–60 µmol m − 2 s − 1 ) to HL conditions (350–400 µmol m − 2 s − 1 ). Such levels of light intensities are not unusual in natural environment. However, the seven-fold increase in intensity was expected to modify PSII efficiency (Dietz, 2015). Here, only two parameters demonstrated statistically significant increases 1 and 3 days post-transfer (dpt): PSII quantum yield (Fig. 1 C) and photochemical fluorescence quenching (Fig. 1 E). HL stress typically leads to a loss of photosynthesis efficiency, represented by a decrease in the F v /F m ratio (Baker, 2008). Therefore, we may conclude that our HL conditions were relatively mild. However, it is noteworthy that we avoided a temperature shift of the root system, which is often an overlooked variable in such experiments. Several reports on tomato plants grown under similar light intensities yield inconsistent results. Takagi and colleagues (2019) demonstrated that plants cultivated or transferred to HL intensities exhibited enhanced efficiency of photosystem II (PSII), whereas a study conducted by Pascual and colleagues (2023) found that the application of light intensities around 700 µmol m − 2 s − 1 for a duration of 9 hours resulted in a reduction of PSII efficiency and photosynthetic rate in tomato plants. Even at applied HL intensities, the molecular response was evident, showing the activation of pathways connected with much stronger abiotic or biotic stimuli (Fig. 2 ). During the first days after transfer to HL, we observed up-regulation of typical markers of defense and antioxidant pathways, while genes that may conserve energy and reduce susceptibility to light-induced stress were down-regulated. Surprisingly, we found down-regulation of the ELONGATED HYPOCOTYL5 ( HY5 ) transcription factor, which induction may be a marker of stress response. HY5 is involved in systemic shoot-root signalling in response to light stress as well as in maintaining homeostasis of carbon and nitrogen metabolism under ambient light conditions (Chen et al., 2016). Many of the observed molecular effects were temporal and disappeared after 3 dpt, indicating effective adaptation. However, even short-term response activation may interfere with a particular phase of nematode parasitism, such as the migration phase, syncytium establishment and functioning, which engage distinct pathways (Siddique et al., 2022; Matuszkiewicz & Sobczak, 2023). It is worth noting that shaded roots appear to be more sensitive than illuminated shoots and showed a more complex reaction. Most plant nematode studies overlook this aspect, whereas it is known that direct illumination of roots cultivated in vitro alters their morphology, cellular, biochemical, and molecular responses (Cabrera et al., 2022). Moreover, reducing gas exchange is an additional modifying factor for root growth phenotype (Matuszkiewicz et al., 2019). To minimize the influence of such factors, we routinely use root shading and air-permeable Petri plate sealing instead of Parafilm. 4.2. Light-mediated modulation of root response to G. rostochiensis The core premise of this study hinges on the understanding that exploring specific aspects of plant interactions with the environment or other organisms in laboratory conditions often yields results that inadequately reflect the phenomena observed in natural settings. Consequently, the anticipation of light-mediated modifications in root responses following nematode attacks was justified, yet the extent and the specific pathways involved remain to be fully elucidated (Pandey et al., 2015; Zandalinas & Mittler, 2022). The decrease in PSII yield observed in infected tomato plants cultivated in LL conditions aligns with expectations. However, infected plants transferred to higher light intensities exhibited a PSII yield comparable to that of control plants. Overall, it can be inferred that infected plants under LL conditions manifested a photoinhibition-like response (Fig. 3 ). This observation is consistent with findings by Schmitz et al. (2006), who demonstrated similar fluorescence parameter alterations in sugar beet plants infected with beet cyst nematodes ( H. schachtii ) under moderate light intensities (200 µmol m − 2 s − 1 ). During the early stages of beet infection by H. schachtii , reductions in photosynthetic efficiency occur, followed by declines in transpiration and photosynthetic processes. These declines are attributed to stomatal closure, impaired mineral nutrient uptake, and reductions in chlorophyll and nitrogen content in the leaves of infected plants. However, changes in photosynthetic efficiency in H. schachtii -infected A. thaliana appear slightly different (Labudda et al., 2018). In this case, only minor changes in photosynthetic efficiency occur, which is consistent with our results, including the stable level of tomato seedling susceptibility (Fig. 4 ). Interestingly, in our previous studies, we documented changes in the susceptibility of A. thaliana infected with H. schachtii , which were dependent on the aforementioned ventilation conditions of the Petri plates. This highlights the importance of considering such multivariate analyses in interpreting experimental outcomes (Matuszkiewicz et al., 2019). 4.3. Tomato transcriptomic reprogramming under combined environmental stimuli Transcriptome profiling using RNA-seq has become a pivotal approach for diagnosing plant responses to stress. Our investigation encompassed nematode-infected and uninfected tomato roots grown persistently under both low and high light conditions, as well as those transferred from low to higher light intensities. Despite the stable susceptibility of tested tomato cultivar to G. rostochiensis across varying light conditions, significant changes in the abundance of differentially expressed root transcripts were observed. Our findings underscore the substantial influence of light on gene expression. Furthermore, the synergistic interaction between light and nematode responses produced more DEGs than the sum of individual stimuli. Such light stimulation, crucial for activating defense/resistance responses, has also been observed in plant-pathogen interactions, particularly with bacterial pathogens (Trotta et al., 2014). Another example of this mechanism was described by Gao et al. (2020), who demonstrated that nucleotide-binding NLR Rpi-vnt1.1 proteins require light for conferring resistance against Phytophthora infestans races, specifically those releasing the effector protein AVRvnt1. Analyzing the DEGs with representation enrichment tools across all generated RNA-seq data, we consistently found two KEGG categories overrepresented, namely “Metabolic Pathways” and “Biosynthesis of Secondary Metabolites” which serve as nonspecific markers of environmental factor response (Fig. 6 ). However, among the DEGs, there were some more specific enrichments, such as “Valine, Leucine, and Isoleucine Degradation” and the “MAPK Signaling Pathway” in the LL-inf group. The degradation of branched-chain amino acids (BCAAs) is connected with energy production and nitrogen recycling and may be part of the classical growth-defense trade-off (Hildebrandt et al., 2015; He et al., 2022). The MAPK signaling pathway is also typical in plant-pathogen interactions, involved in signal transduction to maintain ROS production and integrate signals from JA and SA pathways (Taj et al., 2010). New categories emerged in the group of DEGs after nematode infection of plants grown under HL conditions, namely “Photosynthesis”, “Sulfur Metabolism” and “Phenylpropanoid Biosynthesis”. The double stimuli DEGs were overrepresented by “Photosynthesis”, “Alanine, Aspartate, and Glutamate Metabolism” and another amino acid-related pathway “Valine, Leucine, and Isoleucine Degradation”. These pathways emphasize the importance of amino acid metabolism in plants exposed to complex environmental stimuli, including moderate parasite pressure and extensive light intensity variation. Nematode infection evokes multidirectional changes in roots involving amino acids as substrates for hormones and newly synthesized proteins needed for developmental reprogramming during syncytium formation and feeding parasitic nematodes. The observed synergy between the responses triggered by light exposure and nematode infection indicates substantial enrichment in processes essential for plant adaptation to stress conditions, such as energy allocation, phytohormone crosstalk, and enhanced secondary metabolite production. The integration of these responses is likely context-dependent, specific to environmental stimuli, the type of plant-pathogen interaction, and their intensity. Gene ontology analysis was supplemented with motif enrichment approaches (McLeay & Bailey, 2010). For example, the “cysteine-rich secretory proteins - CRISP family” motif was enriched in the LL DEG group. CRISPs belong to a family of proteins with conserved cysteine residues arrangements present in animals and involved in gamete interaction (Gonzalez et al., 2021). In plants, proteins with that motif could be found among pathogenesis-related proteins (Han et al., 2023). Another pathogenesis-related and enriched motif was found in LL-inf and HL-inf DEGs – “Soybean trypsin inhibitor (Kunitz) protease inhibitors family”, typically occurring in protease inhibitors commonly linked to defense responses. Interestingly, we also observed enriched signatures of antagonistic activities, such as “Eukaryotic and viral aspartyl proteases active site”, typical for proteolytic enzymes involved in stress-related processes such as protein degradation, plant senescence, and programmed cell death (Simões & Faro, 2004). The above-listed statistically significant molecular characteristics are complex and difficult to summarize. We may speculate that in compatible plant-nematode interactions, an additional environmental factor (e.g., higher light intensities) can both enhance and inhibit specific plant defense responses. In the face of such antagonistic responses, other pathways are activated, which on a molecular level resemble the priming phenomenon (Nair et al., 2022). Whether resulting stress tolerance was enhanced requires further studies with higher parasite inocula, more HL levels and different stressors. 5. Conclusion The presence of abiotic and biotic stimuli combinations induces a different response, involving a greater number of genes or biochemical pathways compared to single stressors. This response is characterized by species specificity and dependency on the type and intensity of the applied factor. In the context of interactions between plant parasitic nematodes and elevated light intensity, the important role of amino acid metabolism and hormonal regulation emerges. Processes traditionally classified as “plant-pathogen related” appear to exhibit diminished relevance in the context of complex environmental factors. Therefore, research on genes implicated in the response to stress combinations is crucial for comprehending the molecular pathways associated with such responses and for the development of more resilient cultivars, particularly in the face of climate changes. Declarations Acknowledgments We thank Dr Aska Goverse (Laboratory of Nematology, Wageningen University, the Netherlands) for kindly sharing nematode cysts. We would like to thank Dr Mirosław Sobczak (Department of Botany, Institute of Biology, WULS) for sharing the quarantine laboratory. We are grateful to the Polish National Science Centre for funding ( Project No 2017/25/B/NZ9/02574). Author information Authors and affiliations Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw University of Life Sciences-SGGW, 02-776, Warsaw, Poland Mateusz Matuszkiewicz, Magdalena Święcicka, Marek Koter & Marcin Filipecki Contributions MM & MF: developed the hypothesis and devised the research plan: MF: supervised the experiment; MM, MŚ and MK performed the experiments; MM, MŚ, MK & MF analyzed the results; MM: prepared the figures, MM: wrote the manuscript with the contribution of all authors. The authors read and approved the final manuscript. Corresponding author Correspondence to Marcin Filipecki Data availability statement The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Funding This study was financially supported by National Science Centre, grant no. 2017/25/B/NZ9/02574. 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(2015) Light-induced systemic resistance in tomato plants against root-knot nematode Meloidogyne incognita . Plant Growth Regul 76:167–175. https://doi.10.1007/s10725-014-9986-9 Zandalinas SI, Fritschi FB, Mittler R (2021) Global Warming, Climate Change, and Environmental Pollution: Recipe for a Multifactorial Stress Combination Disaster. Trends Plant Sci 26(6):588–599. https://doi.org/10.1016/j.tplants.2021.02.011 Zandalinas SI, Mittler R (2022) Plant responses to multifactorial stress combination. The New phytologist 234(4):1161– 1167. https://doi.org/10.1111/nph.18087 Zandalinas SI, Peláez-Vico MÁ, Sinha R, Pascual LS, Mittler R (2023) The impact of multifactorial stress combination on plants, crops, and ecosystems: how should we prepare for what comes next? Plant J https://doi.org/10.1111/tpj.16557 Supplementary Files SupplementaryTable1.xlsx SupplementaryTable2.xlsx SupplementaryTable3.xlsx SupplementaryTable4.xlsx SupplementaryTable5.xlsx SupplementaryTable6.xlsx Cite Share Download PDF Status: Published Journal Publication published 14 Aug, 2024 Read the published version in Journal of Applied Genetics → Version 1 posted Reviewers agreed at journal 05 Mar, 2024 Reviewers invited by journal 05 Mar, 2024 Editor assigned by journal 27 Feb, 2024 First submitted to journal 22 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3982446","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276507070,"identity":"087aeb2e-e138-4678-aa21-dbc07b2a342e","order_by":0,"name":"Mateusz Matuszkiewicz","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-4320-7103","institution":"Warsaw University of Life Sciences: Szkola Glowna Gospodarstwa Wiejskiego w Warszawie","correspondingAuthor":true,"prefix":"","firstName":"Mateusz","middleName":"","lastName":"Matuszkiewicz","suffix":""},{"id":276507071,"identity":"c8f98759-6302-41ac-8a79-6769f766612b","order_by":1,"name":"Magdalena Święcicka","email":"","orcid":"","institution":"Warsaw University of Life Sciences: Szkola Glowna Gospodarstwa Wiejskiego w Warszawie","correspondingAuthor":false,"prefix":"","firstName":"Magdalena","middleName":"","lastName":"Święcicka","suffix":""},{"id":276507072,"identity":"b1c1e2bf-3f10-45aa-bcd5-7c52fc6a78d8","order_by":2,"name":"Marek Koter","email":"","orcid":"","institution":"Warsaw University of Life Sciences: Szkola Glowna Gospodarstwa Wiejskiego w Warszawie","correspondingAuthor":false,"prefix":"","firstName":"Marek","middleName":"","lastName":"Koter","suffix":""},{"id":276507073,"identity":"1f1f5cff-5810-412e-bde5-ae48ff9dd9f4","order_by":3,"name":"Marcin Filipecki","email":"","orcid":"https://orcid.org/0000-0003-4107-2484","institution":"Warsaw University of Life Sciences: Szkola Glowna Gospodarstwa Wiejskiego w Warszawie","correspondingAuthor":false,"prefix":"","firstName":"Marcin","middleName":"","lastName":"Filipecki","suffix":""}],"badges":[],"createdAt":"2024-02-23 16:05:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3982446/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3982446/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s13353-024-00897-6","type":"published","date":"2024-08-14T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52295845,"identity":"5a3af49f-fed4-4d7c-a2df-295115756741","added_by":"auto","created_at":"2024-03-08 17:57:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":48979,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChlorophyll a fluorescence in tomato seedlings after transferring to elevated light intensities\u003c/strong\u003e. A: maximum quantum efficiency of PSII photochemistry (F\u003csub\u003ev\u003c/sub\u003e/F\u003csub\u003em\u003c/sub\u003e); B: PSII quantum yield in light-adapted leaves (F\u003csub\u003ev’\u003c/sub\u003e/F\u003csub\u003em’\u003c/sub\u003e); C: PSII quantum yield (PSII Yield); D: non-photochemical quenching (NPQ); E: photochemical fluorescence quenching (qP); F: plant vitality (R\u003csub\u003efd\u003c/sub\u003e). Distribution of data was presented in boxplots (median, quartiles, and potential outliers) from three independent experiments, each containing 3-5 plants per treatment. Statistical analysis was performed by using Two Way Analysis of Variance (ANOVA). Bonferroni test was used for correction for multiple comparisons.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/a6be291fd3cdc452781e46af.png"},{"id":52295397,"identity":"dee2bb69-2416-49c7-b19e-cad68146b555","added_by":"auto","created_at":"2024-03-08 17:49:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":89278,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene expression analysis in leaves and roots of tomato plants\u003c/strong\u003e. qRT-PCR analysis of marker genes linked to photochromes, ROS metabolism, and phytohormones related to biotic stress were examined in leaves (A) and roots (B) of tomato plants after transferring to elevated light intensities. The expression levels of target genes were quantified with reference to the expression of \u003cem\u003eRPL8\u003c/em\u003eand \u003cem\u003eSAND\u003c/em\u003e compared to the control (plants grown in low light intensities). The relative expression levels are shown as logarithm of fold changes relative to the copy number of a particular mRNA gene in the control sample. Results are the means (± SEM; standard error of mean) from three independent experiments. The asterisks indicate the significant differences from the control as revealed by REST (Pfaffl et al., 2002) (p\u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/2f198519df6daf1973db51c7.png"},{"id":52295064,"identity":"7b9e07b2-e865-4844-9d00-42ab811396e8","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":47973,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChlorophyll a fluorescence in infected tomato seedlings after transferring to elevated light intensities\u003c/strong\u003e. A: maximum quantum efficiency of PSII photochemistry (F\u003csub\u003ev\u003c/sub\u003e/F\u003csub\u003em\u003c/sub\u003e); B: PSII quantum yield in light-adapted leaves (F\u003csub\u003ev\u003c/sub\u003e’/F\u003csub\u003em\u003c/sub\u003e’); C: PSII quantum yield (PSII Yield); D: non-photochemical quenching (NPQ); E: photochemical fluorescence quenching (qP); F: plant vitality (R\u003csub\u003efd\u003c/sub\u003e). Distribution of data was presented in boxplots (median, quartiles, and potential outliers) from three independent experiments, each containing 3-5 plants per treatment. Statistical analysis was performed by using One Way Analysis of Variance (ANOVA). Tukey test was used for correction for multiple comparisons.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/4f211846576cee46267c6e09.png"},{"id":52295395,"identity":"2b323cc2-3d7c-49b8-a017-34a83d80c4f0","added_by":"auto","created_at":"2024-03-08 17:49:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":7841,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNematode infection assay on tomato roots infected by Globodera rostochiensis pathotype Ro1. \u003c/strong\u003eThe numbers of developed syncytia were counted at 14 dpi and represented as box-plots. Data was collected from three independent experiments. Statistical analysis was performed by using t-test (p\u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/937eccbefba10db080ffd3d1.png"},{"id":52295062,"identity":"860ffc6e-f463-40c0-87b2-ff33123b2ee6","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":74871,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNumber of DEGs after infections with \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG.rostochiensis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eat 14 dpi in roots containing syncytia\u003c/strong\u003e. (A) Total number of DEGs in response to different conditions. (B) Venn diagram presenting the DEGs grouped according to the changes in their expression relative to the type of comparison.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/b0c4b2fb81cb1a5ca8293f20.png"},{"id":52295067,"identity":"aa0f7dbc-9374-44ab-aa1f-64279f9ac3a9","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":201032,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGene ontology enrichment analysis within DEG groups\u003c/strong\u003e. The KEGG pathways enriched in tomato roots due to \u003cem\u003eG. rostochiensis\u003c/em\u003eparasitism under dfferent light intensities.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/27bd0cb7ae6fbb87b0943a74.png"},{"id":52295846,"identity":"80eceaa4-b3a1-4c78-8acc-e1bf36adafd3","added_by":"auto","created_at":"2024-03-08 17:57:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":41355,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of tomato transcriptomic responses to \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eG. rostochiensis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e parasitism.\u003c/strong\u003e Venn diagrams showing the number of mapped DEGs described here and in cDNA-AFLP approaches.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/f20cb86dc4049840d4be6909.png"},{"id":63071225,"identity":"c14ce44c-160f-498a-b9bb-5108a37326e4","added_by":"auto","created_at":"2024-08-22 20:04:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1417205,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/4c2ea384-5ca0-4cf9-bda1-5d862dccdea8.pdf"},{"id":52295399,"identity":"57ad1426-bbd7-400d-9d2c-d0fb04ed0cd3","added_by":"auto","created_at":"2024-03-08 17:49:16","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":15448,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/9fd33a6236d7fe5f25bbd7c7.xlsx"},{"id":52295070,"identity":"0f611096-15b5-4f77-9e65-9c860ed98ac8","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":10597,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/9ee31100ff174d3df2ee89a1.xlsx"},{"id":52295071,"identity":"2fdcafbd-ea44-4755-b0ca-935e8dd2a97c","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"xlsx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":624066,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/2f8a839b8715f0609539c354.xlsx"},{"id":52295069,"identity":"5e297149-93cc-499b-8623-224fa46aa805","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"xlsx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":56343,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/f902fd693b172f8924511fbd.xlsx"},{"id":52295400,"identity":"2cc935da-9ae9-498b-8400-ea446c23428c","added_by":"auto","created_at":"2024-03-08 17:49:16","extension":"xlsx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":17885,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/b825cfcba7d2804c84fff7d4.xlsx"},{"id":52295073,"identity":"35f4397b-6601-40d3-be66-5316e1f40d29","added_by":"auto","created_at":"2024-03-08 17:41:16","extension":"xlsx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":103252,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3982446/v1/0445218dc0f48518d0865f8c.xlsx"}],"financialInterests":"","formattedTitle":"Identification of genes involved in the tomato root response to Globodera rostochiensis parasitism under varied light conditions","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePlants have evolved to thrive in environmental conditions which vary within the range of variability characteristic of a given climatic zone and ecosystem. Moreover they try to endure more or less regular pression of biotic threats such as diseases and pests. On top of this there is a pressure of climate changes including recent anthropogenic global warming and environment pollution. All of these factors, usually acting simultaneously, affect crop plant growth development and yield making the study of adaptation mechanisms increasingly important (Zandalinas \u0026amp; Mittler 2022). The ability to detect and adjust reactions applies to both abiotic (drought, salinity, heat, cold, chilling, freezing, nutrient deficiency, varying light intensities, UV radiation, ozone exposure, and anaerobic conditions caused by flooding) and biotic stimuli (bacteria, fungi, viruses, oomycetes, and a multitude of herbivorous animals) (Zandalinas et al., 2023). Hans Selye (1936) postulated conception of stress response for living organisms, which can be synthetized to: \u0026ldquo;All agents can serve as stressors, inducing both stress and specific actions. These caused coexistence of stressor-specific and general non-specific responses\u0026rdquo;. \u0026ldquo;True stress\u0026rdquo; occurred when a specific threshold of a stressor surpasses the compensatory capacity of the plant. The stress tolerance threshold is contingent not solely upon the plant species but also on the nature of applied stressors and the conditions of the plant. Additionally, variations exist among plants in terms of their capacity to cope with stress. Is mean that stress is a dose-dependent and species-specific type of plant response (Lichtenthaler 1998; Georgieva \u0026amp; Vassileva 2023). Consequently, plants constantly confront diverse combinations of several stimuli or stressors (Anwar et al., 2021). Zandalinas and colleagues (2021) introduced the term \u0026ldquo;multifactorial stress combination\u0026rdquo; (MFSC) to characterize situations where three or more stress-inducing factors co-occur. Even the number of MFSC is very high, the number of physiological and molecular responses tend to integrate towards relatively limited repertoire of adaptive or defense mechanisms. Consequently the individual impact of a given stressor may be different than their collective effect showing synergy or antagonism. Importantly the molecular outcome of underlaying mechanisms is distinctly discernible at the level of the plant's transcriptome, proteome, or metabolome being the source of potential targets to enhance crop performance via e.g. genome editing (Zandalinas et al., 2023).\u003c/p\u003e \u003cp\u003eMost of studies with combined stress conditions indicate that there is a negative impact of abiotic stress (mainly drought and salinity stress) on pathogen resistance (Suzuki et al., 2014). There are however some exceptions such as the beneficial role of salt-related stress on the powdery mildew resistance of barley (Wiese et al., 2004). Such unpredictable reaction may depend on the dual role of ROS and the specific and local interplay of ROS stoichiometry and pathogen effectors (Gadjev et al., 2006; Siddique et al., 2014).\u003c/p\u003e \u003cp\u003ePlant parasitic nematodes are among the most significant pests, with those belonging to the genera \u003cem\u003eGlobodera\u003c/em\u003e and \u003cem\u003eHeterodera\u003c/em\u003e, known as cyst-forming nematodes, ranking at the top of the list, and causing annual losses ranging from US\u003cspan\u003e$\u003c/span\u003e 80 to 358\u0026nbsp;billion (Jones et al., 2013). These nematodes infect roots, suppressing the defense response and inducing plant cells to form syncytia specialized in sustaining the nutrition of developing larvae. During syncytium formation, numerous morphological, ultrastructural, physiological, and molecular changes occur in the infected plant. Particularly, the initial syncytial cell undergoes significant enlargement, the nucleus swells and the central vacuole is replaced by smaller ones. Mitochondria, plastids, endoplasmic reticulum, lipid bodies, and ribosomes proliferate, causing the cytoplasm to become denser. The syncytium gradually enlarges through partial dissolution of cell walls and fusion of neighbouring protoplasts (Matuszkiewicz \u0026amp; Sobczak, 2023). All these changes are accompanied by local or systemic alterations in the expression of genes related to various processes such as the cell cycle, cell wall modification, ROS homeostasis, and defense. Additionally, there is a shift in the expression of genes involved in signal transduction and hormonal regulation (Matuszkiewicz et al., 2018; Siddique et al., 2022).\u003c/p\u003e \u003cp\u003eDespite advancements in understanding plant responses to various stimuli, there remains a limited number of studies examining the concurrent effects of biotic or abiotic stressors alongside plant-parasitic nematodes. Kutyniok et al. (2014a) conducted a study investigating the impact of nematode (\u003cem\u003eH. schachtii\u003c/em\u003e) parasitism on Arabidopsis plants concurrently attacked by aphids (\u003cem\u003eMyzus persicae\u003c/em\u003e). Their findings indicated that the sequence of parasite feeding on a host plant reciprocally affected their fitness and reproductive success. Notably, the effect of beet cyst nematode on aphid performance was found to be modified by nitrate fertilization (Kutyniok \u0026amp; M\u0026uuml;ller, 2013). Additionally, the researchers presented microarray transcriptome data illustrating that aphid infestation influenced nematode-induced transcription in roots, but not vice versa (Kutyniok et al., 2014b). Kammerhofer et al. (2015) further explored the communication between roots and leaves subjected to biotic stimuli. They simultaneously infested Arabidopsis roots with \u003cem\u003eH. schachtii\u003c/em\u003e and leaves with \u003cem\u003eFrankliniella occidentalis\u003c/em\u003e or \u003cem\u003eTetranychus urticae\u003c/em\u003e. The study revealed that \u003cem\u003eH. schachtii\u003c/em\u003e triggered hormone-related systemic responses, leading to elevated levels of JA, SA, and IAA in aboveground parts of plants. These findings elucidated the altered susceptibility and/or attraction of shoot invaders to these plants. Interestingly, while shoot-feeding herbivores (thrips and spider mites) modified Arabidopsis phytohormone homeostasis, only \u003cem\u003eF. occidentalis\u003c/em\u003e increased susceptibility to \u003cem\u003eH. schachtii\u003c/em\u003e by altering JA and its active conjugate JA-Ile in the roots. Several studies have also investigated the combined effects of abiotic stress and nematode parasitism. For example, in-depth physiological studies on upland rice led to the conclusion that the presence of plant-parasitic nematodes exacerbates the detrimental effects of drought (Audebert et al., 2000). Yang et al. (2015) discovered that night time irradiation of tomato and watermelon plants with different light qualities influenced susceptibility to the root knot nematode \u0026ndash; \u003cem\u003eMeloidogyne incognita\u003c/em\u003e. Notably, treatment with red light significantly boosted immunity, correlating with increased expressions of PR1 (a marker gene of SA signalling activation) and PI1 (a marker gene of JA signalling). Moreover, this treatment improved plant growth and leaf CO\u003csub\u003e2\u003c/sub\u003e assimilation. The molecular investigation of the combination of drought stress and \u003cem\u003eH. schachtii\u003c/em\u003e infection was conducted by Atkinson et al. (2013) in \u003cem\u003eArabidopsis\u003c/em\u003e roots. Detailed transcriptome analysis showed that 47% of genes expressed differentially during drought stress, and 85% of the genes involved in the response to \u003cem\u003eH. schachtii\u003c/em\u003e parasitism did not undergo differential expression under cumulative stress. Further studies focused on selected genes - RAPID ALKALINIZATION FACTOR-LIKE8 (\u003cem\u003eAtRALFL8\u003c/em\u003e), METHIONINE GAMMA LYASE (\u003cem\u003eAtMGL\u003c/em\u003e), and AZELAIC ACID INDUCED1 (\u003cem\u003eAtAZI1\u003c/em\u003e) - highlighting the intricate interplay among various stress responses in plants, affirming the significance of investigating combined stress factors.\u003c/p\u003e \u003cp\u003eSimilar to other abiotic stresses, substantial changes in light intensity and quality have negative effects on plant growth due to the deregulation or damage of photosynthetic machinery by excess energy. Plants have therefore evolved various protective and compensating mechanisms that monitor the intensity, wavelength, duration, and direction of light, and respond to mitigate the negative effects of harsh conditions (Roeber et al., 2021). Chloroplasts seem to play a central role not only in sensing and responding to environmental stresses but also in orchestrating immune reactions against plant pathogens. They are well-adapted for this role as they are the primary source of reactive oxygen species (ROS) and the starting point of salicylic acid (SA) biosynthesis in plants (Trotta et al., 2014; Lefevere et al., 2020). Consistently, light stress induces systemic acclimatization, enhancing tolerance to virulent bacteria through local and systemic changes in the pool of ROS, SA, and ethylene (Szechyńska-Hebda et al., 2010). The data mentioned clearly indicate numerous points of intersection in the responses to biotic stress and light stress.\u003c/p\u003e \u003cp\u003eWe conducted this study to enhance the understanding of how different light intensities influence the molecular response of tomato (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e) roots to parasitism by the potato cyst nematode (\u003cem\u003eGlobodera rostochiensis\u003c/em\u003e).\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Plant material\u003c/h2\u003e \u003cp\u003eSeeds of tomato (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e) cv. Moneymaker were used in experiments. Seeds were surface-sterilized in 1.5% sodium hypochlorite for 10 min and subsequently rinsed three times in distilled water. Two seeds per Petri dish (100 mm in diameter) were sowed on medium containing 1.5% (w/v) B5 medium (Gamborg\u0026rsquo;s basal salt mixture, 2% (w/v) sucrose, and 1.5% (w/v) agar, pH 6.2) and subsequently grown at a long day regime (16 : 8 h light/dark, 22 : 20\u0026deg;C, 70% HR). Light intensity was between 50\u0026ndash;60 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e \u0026ndash; low light conditions (LL) and 350\u0026ndash;400 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e \u0026ndash; high-light conditions (double stimuli; HL). Petri dishes were sealed with gas permeable medical adhesive tape (3M\u0026trade; Micropore\u0026trade;). To avoid root system illumination Petri dishes were covered in black envelopes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Nematode assay\u003c/h2\u003e \u003cp\u003eCysts of potato cyst nematode (\u003cem\u003eG. rostochiensis\u003c/em\u003e Woll.) pathotype Ro1 were surface sterilized in 90% (v/v) ethanol for 15 s following a 10 min incubation in 1.3% (w/v) sodium hypochlorite. Then cysts were washed 3 times in sterile water, and rehydrated in sterile potato root diffusates in the dark at 20\u0026deg;C for one week. The potato root diffusate was made according to method established by Evans (1983). Hatched pre-parasitic J2s were sterilized by 0.05% HgCl\u003csub\u003e2\u003c/sub\u003e for 5 min and immediately washed five times in distilled water. After sterilization suspended in sterile distilled water nematodes were check for their vitality and concentration.\u003c/p\u003e \u003cp\u003eFourteen-day-old tomato seedlings were inoculated with 200\u0026ndash;250 J2s under sterile conditions. Inoculated plates were kept in the dark for 6 h, and subsequently transferred into a growth chamber under high-light conditions. Two plants were used in one Petri dish and the experiments were repeated three times with 10 plants per genotype in one replicate. The numbers of induced syncytia per root system were counted at 14 dpi and the data were analyzed by a t-test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Chlorophyll a fluorescence measurement\u003c/h2\u003e \u003cp\u003eChlorophyll a fluorescence was determined using a pulse amplitude-modulated FluorCam 800 MF PSI device (Brno, Czech Republic) on whole \u003cem\u003eS. lycopersicum\u003c/em\u003e leaves. Before taking measurements, the plants underwent a 30-minute period of dark adaptation to determine the initial fluorescence (F\u003csub\u003eo\u003c/sub\u003e) and the maximum fluorescence (F\u003csub\u003em\u003c/sub\u003e). Accordingly to methodology established by Baker (2008) the maximum quantum efficiency of PSII \u0026ndash; F\u003csub\u003ev\u003c/sub\u003e/F\u003csub\u003em\u003c/sub\u003e=(F\u003csub\u003em\u003c/sub\u003e\u0026ndash;F\u003csub\u003eo\u003c/sub\u003e)/F\u003csub\u003em\u003c/sub\u003e, non-photochemical quenching \u0026ndash; NPQ=(F\u003csub\u003em\u003c/sub\u003e\u0026ndash;F\u003csub\u003emʹ\u003c/sub\u003e)/F\u003csub\u003emʹ\u003c/sub\u003e, photochemical quenching \u0026ndash; qp=(F\u003csub\u003emʹ\u003c/sub\u003e\u0026ndash;F\u003csub\u003et\u003c/sub\u003e)/(F\u003csub\u003emʹ\u003c/sub\u003e\u0026ndash;F\u003csub\u003e0ʹ\u003c/sub\u003e), and the operating quantum efficiency of PSII known as PSII quantum yield \u0026ndash; ΦPSII=(F\u003csub\u003emʹ\u003c/sub\u003e\u0026minus;F\u003csub\u003es\u003c/sub\u003e)/F\u003csub\u003emʹ\u003c/sub\u003e were calculated. The plant vitality index R\u003csub\u003efd\u003c/sub\u003e was calculated by the FluorCam 7.0 software. Data were further statistically analyzed using two-way ANOVA with Bonferroni test for correction for multiple comparisons (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. RNA Extraction for Transcriptomic Analysis\u003c/h2\u003e \u003cp\u003eTotal RNA was isolated from uninfected plants (both leaves and roots) at 1st and 3rd days post transfer (dpt), and infected root segments, along with appropriate controls, were collected 14 days post-infection. The isolation was performed using the Universal RNA Purification Kit (Eurx, Gdańsk, Poland) following the manufacturer's protocol, which included on-column digestion of DNA. RNA integrity was evaluated on 1% agarose gel. However RNA yield and purity were estimated using the NanoDrop ND-1000 (NanoDrop Products, Wilmington, DE, United States), and the Experion (Bio-Rad, Miasto, CA, United States). Total RNA with RQI values\u0026thinsp;\u0026ge;\u0026thinsp;9.0 and 28S:18S ratios\u0026thinsp;\u0026ge;\u0026thinsp;1.2 was used in the RNA-sequencing analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. RNA-Sequencing Analysis\u003c/h2\u003e \u003cp\u003eThe Illumina HiSeq2500 platform (Illumina Inc., San Diego, CA, United States) was used for RNA-sequencing (RNA-seq) analysis. To obtain a comprehensive overview of the tomato root transcriptome and transcript profiles in response to \u003cem\u003eG. rostochiensis\u003c/em\u003e parasitism under increased light intensity, three biological replicates were used to construct the libraries. Genomed SA (Warsaw, Poland) conducted paired-end sequencing.\u003c/p\u003e \u003cp\u003eIn all analytical procedures, the ITAG4.1 Tomato Genome Annotation Release file, obtained from Solgenomics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://solgenomics.net\u003c/span\u003e\u003cspan address=\"https://solgenomics.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), was employed. Initially, the ITAG4.1_gene_models.gff file was subjected to conversion into the ITAG4.1_gene_models.gtf file format, utilizing the gffread software version 0.11.7 (Pertea \u0026amp; Pertea 2020). The quality assessment and trimming of fastq files were executed with Trim Galore version 0.6.4 (Krueger et al., 2023). Subsequently, the STAR aligner version 2.7.3a (Dobin et al., 2013) was utilized to index the genome and align reads to the tomato genome assembly build 4.00. Mapped reads or fragments, in the case of paired-end data, were associated with genomic features, generating bam files, through the featureCounts function from the Rsubread package version 2.14.2 (Liao et al., 2019), integrated into R software version 4.3.0. The resulting count matrix was then subjected to the identification of Differentially Expressed Genes (DEGs) employing the DESeq2 package version 1.40.2 (Love et al., 2014) within R software version 4.3.0. The criteria for DEG selection were set at |log2-fold change (FC)| \u0026gt; 1.0 and adjusted P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Finally, DEGs were annotated by referencing the ITAG4.1_descriptions.txt file from Solgenomics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://solgenomics.net\u003c/span\u003e\u003cspan address=\"https://solgenomics.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with the aid of the dplyr package version 1.1.3 (Wickham et al., 2023) within R software version 4.3.0. The software tools, namely gffread, Trim Galore, and STAR, were executed on an operating system environment running Ubuntu 20.04.5 LTS (GNU/Linux 4.4.0-19041-Microsoft x86_64). Gene ontology enrichment analysis was performed with ShinyGO v.0.77 (Ge et al. 2020) The sequencing data are accessible in SRA database (PRJNA1078223).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Quantitative Real-Time RT-PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eRNA was isolated using the Universal RNA Purification Kit (Eurx, Gdansk, Poland) according to the manufacturer's protocol with on-column digestion of DNA. RNA integrity was assessed using a 1% agarose gel, while RNA yield and purity were determined using the NanoDrop ND-1000 (NanoDrop Products, Wilmington, DE, USA). A total of 1 \u0026micro;g of RNA was reverse transcribed using (N) 6 random hexamer primers and following the conditions specified in the \u003cem\u003eQuantiTect\u003c/em\u003e Reverse Transcription Kit (Qiagen). Quantitative RT-PCR was performed in triplicate using the \u003cem\u003eQuantiTect\u003c/em\u003e SYBR Green PCR Kit (Qiagen) with the Bio-Rad CFX96 Touch\u0026trade; Real-Time PCR Detection System (Bio-Rad, Niasto, CA, USA). The reaction conditions were as follows: denaturation at 95\u0026deg;C for 3 min, and 40 cycles of 95\u0026deg;C for 10 s and 60\u0026deg;C for 30 s. The reaction mixture, with a total volume of 20 \u0026micro;L, consisted of 8 \u0026micro;L of cDNA (2.5 ng/\u0026micro;L), 1 \u0026micro;L for each gene-specific primer (10 mM), and 10 \u0026micro;L of the 2\u0026times; Ready Fast Green Mix reagent (from Biochem Development, Gdańsk, Poland). Two tomato genes, SAND (SGN-U316474) and RPL8 (NM_001247186), were used as internal reference genes. The transcript level of the selected genes was normalized to that of SAND and RPL8 using the \u003csup\u003eΔΔ\u003c/sup\u003eCt method (Livak and Schmittgen, 2001). The significance of differences from the control was revealed by REST (Pfaffl et al., 2002). After the PCR, product melting curves were generated to verify the purity of the amplicons. The same methodology as described above was used for validation of the RNA-seq data (Supplementary Table\u0026nbsp;1). The list of primers used in qRT-PCR are included in the supplementary materials (Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Effects of elevated light intensities on photosynthetic performance and molecular response in tomato seedlings\u003c/h2\u003e \u003cp\u003eCommonly employed non-invasive assessments of a plant's physiological state rely on measuring chlorophyll a fluorescence. In this study, we aimed to investigate the combined reaction to high light intensity and nematode infection therefore the conditions typically used in tomato/potato cyst nematode experiments were slightly modified (Dąbrowska-Bronk et al., 2015; Święcicka et al., 2017). Tomato seedlings were exposed to elevated light intensities being placed on a medium in a plastic Petri dish sealed with permeable medical adhesive tape. The shoots remained uncut, while the roots were shielded with a black envelope. The maximum light intensity was adjusted to a level that did not cause temperature shifts. The impact of transferring tomato plants from low light (LL) to high light (HL) conditions on photosystem II (PSII) photochemistry was assessed using various chlorophyll fluorescence-related parameters, including maximum quantum efficiency of PSII (F\u003csub\u003ev\u003c/sub\u003e/F\u003csub\u003em\u003c/sub\u003e), non-photochemical quenching (NPQ), photochemical fluorescence quenching (qP), PSII quantum yield (ΦPSII), PSII quantum yield in light-adapted leaves (F\u003csub\u003ev\u003c/sub\u003e\u0026rsquo;/F\u003csub\u003em\u003c/sub\u003e\u0026rsquo;), and plant vitality (R\u003csub\u003efd\u003c/sub\u003e) (Baker, 2008). Measurements were taken at two time points: 1 day post-transfer (dpt) and 3 dpt, with appropriate LL controls on two-week-old tomato seedlings. Two parameters exhibited statistically significant increases after transferring plants to elevated light conditions at both time points: PSII quantum yield and photochemical fluorescence quenching (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and E). The other parameters showed insignificant fluctuations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B, D and F). These results indicate that seedlings cultured under higher light intensities had greater efficiency of PSII, consistent with previous literature (Takagi et al., 2019).\u003c/p\u003e \u003cp\u003eTo track the activation of signaling pathways, we evaluated the expression of several stress-related marker genes using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis. The expression was checked in leaves (organs subjected to HL stimuli) and roots (remote, shaded organs) at 1 and 3 dpt. Cyst nematodes migrate along the roots to find the initial syncytial cell (ISC) before inducing the feeding structure. Upon initial penetration, the root cells undergo localized damage, triggering the plant's defense response. Additionally, cyst nematodes secrete effector proteins into the plant root to manipulate host cell functions and modulate plant hormone levels to promote syncytium formation and alter root development. Therefore, the first few days are crucial for parasite success (Matuszkiewicz \u0026amp; Sobczak, 2023). The selected genes played a role in the interaction of other nematode/host species, as well as in response to light stress (Huang et al., 2019).\u003c/p\u003e \u003cp\u003eIn leaves, the strongest up-regulation at 1 dpt was observed in the \u003cem\u003eACO1\u003c/em\u003e, \u003cem\u003eNPR1\u003c/em\u003e, \u003cem\u003ePr1a4\u003c/em\u003e, \u003cem\u003eAPX1\u003c/em\u003e, and \u003cem\u003eDHAR\u003c/em\u003e genes, while down-regulation was observed for \u003cem\u003eISC\u003c/em\u003e, \u003cem\u003eHY5\u003c/em\u003e, \u003cem\u003ePHYA\u003c/em\u003e, and \u003cem\u003ePHYB2\u003c/em\u003e transcripts (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Changes in gene expression at 3 dpt were less widespread, with up-regulation of \u003cem\u003eNPR1\u003c/em\u003e, \u003cem\u003eAPX1\u003c/em\u003e, and \u003cem\u003eDHAR\u003c/em\u003e and down-regulation of \u003cem\u003eACCase\u003c/em\u003e and \u003cem\u003eHY5\u003c/em\u003e. The observed changes in leaves may be attributed to the activation of defense and antioxidant pathways to counteract oxidative stress and damage caused by excessive light. Simultaneously, down-regulation of \u003cem\u003eACCase\u003c/em\u003e, \u003cem\u003eICS\u003c/em\u003e, and \u003cem\u003eHY5\u003c/em\u003e may aim to conserve energy, possibly due to \u003cem\u003eACCase's\u003c/em\u003e role in lipid metabolism and fatty acid synthesis, while also reducing susceptibility to light-induced stress.\u003c/p\u003e \u003cp\u003eInterestingly, the tomato root system was more sensitive to applied conditions, even when protected from light. We observed down-regulation of \u003cem\u003eRBOHD\u003c/em\u003e and \u003cem\u003eRBOHF\u003c/em\u003e and up-regulation of \u003cem\u003eAPX1\u003c/em\u003e, \u003cem\u003eSOD\u003c/em\u003e, and \u003cem\u003eDHAR\u003c/em\u003e among oxidative stress-sensitive genes. Genes involved in SA, JA, and ET signaling were up-regulated. Notably, both \u003cem\u003ePHYA\u003c/em\u003e and \u003cem\u003ePHYB2\u003c/em\u003e were strongly down-regulated in roots (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). At 1 dpt, all the mentioned gene expression changes were observed, while at 3 dpt, only \u003cem\u003eNCED1\u003c/em\u003e (involved in ABA biosynthesis) exhibited statistically significant alterations in roots, suggesting effective adaptation to unfavorable conditions and moderation of stress-related responses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Higher light intensities modify PSII photochemistry during \u003cem\u003eG. rostochiensis\u003c/em\u003e parasitism\u003c/h2\u003e \u003cp\u003eThe introduction of a second stress factor can significantly alter the plant's response across various dimensions, including physiological, biochemical, and molecular aspects. Therefore, our objective was to investigate how changes in light conditions might impact the susceptibility of tomatoes and whether these alterations would affect the efficiency of the photosynthetic apparatus. Among the six parameters measured, three showed differences associated with the combination of nematode parasitism and the transfer of plants to different light regimes: PSII yield, qP, and R\u003csub\u003efd\u003c/sub\u003e. In plants infected with \u003cem\u003eG. rostochiensis\u003c/em\u003e and cultivated in low light (LL) conditions, the PSII yield decreased. However, when infected plants were transferred to high light (HL) conditions, their PSII yield levels were similar to those of both control groups of plants. A similar trend was observed for photochemical fluorescence quenching and the parameter representing plant vitality. Infected plants acclimated to LL conditions exhibited a photoinhibition-like response, as evidenced by a decrease in the aforementioned parameters (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Light intensity variation is irrelevant to nematodes\u003c/h2\u003e \u003cp\u003eThe interplay between plant roots and cyst nematodes is a highly complex and extended process involving developmental and metabolic changes of plant cells, along with responses to damages, molecular patterns, and effectors associated with parasite activity (Matuszkiewicz \u0026amp; Sobczak, 2023). The observed changes in photosynthetic efficiency and gene expression in non-infected plants may translate into the susceptibility level of the tomato (see Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). To test this hypothesis, we quantified the number of induced syncytia on tomato root systems in plants that were either continuously grown in low light (LL) conditions or transferred to high light (HL) intensities, and we did not observe any differences (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). It is worth mentioning that we did not observe changes in the morphology of the root system in both comparisons, which could potentially interfere with the level of susceptibility.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.4. Transcriptome analysis reveals DEGs in response to different light conditions during\u003c/b\u003e \u003cb\u003eG. rostochiensis\u003c/b\u003e \u003cb\u003eparasitism in tomato\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTranscriptome profiling has become the fundamental diagnostic tool for monitoring plant reactions to stress, with RNA-seq being increasingly favoured over microarrays, systematic RT-qPCR, SAGE, or cDNA-AFLP due to its advantages. Despite the importance of the tomato/PCN interaction, there is still a lack of RNA-seq perspective. In this study, we employed RNA-seq to investigate the regulatory networks active in nematode-infected roots subject to varying light conditions. Our investigation involved analyzing RNA-seq data derived from plants persistently grown under both low light (LL) and high light (HL) conditions, as well as plants subjected to a transition from LL to HL intensities. This comparative analysis aimed to elucidate the complexity of the response to dual stimuli. We also included non-infected plants subjected to an increase in light intensity, characterizing this scenario as a \u0026ldquo;light response\u0026rdquo;.\u003c/p\u003e \u003cp\u003eAn initial noteworthy observation was that, despite the absence of variances in tomato susceptibility to \u003cem\u003eG. rostochiensis\u003c/em\u003e across distinct light conditions, we detected substantial alterations in the abundance of differentially expressed transcripts. The smallest number of DEGs, 173, was observed when comparing transcriptomes of infected LL-grown roots to control samples. In HL conditions, this comparison yielded nearly twice as many DEGs (303). The highest number of DEGs emerged in the double stimuli comparison \u0026ndash; 2979, while the light response alone resulted in 1746 DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In all comparisons, up-regulated DEGs constituted the predominant group, with the exception of the LL comparison, where down-regulated genes accounted for 68% of the total DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This indicates that, despite relatively small differences observed in DEGs between LL and HL conditions, light exerts a dominant influence on the regulation of gene expression. Moreover, light and nematode response synergistically interact, yielding more DEGs than the sum of individual stimuli.\u003c/p\u003e \u003cp\u003eThe overlap of the aforementioned groups of DEGs would indicate more general mechanisms of plant reaction to biotic and abiotic stimuli (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). For example, in the group common for all four comparisons (9 DEGs), we found genes such as Zinc finger protein (\u003cem\u003eSolyc08g006470.5\u003c/em\u003e), Peroxidase (\u003cem\u003eSolyc10g078890.2\u003c/em\u003e), Glutathione S-transferase (\u003cem\u003eSolyc09g011540.2\u003c/em\u003e), and Defensin protein (\u003cem\u003eSolyc07g007750.3\u003c/em\u003e). Interestingly, in the common pool of DEGs for nematode-related response (11 DEGs), genes involved in secondary metabolism such as O-methyltransferase (\u003cem\u003eSolyc06g064510.2\u003c/em\u003e), Flavin-containing monooxygenase (\u003cem\u003eSolyc08g068160.2\u003c/em\u003e), Glycosyltransferase (\u003cem\u003eSolyc11g007460.1\u003c/em\u003e),\u003c/p\u003e \u003cp\u003e2-oxoglutarate (\u003cem\u003eSolyc11g072110.2\u003c/em\u003e), and ABA 8'-hydroxylase (\u003cem\u003eSolyc04g078900.3\u003c/em\u003e) were present. Additionally, the analysis of DEGs revealed transcripts unique for each treatment, indicating specific processes related to the tested variables and their synergy. The smallest number of exclusive DEGs was found in the LL comparison, while the highest number was observed under double stress conditions, totalling 1641 DEGs. Here, we found genes involved in defense response, hormone homeostasis, ROS signalling, and regulation of primary and secondary metabolic processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eOur analysis of DEGs uncovered a remarkable dynamic range of FC-value for several genes throughout the comparisons. However, as usual, the highest changes were detected for genes with very low expression. For a more detailed description, see Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Categorization of Differentially Expressed Genes\u003c/h2\u003e \u003cp\u003eScreening large datasets of DEGs encounters problems with drawing more general conclusions; therefore, we employed ShinyGO v.0.77 software for functional categorization of DEGs and gene ontology (GO) enrichment analysis. Genes were classified accordingly to four groups of GO terms: KEGG pathways, biological process (BP), molecular function (MF), and cellular component (CC) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Supplementary Table\u0026nbsp;4). This approach allowed us to dissect processes being preferentially targeted upon potato cyst nematode parasitism in combination with environmental stimuli.\u003c/p\u003e \u003cp\u003eIn all analyzed DEG groups, the most general category, \u0026ldquo;Metabolic Pathways\u0026rdquo; and also quite capacious \u0026ldquo;Biosynthesis of Secondary Metabolites\u0026rdquo; were consistently enriched. Specifically, among the LL-inf DEGs, notable enrichment was observed in \u0026ldquo;Valine, Leucine, and Isoleucine Degradation\u0026rdquo; as well as the \u0026ldquo;MAPK Signaling Pathway\u0026rdquo; categories (when KEGG pathways define the category) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Among other categories, the highest enrichment was evident in \u0026ldquo;Glutamine Family Amino Acid Catabolic Process\u0026rdquo; and \u0026rdquo;Negative Regulation of Hydrolase Activity\u0026rdquo; categorized accordingly to BP, and in \u0026ldquo;Fatty Acid Binding\u0026rdquo; and \u0026ldquo;Water Channel Activity\u0026rdquo; when MF determines functional category (refer to Supplementary Table\u0026nbsp;4). As expected, the HL-inf DEGs were enriched in pathways associated with \u0026ldquo;Photosynthesis\u0026rdquo;. Moreover, two additional categories, \u0026ldquo;Sulfur Metabolism\u0026rdquo; and \u0026ldquo;Phenylpropanoid Biosynthesis\u0026rdquo; were highly enriched (see Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). These findings were consistently supported across both GO terms for BP and MF (refer to Supplementary Table\u0026nbsp;4). The most pronounced KEGG pathway overrepresentation among the double stimuli DEGs was \u0026ldquo;Photosynthesis\u0026rdquo; followed by \u0026ldquo;Alanine, Aspartate, and Glutamate Metabolism\u0026rdquo;. Notably, the \u0026ldquo;Valine, Leucine, and Isoleucine Degradation\u0026rdquo; pathway also showed enrichment among double stimuli DEGs, highlighting the significance of amino acid metabolism in plants exposed to a complex environment (see Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Additionally, \u0026ldquo;Gamma-Aminobutyric Acid Metabolic Process\u0026rdquo; emerged as a highly enriched category for BP, while \u0026ldquo;Cytidine Triphosphate (CTP) Synthase Activity\u0026rdquo; stood out for MF. Moreover, in both category groups \u0026ndash; BP and MF, we found expected functional enrichments related to plant-nematode interaction, such as stress response, phytohormone regulation, defense response, cell wall remodelling, and ROS signalling.\u003c/p\u003e\u003cp\u003eThe association of a gene product with a gene ontology term does not always proportionally reflect its engagement in a given molecular function, cellular component, or biological process. Therefore, dissecting domains from complex multidomain arrangements and conducting enrichment analysis could provide valuable supplementary insights needed for understanding large candidate lists. We found the Analysis of Motif Enrichment (AME; McLeay \u0026amp; Bailey, 2010) particularly helpful in interpreting our DEGs lists (refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among LL-inf DEGs, five significantly enriched motifs were identified. Among them, three were unique for LL-inf: \u0026ldquo;Hydroxymethylglutaryl-coenzyme A reductases signature 2\u0026rdquo; (PS00318), \u0026ldquo;cysteine-rich secretory proteins - CRISP family\u0026rdquo; (PS01009), and \u0026ldquo;nitrite and sulfite reductases iron-sulfur/siroheme-binding site\u0026rdquo; (PS00365). The Hydroxymethylglutaryl-coenzyme A (HMG-CoA) reductase is a key enzyme in the mevalonate pathway, responsible for biosynthesizing isoprenoids including sterols (Friesen \u0026amp; Rodwell, 2004). Both LL-inf and HL-inf DEGs share the enriched motif named \u0026ldquo;Soybean trypsin inhibitor (Kunitz) protease inhibitors family\u0026rdquo; (PS00283). Three DEGs groups, the LL-inf, double stimuli, and light response share the enriched signature \u0026ldquo;Zinc finger RING-type\u0026rdquo; (PS00518), describing a conserved RING domain pivotal in the ubiquitination pathway. The potential role of proteins with this motif in stress responses could be linked to modulating protein abundance or turnover via ubiquitin-mediated protein degradation (Sun et al., 2019). Among HL-inf DEGs, the \u0026ldquo;Cytochrome P450 cysteine heme-iron ligand signature\u0026rdquo; (PS00086) is enriched, while among the double stimuli DEGs, three significantly enriched motifs were found: \u0026ldquo;Eukaryotic and viral aspartyl proteases active site\u0026rdquo; (PS00141), \u0026ldquo;Serine/Threonine protein kinases active-site\u0026rdquo; (PS00108), and \u0026ldquo;2Fe-2S ferredoxin-type iron-sulfur binding region\u0026rdquo; (PS00197). These results were partially confirmed by a similar, recently published tool - Simple Enrichment Analysis (SEA; Bailey \u0026amp; Grant, 2021; refer to Supplementary Table\u0026nbsp;5). The presence of the aforementioned motifs within protein sequences may be linked to particular condition-specific functions and regulatory roles in plant-biotic interactions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eThe regulatory protein motifs enriched in analyzed datasets\u003c/b\u003e. The Analysis of Motif Enrichment (AME) method was employed to identify over-represented motifs within the proteins encoded by DEGs from \u003cem\u003eG. rostochiensis\u003c/em\u003e attacked tomato roots under different light conditions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDEG group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003emotif ID (prosite)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emotif alternative ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003econsensus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eadj_p-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eE-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eLL-inf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHMG_COA_REDUCTASE_2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLGXLGGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.01e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.50e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.45e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS01009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCRISP_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGRFSALLWXXS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.44e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.89e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.82e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNIR_SIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSGCXXXCXXXXXXELGL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.44e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.89e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.82e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSOYBEAN_KUNITZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLXDXNGKXLXXXXXYXL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.44e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.89e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.82e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZF_RING_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXHXLCXXCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.44e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.33e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.23e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHL-inf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSOYBEAN_KUNITZ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLXDXEGKXLXXXXXYXL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.34e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.03e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.88e-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCYTOCHROME_P450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFSXGXKXCLG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.85e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.69e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.52e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003edouble stimuli\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZF_RING_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXHXLCXXCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.75e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.27e-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.22e-2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eASP_PROTEASE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLLSDSGSSXSXL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.16e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePROTEIN_KINASE_ST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLXYXDLKXXNLLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.48e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.44e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2FE2S_FER_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXXGXCSSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.62e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.59e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003elight response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZF_RING_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXHXLCXXCL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.42e-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.64e-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.43e-2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePS00198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4FE4S_FER_1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCXXCXXCXXXCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.56e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.77e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.67e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Consistency of RNA-seq results with other transcriptomic studies\u003c/h2\u003e \u003cp\u003eMeta-analyses of transcriptomic results obtained by different methods help identify strong candidates for further research. Despite our RNA-seq data reflecting gene expression changes in whole nematode-infected root systems 14 days post inoculation (since syncytia initiation was not synchronized, root samples contained 10\u0026ndash;14 days old feeding structures), we compared the DEGs list to earlier studies on the same species, where cDNA-AFLP was used to monitor transcriptome changes at 1, 3, 7 and 14 days post infection (dpi) with dissected syncytia (Swiecicka et al., 2009; Święcicka et al., 2017). Thirty-four DEGs overlapped between these two approaches \u0026minus;\u0026thinsp;19 up-regulated, 13 down-regulated, and 2 were stable in the RNA-seq study (refer to Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; Supplementary Table\u0026nbsp;6). Notably, 65% of the DEGs found in both analyses (22 genes) confirmed expression trends (up- or down-regulation upon nematode infection at any time point), while 35% (12 DEGs) demonstrated an inconsistent expression pattern. Among transcripts with a consistent expression pattern, there are several intriguing candidates for future research. The highly up-regulated gene, \u003cem\u003eSolyc11g021060.2\u003c/em\u003e, encodes the TOMARPIX proteinase inhibitor (with a 3.09 log2FC in the double stress comparison). Conversely, a strongly down-regulated gene observed in the double stress response was \u003cem\u003eSolyc08g014130.3\u003c/em\u003e, which encodes Isopropylmalate synthase (with a -1.44 log2FC).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe divergence in plant responses to the co-occurrence of abiotic and biotic stresses is well known. The variability in these responses is influenced by factors such as the magnitude and duration of the applied stress, the specific plant species involved, and the developmental stage of the plant (Zandalinas \u0026amp; Mittler 2022; Georgieva \u0026amp; Vassileva 2023). Examining the plant's response to a combination of factors involves an assessment of whether a physiological and molecular response is induced. In our study, we identified genes that exhibit differential expression in response to the combination of simultaneous action of environmental stimuli in tomato plants \u0026ndash; nematode pest attacking roots and higher light intensity applied to leaves.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1. The impact of elevated light intensities on tomato seedlings\u003c/h2\u003e \u003cp\u003ePlants depend on light for their survival, yet excessive light can have detrimental effects. Beyond a critical threshold, high light (HL) intensity not only directly impairs the photosynthetic apparatus but also induces oxidative stress, leading to photodamage and photoinhibition. Moreover, elevated light levels trigger the generation of reactive oxygen species, increasing the risk of widespread cellular damage (Li et al., 2009; Roeber et al., 2021). To monitor the physiological state of tomato seedlings, we measured chlorophyll a fluorescence. To induce a HL response, we transferred plants from low light intensities (50\u0026ndash;60 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to HL conditions (350\u0026ndash;400 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Such levels of light intensities are not unusual in natural environment. However, the seven-fold increase in intensity was expected to modify PSII efficiency (Dietz, 2015). Here, only two parameters demonstrated statistically significant increases 1 and 3 days post-transfer (dpt): PSII quantum yield (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) and photochemical fluorescence quenching (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). HL stress typically leads to a loss of photosynthesis efficiency, represented by a decrease in the F\u003csub\u003ev\u003c/sub\u003e/F\u003csub\u003em\u003c/sub\u003e ratio (Baker, 2008). Therefore, we may conclude that our HL conditions were relatively mild. However, it is noteworthy that we avoided a temperature shift of the root system, which is often an overlooked variable in such experiments. Several reports on tomato plants grown under similar light intensities yield inconsistent results. Takagi and colleagues (2019) demonstrated that plants cultivated or transferred to HL intensities exhibited enhanced efficiency of photosystem II (PSII), whereas a study conducted by Pascual and colleagues (2023) found that the application of light intensities around 700 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for a duration of 9 hours resulted in a reduction of PSII efficiency and photosynthetic rate in tomato plants.\u003c/p\u003e \u003cp\u003eEven at applied HL intensities, the molecular response was evident, showing the activation of pathways connected with much stronger abiotic or biotic stimuli (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). During the first days after transfer to HL, we observed up-regulation of typical markers of defense and antioxidant pathways, while genes that may conserve energy and reduce susceptibility to light-induced stress were down-regulated. Surprisingly, we found down-regulation of the \u003cem\u003eELONGATED HYPOCOTYL5\u003c/em\u003e (\u003cem\u003eHY5\u003c/em\u003e) transcription factor, which induction may be a marker of stress response. HY5 is involved in systemic shoot-root signalling in response to light stress as well as in maintaining homeostasis of carbon and nitrogen metabolism under ambient light conditions (Chen et al., 2016). Many of the observed molecular effects were temporal and disappeared after 3 dpt, indicating effective adaptation. However, even short-term response activation may interfere with a particular phase of nematode parasitism, such as the migration phase, syncytium establishment and functioning, which engage distinct pathways (Siddique et al., 2022; Matuszkiewicz \u0026amp; Sobczak, 2023). It is worth noting that shaded roots appear to be more sensitive than illuminated shoots and showed a more complex reaction. Most plant nematode studies overlook this aspect, whereas it is known that direct illumination of roots cultivated in vitro alters their morphology, cellular, biochemical, and molecular responses (Cabrera et al., 2022). Moreover, reducing gas exchange is an additional modifying factor for root growth phenotype (Matuszkiewicz et al., 2019). To minimize the influence of such factors, we routinely use root shading and air-permeable Petri plate sealing instead of Parafilm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Light-mediated modulation of root response to \u003cem\u003eG. rostochiensis\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe core premise of this study hinges on the understanding that exploring specific aspects of plant interactions with the environment or other organisms in laboratory conditions often yields results that inadequately reflect the phenomena observed in natural settings. Consequently, the anticipation of light-mediated modifications in root responses following nematode attacks was justified, yet the extent and the specific pathways involved remain to be fully elucidated (Pandey et al., 2015; Zandalinas \u0026amp; Mittler, 2022). The decrease in PSII yield observed in infected tomato plants cultivated in LL conditions aligns with expectations. However, infected plants transferred to higher light intensities exhibited a PSII yield comparable to that of control plants. Overall, it can be inferred that infected plants under LL conditions manifested a photoinhibition-like response (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This observation is consistent with findings by Schmitz et al. (2006), who demonstrated similar fluorescence parameter alterations in sugar beet plants infected with beet cyst nematodes (\u003cem\u003eH. schachtii\u003c/em\u003e) under moderate light intensities\u003c/p\u003e \u003cp\u003e(200 \u0026micro;mol m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). During the early stages of beet infection by \u003cem\u003eH. schachtii\u003c/em\u003e, reductions in photosynthetic efficiency occur, followed by declines in transpiration and photosynthetic processes. These declines are attributed to stomatal closure, impaired mineral nutrient uptake, and reductions in chlorophyll and nitrogen content in the leaves of infected plants. However, changes in photosynthetic efficiency in \u003cem\u003eH. schachtii\u003c/em\u003e-infected \u003cem\u003eA. thaliana\u003c/em\u003e appear slightly different (Labudda et al., 2018). In this case, only minor changes in photosynthetic efficiency occur, which is consistent with our results, including the stable level of tomato seedling susceptibility (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Interestingly, in our previous studies, we documented changes in the susceptibility of \u003cem\u003eA. thaliana\u003c/em\u003e infected with \u003cem\u003eH. schachtii\u003c/em\u003e, which were dependent on the aforementioned ventilation conditions of the Petri plates. This highlights the importance of considering such multivariate analyses in interpreting experimental outcomes (Matuszkiewicz et al., 2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Tomato transcriptomic reprogramming under combined environmental stimuli\u003c/h2\u003e \u003cp\u003eTranscriptome profiling using RNA-seq has become a pivotal approach for diagnosing plant responses to stress. Our investigation encompassed nematode-infected and uninfected tomato roots grown persistently under both low and high light conditions, as well as those transferred from low to higher light intensities. Despite the stable susceptibility of tested tomato cultivar to \u003cem\u003eG. rostochiensis\u003c/em\u003e across varying light conditions, significant changes in the abundance of differentially expressed root transcripts were observed. Our findings underscore the substantial influence of light on gene expression. Furthermore, the synergistic interaction between light and nematode responses produced more DEGs than the sum of individual stimuli. Such light stimulation, crucial for activating defense/resistance responses, has also been observed in plant-pathogen interactions, particularly with bacterial pathogens (Trotta et al., 2014). Another example of this mechanism was described by Gao et al. (2020), who demonstrated that nucleotide-binding NLR Rpi-vnt1.1 proteins require light for conferring resistance against \u003cem\u003ePhytophthora infestans\u003c/em\u003e races, specifically those releasing the effector protein AVRvnt1.\u003c/p\u003e \u003cp\u003eAnalyzing the DEGs with representation enrichment tools across all generated RNA-seq data, we consistently found two KEGG categories overrepresented, namely \u0026ldquo;Metabolic Pathways\u0026rdquo; and \u0026ldquo;Biosynthesis of Secondary Metabolites\u0026rdquo; which serve as nonspecific markers of environmental factor response (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). However, among the DEGs, there were some more specific enrichments, such as \u0026ldquo;Valine, Leucine, and Isoleucine Degradation\u0026rdquo; and the \u0026ldquo;MAPK Signaling Pathway\u0026rdquo; in the LL-inf group. The degradation of branched-chain amino acids (BCAAs) is connected with energy production and nitrogen recycling and may be part of the classical growth-defense trade-off (Hildebrandt et al., 2015; He et al., 2022). The MAPK signaling pathway is also typical in plant-pathogen interactions, involved in signal transduction to maintain ROS production and integrate signals from JA and SA pathways (Taj et al., 2010).\u003c/p\u003e \u003cp\u003eNew categories emerged in the group of DEGs after nematode infection of plants grown under HL conditions, namely \u0026ldquo;Photosynthesis\u0026rdquo;, \u0026ldquo;Sulfur Metabolism\u0026rdquo; and \u0026ldquo;Phenylpropanoid Biosynthesis\u0026rdquo;. The double stimuli DEGs were overrepresented by \u0026ldquo;Photosynthesis\u0026rdquo;, \u0026ldquo;Alanine, Aspartate, and Glutamate Metabolism\u0026rdquo; and another amino acid-related pathway \u0026ldquo;Valine, Leucine, and Isoleucine Degradation\u0026rdquo;. These pathways emphasize the importance of amino acid metabolism in plants exposed to complex environmental stimuli, including moderate parasite pressure and extensive light intensity variation. Nematode infection evokes multidirectional changes in roots involving amino acids as substrates for hormones and newly synthesized proteins needed for developmental reprogramming during syncytium formation and feeding parasitic nematodes. The observed synergy between the responses triggered by light exposure and nematode infection indicates substantial enrichment in processes essential for plant adaptation to stress conditions, such as energy allocation, phytohormone crosstalk, and enhanced secondary metabolite production. The integration of these responses is likely context-dependent, specific to environmental stimuli, the type of plant-pathogen interaction, and their intensity.\u003c/p\u003e \u003cp\u003eGene ontology analysis was supplemented with motif enrichment approaches (McLeay \u0026amp; Bailey, 2010). For example, the \u0026ldquo;cysteine-rich secretory proteins - CRISP family\u0026rdquo; motif was enriched in the LL DEG group. CRISPs belong to a family of proteins with conserved cysteine residues arrangements present in animals and involved in gamete interaction (Gonzalez et al., 2021). In plants, proteins with that motif could be found among pathogenesis-related proteins (Han et al., 2023). Another pathogenesis-related and enriched motif was found in LL-inf and HL-inf DEGs \u0026ndash; \u0026ldquo;Soybean trypsin inhibitor (Kunitz) protease inhibitors family\u0026rdquo;, typically occurring in protease inhibitors commonly linked to defense responses. Interestingly, we also observed enriched signatures of antagonistic activities, such as \u0026ldquo;Eukaryotic and viral aspartyl proteases active site\u0026rdquo;, typical for proteolytic enzymes involved in stress-related processes such as protein degradation, plant senescence, and programmed cell death (Sim\u0026otilde;es \u0026amp; Faro, 2004).\u003c/p\u003e \u003cp\u003eThe above-listed statistically significant molecular characteristics are complex and difficult to summarize. We may speculate that in compatible plant-nematode interactions, an additional environmental factor (e.g., higher light intensities) can both enhance and inhibit specific plant defense responses. In the face of such antagonistic responses, other pathways are activated, which on a molecular level resemble the priming phenomenon (Nair et al., 2022). Whether resulting stress tolerance was enhanced requires further studies with higher parasite inocula, more HL levels and different stressors.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe presence of abiotic and biotic stimuli combinations induces a different response, involving a greater number of genes or biochemical pathways compared to single stressors. This response is characterized by species specificity and dependency on the type and intensity of the applied factor. In the context of interactions between plant parasitic nematodes and elevated light intensity, the important role of amino acid metabolism and hormonal regulation emerges. Processes traditionally classified as \u0026ldquo;plant-pathogen related\u0026rdquo; appear to exhibit diminished relevance in the context of complex environmental factors. Therefore, research on genes implicated in the response to stress combinations is crucial for comprehending the molecular pathways associated with such responses and for the development of more resilient cultivars, particularly in the face of climate changes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Dr Aska Goverse (Laboratory of Nematology, Wageningen University, the Netherlands) for kindly sharing nematode cysts. We would like to thank Dr Mirosław Sobczak (Department of Botany, Institute of Biology, WULS) for sharing the quarantine laboratory. We are grateful to the Polish National Science Centre for funding ( Project No 2017/25/B/NZ9/02574).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw University of Life Sciences-SGGW, 02-776, Warsaw, Poland\u003c/p\u003e\n\u003cp\u003eMateusz Matuszkiewicz, Magdalena Święcicka, Marek Koter \u0026amp; Marcin Filipecki\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMM \u0026amp; MF: developed the hypothesis and devised the research plan: MF: supervised the experiment; MM, MŚ and MK performed the experiments; MM, MŚ, MK \u0026amp; MF analyzed the results; MM: prepared the figures, MM: wrote the manuscript with the contribution of all authors. The authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Marcin Filipecki\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by National Science Centre, grant no. 2017/25/B/NZ9/02574.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnwar K, Joshi R, Dhankher OP, Singla-Pareek SL, Pareek A (2021) Elucidating the response of crop plants towards individual, combined and sequentially occurring abiotic stresses. 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Plant J https://doi.org/10.1111/tpj.16557\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joag","sideBox":"Learn more about [Journal of Applied Genetics](https://www.springer.com/journal/13353)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/joag/default.aspx","title":"Journal of Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"cyst nematodes, stress combination, abiotic stress, biotic stress, RNA-seq","lastPublishedDoi":"10.21203/rs.3.rs-3982446/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3982446/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding the intricate interplay between abiotic and biotic stresses is crucial for deciphering plant responses and developing resilient cultivars. Here, we investigate the combined effects of elevated light intensity and nematode infection on tomato seedlings. Chlorophyll fluorescence analysis revealed significant enhancements in PSII quantum yield and photochemical fluorescence quenching under high light conditions. qRT-PCR analysis of stress-related marker genes exhibited differential expression patterns in leaves and roots, indicating robust defense and antioxidant responses. Despite root protection from light, roots showed significant molecular changes, including down-regulation of genes associated with oxidative stress and up-regulation of genes involved in signalling pathways. Transcriptome analysis uncovered extensive gene expression alterations, with light exerting a dominant influence. Notably, light and nematode response synergistically induced more differentially expressed genes than individual stimuli. Functional categorization of differentially expressed genes upon double stimuli highlighted enrichment in metabolic pathways, biosynthesis of secondary metabolites, and amino acid metabolism, whereas the importance of specific pathogenesis related pathways decreased. Overall, our study elucidates complex plant responses to combined stresses, emphasizing the importance of integrated approaches for developing stress-resilient crops in the face of changing environmental conditions.\u003c/p\u003e","manuscriptTitle":"Identification of genes involved in the tomato root response to Globodera rostochiensis parasitism under varied light conditions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-08 17:41:11","doi":"10.21203/rs.3.rs-3982446/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-03-05T17:27:39+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-05T12:56:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-27T08:52:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Applied Genetics","date":"2024-02-22T08:58:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joag","sideBox":"Learn more about [Journal of Applied Genetics](https://www.springer.com/journal/13353)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/joag/default.aspx","title":"Journal of Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"985afaa3-1058-4ce8-b3c6-8947d16770cf","owner":[],"postedDate":"March 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-22T19:32:59+00:00","versionOfRecord":{"articleIdentity":"rs-3982446","link":"https://doi.org/10.1007/s13353-024-00897-6","journal":{"identity":"journal-of-applied-genetics","isVorOnly":false,"title":"Journal of Applied Genetics"},"publishedOn":"2024-08-14 15:57:46","publishedOnDateReadable":"August 14th, 2024"},"versionCreatedAt":"2024-03-08 17:41:11","video":"","vorDoi":"10.1007/s13353-024-00897-6","vorDoiUrl":"https://doi.org/10.1007/s13353-024-00897-6","workflowStages":[]},"version":"v1","identity":"rs-3982446","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3982446","identity":"rs-3982446","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}