{"paper_id":"05f6a358-4e99-49bb-a723-66facf6c8eb0","body_text":"Unraveling the transcriptional response mechanisms to yellow and wilt disease, caused by race 6 of Fusarium oxysporum f.sp. ciceris in two contrasting chickpea cultivars | 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 Unraveling the transcriptional response mechanisms to yellow and wilt disease, caused by race 6 of Fusarium oxysporum f.sp. ciceris in two contrasting chickpea cultivars Aliakbar Faramarzpour, Sara Dezhsetan, Hamid Hassaneian Khoshro, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5212429/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Feb, 2025 Read the published version in BMC Genomics → Version 1 posted 4 You are reading this latest preprint version Abstract Background Chickpea ( Cicer arietinum L.) ranks as the third most crucial grain legume worldwide. Fusarium wilt ( Fusarium oxysporum f. sp. ciceri (Foc)) is a devastating fungal disease that prevents the maximum potential for chickpea production. Results To identify genes and pathways involved in resistance to race 6 of Foc, this study utilized transcriptome sequencing of two chickpea cultivars: resistant (Ana) and susceptible (Hashem) to Foc race 6. Illumina sequencing of the root samples yielded 133.5 million raw reads, with about 90% of the clean reads mapped to the chickpea reference genome. The analysis revealed that 518 genes (317 upregulated and 201 downregulated) in the resistant genotype (Ana) and 1063 genes (587 upregulated and 476 downregulated) in the susceptible genotype (Hashem) were differentially expressed under Fusarium wilt (FW) disease stress caused by Foc race 6. The expression patterns of some differentially expressed genes (DEGs) were validated using quantitative real-time PCR. A total of 127 genes were exclusively upregulated under FW stress in the resistant cultivar, including several genes involved in sensing (e.g., CaNLR-RPM1 , CaLYK5-RLK , CaPR5-RLK , CaLRR-RLK , and CaRLP-EIX2 ), signaling (e.g., CaPP7 , CaEPS1 , CaSTY13 , and CaPR-1 ), transcription regulation (e.g., CaMYBs , CaGLK , CaERFs , CaZAT11-like , and CaNAC6 ) and cell wall integrity (e.g., CaPGI2-like , CaEXLs , CaCSLD and CaCYP73A100-like ). Conclusions The achieved results could provide significant insights into the molecular mechanism underlying resistance to FW and could be valuable for breeding programs aimed at developing FW-resistant chickpea varieties. Chickpea Biotic stress Fusarium wilt (Race 6) RNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Chickpea ( Cicer arientinum L.), classified as the third most important grain legume, is commonly known as a low-cost protein source for both livestock feed and human consumption [ 1 ]. It contains many carbohydrates, lipids, minerals, vitamins, and other nonnutritive compounds that are beneficial to health [ 2 ]. Moreover, it has a significant impact on sustaining agricultural systems through nitrogen fixation, similar to other legumes [ 3 ]. Chickpea is produced about 16 million tons annually [ 4 ]. It is mainly cultivated in 50 countries and grown in a variety of ecological conditions; however, its yield and quality are affected by several challenges, such as fungal diseases [ 5 , 6 ]. Among the fungal diseases, Fusarium wilt (FW) induced by Fusarium oxysporum f. sp. ciceris (Foc) is a widespread soil-borne disease that causes a significant reduction in chickpea production [ 7 ]. According to reports, Foc penetrates the roots through epidermal cells, and subsequently, hyphae spread to the root cortex region, where they colonize the xylem vessels. All of these factors prevent the upward movement of water and essential solutes, which results in wilting. The initial symptom of the infection is wilting, which ultimately results in death [ 8 , 9 ]. Fusarium wilt epidemics can result in the destruction or complete loss of crops in fields that are highly infested under favorable conditions [ 10 ]. Eight distinct physiological races of the pathogen, identified as 0, 1A, 1B/C, 2, 3, 4, 5, and 6, have been found to infect chickpea [ 10 ]. Races 1A, 2, 3, 4, 5, and 6 cause wilting symptoms in chickpea, characterized by flaccidity, severe chlorosis, and vascular discoloration, eventually leading to plant death. In contrast, races 1B/C and 0 are less virulent, causing only yellowing symptoms[ 11 ]. Despite the availability of complete sequencing of desi and kabuli chickpea genomes [ 12 , 13 ]. The genes responsible for Fusarium resistance are poorly understood. Recently, researchers have employed the RNA-seq technique to identify stress-related genes involved in the response to FW. These authors reported several overrepresented genes related to the defense signaling pathway, disease resistance, and cell wall biogenesis in root tissues [ 14 – 19 ]. Various attempts have been made to dissect the genetic basis of resistance to different FW races in chickpea. Thus, some genes and quantitative trait loci (QTLs) have been identified in various chickpea genotypes to be associated with resistance to certain Foc races. However, limited data are available regarding the genetics of resistance to some Fusarium races, such as races 6 and 1B/C [ 16 , 19 ]. Herein, we conducted a comparative transcriptome study of root tissues of Iranian contrasting genotypes named Ana (a resistant genotype) and Hashem (a susceptible genotype) to Foc race 6. This research focused on root tissues as the initial organ, which serves as the first line of defense against phytopathogens and is crucial for sensing and signaling during Fusarium infection. Our results revealed differential expression patterns between resistant and susceptible cultivars 48 hours after the onset of infection. This study investigated transcriptome dynamics linked to FW disease in chickpea, highlighting crucial factors that influence disease resistance. Specific and differential expression patterns of genes were identified between resistant and susceptible cultivars. These findings provide a basis for further investigations to elucidate the molecular mechanisms underlying resistance in cultivars compared with susceptibility during Fusarium infection. Results Phenotyping The first Fusarium disease symptoms appeared on the lower leaves of the plants approximately 12 days after inoculation. The symptoms started with slight yellowing at the leaf edges and progressed to twisting and complete yellowing. Finally, the leaves become necrotic and fall. The reaction of two cultivars, Ana and Hashem, to Fusarium disease (Race 6) under controlled conditions was marked by early onset of wilt symptoms (distinct and consistent disease phenotypes), based on the method proposed by Sharma et al. in 2005 [ 20 ]. The percentages of FW incidence in the Ana and Hashem cultivars were 20% (resistant) and 80% (susceptible), respectively (Supplementary Figure S1 and S2). Sequencing metrics and mapping results In total, 133.5 million raw reads were obtained from the root samples of the Ana and Hashem cultivars under control and FW stress conditions, and more than 89.15% of the raw reads presented Phred quality scores at the Q30 level. Additionally, almost 90% of the clean reads were mapped to the chickpea reference genome (Table 1 ). The assembly of mapped reads led to the recognition of 61997 transcript isoforms and 31177 genes. The results indicated that 518 (317 up- and 201 downregulated) and 1063 (587 up- and 476 downregulated) genes were differentially expressed under Foc race 6 stress in the resistant and susceptible cultivars, respectively (Fig. 1 ). Table 1 Summary statistics of the transcriptome reads and their mapping to the reference genome. Reads mapping Reads number (%) Sample Ana Control Ana Treated 1 Ana Treated 2 Total reads 20974728 22881594 21195569 Total mapped reads 19069583 (90.92%) 20879587 (91.25%) 19082588 (90.03%) Unique match 18203933 (86.79%) 19924028 (87.07%) 18397275 (86.8%) Multiposition match 865650 (4.13%) 955559 (4.18%) 685313 (3.23%) Total unmapped reads 1905145 (9.08%) 2002007 (8.75%) 2112981 (9.97%) Sample Hashem Control Hashem Treated 1 Hashem Treated 2 Total reads 23529811 23872344 21044139 Total mapped reads 21229993 (90.22%) 21429429 (89.77%) 18890896 (89.76%) Unique match 20299725 (86.27%) 20633219 (86.43%) 18132422 (86.16%) Multiposition match 930268 (3.95%) 796210 (3.34%) 758474 (3.6%) Total unmapped reads 2299818 (9.77%) 2442915 (10.23%) 2153243 (10.23%) Gene Ontology classification analysis for DEGs Based on the GO analysis, significant GO terms were assigned to 193 (of 558) DEGs Ana and 333 (of 1085) DEGs Hashem. Moreover, the results demonstrated that several biological procedures, including defense response, response to stress, response to biotic stimulus, metabolic process, and primary metabolic process, were significantly enriched in both cultivars, with their percentages being somewhat greater in the Ana cultivar than in the Hashem cultivar (Fig. 2 ). Remarkably, some biological processes, such as the response to ethylene stimulus and the regulation of flavonoid biosynthetic processes, were significantly enriched only in the resistant cultivar (Fig. 2 ). In the molecular function category, hydrolase activity, catalytic activity, oxidoreductase activity, transferase activity, transcription regulator activity and transcription factor activity were highly enriched in both cultivars; however, their percentages in the Ana cultivar were dramatically greater than those in the Hashem cultivar (Fig. 2 ). The terms lyase activity, lipase activity, cellulose synthase activity, triglyceride lipase activity, triglyceride lipase activity, peptidase inhibitor activity, nitrate transmembrane transporter activity, and chitinase activity were significantly enriched only in the Ana cultivar (Fig. 2 ). On the one hand, some cellular component terms, including membrane, cell part, cell wall, external encapsulating structure, and extracellular region, were dramatically enriched in the resistant cultivar compared with the susceptible cultivar. Furthermore, the chloroplast part was enriched only in the susceptible cultivar (Fig. 2 ). Pathway analysis of DEGs To achieve a more comprehensive understanding of the pathways involved in the response of each cultivar to FW stress, a BLAST search against the KEGG protein database was carried out [ 21 , 22 ]. In total, 218 of the 553 Ana significant DEGs were categorized into 121 KEGG pathways, and 443 of the 1118 Hashem significant DEGs were categorized into 173 KEGG pathways, consisting of five main KEGG classes: genetic information processing, cellular processes, metabolism, environmental information processing, and organismal systems. These genes mainly belong to the following KEGG pathways: MAPK signaling pathway-plant, plant‒pathogen interaction, plant hormone signal transduction, glycolysis/gluconeogenesis, glutathione metabolism, phenylpropanoid biosynthesis, flavonoid biosynthesis, cytochrome P450, nitrogen metabolism, ubiquinone, ABC transporters, other terpenoid‒quinone biosynthesis, transcription factors, glycosyltransferases, protein kinases, transporters and exosomes (Fig. 3 ). The phenylpropanoid pathway, which had the most number of genes, is a metabolic pathway responsible for the synthesis of various plant secondary metabolites, containing lignin, flavonoids, lignans, phenylpropanoid esters, sporopollenin and hydroxycinnamic acid amides[ 23 , 24 ]. The cytochrome P450 pathway, which had the second most number of genes in the Ana cultivar, is a transcription factor linked to plant stress responses [ 25 , 26 ]. Additionally, the percentages of genes belonged to cytochrome P450, glutathione metabolism and flavonoid biosynthesis pathways in the Ana cultivar were higher than those in the Hashem cultivar (Fig. 3 ). \"Proteomic and metabolomic analyses of chickpea–Foc interactions showed that numerous metabolic pathways, phenylpropanoid, isoflavonoid, and flavonoid biosynthesis pathways, were significantly upregulated in the resistant genotype. Proteomic and metabolomic studies of chickpea–Foc interactions revealed that many metabolic pathways, including the phenylpropanoid, isoflavonoid, and flavonoid biosynthesis pathways, were significantly upregulated in the resistant genotype [ 9 , 27 , 28 ]. Overview of the biotic stress pathway To comprehend the various defense responses in the resistant and susceptible cultivars at the initial stage of Foc race 6 infection, MapMan analysis was used to investigate fluctuations in the significant DEGs in both cultivars under biotic stress. Also, the putative involvement of significant DEGs in the biotic stress response pathways was visualized using MapMan software (Fig. 4 ; Supplementary Figures S4 and S5). On the basis of the MapMan analysis results, several genes located in the cell wall, such as pectinesterase 2-like (LOC101508209), probable pectinesterase/pectinesterase inhibitor 7 (LOC101489717) and expansin-like B1 (LOC101489892 and LOC101507544), were more highly upregulated in the resistant cultivar (Ana) than in the susceptible cultivar (Hashem). In addition, some genes related to the cell wall were upregulated exclusively in the resistant cultivar, including polygalacturonase inhibitor 2-like (LOC105852278) and probable xyloglucan endotransglucosylase/hydrolase protein 23 ( CaXTH23 : LOC101489989 and LOC101490102), which have logFCs of 3.87, 4.55 and 2.9, respectively (Fig. 4 ; Supplementary Figure S4 and S5). On the other hand, in the GO analysis, some cellular component terms assigned to the cell wall category were more sharply enriched in the resistant cultivar than in the susceptible cultivar (Fig. 2 ). Two genes encoding glutathione S-transferase (GST; LOC101494465 and LOC113787225) were upregulated only in the resistant cultivar (Fig. 4 ; Supplementary Figure S4 and S5). One gene encoding the transcription factor MYB41 (LOC101497118) was highly upregulated only in the resistant cultivar under FW stress (logFC = 4.71) (Fig. 4 ; Supplementary Figure S4 and S5). Furthermore, several genes encoding pathogenesis-related proteins (LOC101499251, LOC105851085, and LOC101510493) were exclusively upregulated in the resistant cultivar. Some individual genes encoding proteolysis components, such as basic 7S globulin-like ( CaBg7S-like : LOC101509822), senescence-specific cysteine protease Ca SAG39-like (LOC101497435) and uncharacterized (ncRNA; LOC113785693), were upregulated only in resistant plants under Fusarium wilt disease stress (Figs. 4 and 6 ; Supplementary Figure S4 and S5). Interestingly, a gene encoding the cytochrome P450 CYP73A100-like ( CaCYP73A100-like : LOC101503511) was upregulated (logFC = 3.89) only in the Ana cultivar under Fusarium wilt (race 6). On the other hand, analysis of biotic stress by MapMan software revealed that in the hormone signaling part (Auxins), several genes encoding cytochrome P450 (LOC101510162, LOC101494883, and LOC101510201) were downregulated only in resistant plants (Fig. 4 ; Supplementary Figure S4 and S5). The results of MapMan showed that genes encoding the protein EXORDIUM-like (LOC101501686 and LOC101502011) were more upregulated in the Ana cultivar (resistant) than in the Hashem cultivar (susceptible). The protein LYK5 (LOC101494861) on chromosome 2 was upregulated only in the resistant cultivar, but another gene encoding the protein LYK5-like (LOC101501405) was downregulated in the susceptible cultivar. On the other hand, we found some uncharacterized genes that were upregulated only in the resistant cultivar (LOC113785810, LOC101496586 and LOC113788231), and some of them were ncRNAs (Fig. 4 ; Supplementary Figure S4 and S5). The secondary metabolism pathway analysis of differentially expressed genes by MapMan determined that several genes encoding laccase-7-like (LOC101515697), 3-isopropylmalate dehydratase large subunit, chloroplastic-like (LOC101494361) and uncharacterized (LOC101511595) genes were more highly upregulated in the Ana cultivar than in the Hashem cultivar. Moreover, a gene encoding shikimate O-hydroxy cinnamoyl transferase-like (LOC101501659) was upregulated only in the Ana cultivar in response to Fusarium wilt disease (Supplementary Figure S4 and S5). Although a gene encoding chalcone-flavonone isomerase 2-like (LOC101508130) was highly downregulated in the resistant cultivar under Fusarium wilt disease (logFC= -10), another gene encoding chalcone-flavonone isomerase 2 (LOC101500746) was slightly upregulated in the susceptible cultivar (logFC = 1.59) (Fig. 4 ; Supplementary Figure S4 and S5). Confirming DEGs using qRT‒PCR In order to validate the RNA-seq results, the expression patterns of twelve FW-responsive candidate genes were inspected by qRT‒PCR (quantitative real-time PCR) in the resistant and susceptible cultivars (Fig. 5 ). The selected genes were as follows; LOC101491624 (linoleate 9S-lipoxygenase-like), LOC101501931 (heat shock cognate 70 kDa protein 2), LOC101495891 (1-aminocyclopropane-1-carboxylate oxidase), LOC101513977 (probable leucine-rich repeat receptor-like serine/threonine-protein kinase), LOC101493121 (protein ENHANCED PSEUDOMONAS SUSCEPTIBILTY 1), LOC101497118 (transcription factor MYB41), LOC101510034 (basic 7S globulin-like), LOC101513347 (spermidine hydroxycinnamoyl transferase-like), LOC101489892 (expansin-like B1), LOC101495793 (MATH and LRR domain-containing protein PFE0570w), LOC101507324 (putative protein TPRXL) and LOC101498889 (carbonic anhydrase 1) (Figs. 4 and 5 ). The results of the qRT‒PCR confirmed the RNA‒Seq results for both chickpea cultivars (in Ana; R 2 = 0.999 and in Hashem; R 2 = 0.987). Discussion Chickpea is an excellent source of protein for a large population worldwide, especially in Asia. It can serve as an alternative to fallow periods in cereal crop rotations, but FW disease causes significant economic losses in its production. Therefore, identifying the resistance mechanism to this disease in chickpeas is crucial [ 10 ]. Next-generation RNA-seq provided a comprehensive comparison between Ana (a resistant cultivar) and Hashem (a susceptible cultivar) in this research. Through transcriptome analysis, we identified differential gene expression patterns between Ana and Hashem. Several genes involved in disease resistance pathways that have been previously reported in chickpea and/or other plants were differentially expressed in Ana, as discussed below (Fig. 4 ; Fig. 6 and Supplementary Table S2). DEGs involved in pathogen sensing To sense pathogens in a timely manner, resistant plants express many RLKs and RLPs as recognition receptors (PRRs), which act as the first layer of inducible defenses during the early stages of tension [ 29 ]. The downstream defense signaling cascades are activated on time when the resistant cultivar detects the pathogen early [ 19 ]. Interestingly, several receptor genes, including CaNLR-RPM1 (Nucleotide-binding site leucine-rich repeat-disease resistance protein RPM1; LOC101504665), CaLYK5/PR5-RLK (Lysin Motif Receptor-Like Kinase5/Pathogenesis related5-receptor like kinase; OC101494861 and LOC101493461), CaLRR-RLK (Leucine-rich repeat-receptor like kinases; LOC101489235 and LOC101513977) and CaRLP-EIX2 (Receptor-like protein-Ethylene inducing xylanase2; LOC101498360), were significantly induced by FW in the root tissues of Ana (Fig. 4 ; Fig. 6 and Supplementary Table S2). It is noteworthy that transcripts of CaNLR-RPM1 (LOC101504665) and CaLYK5-RLK (LOC101494861) were exclusively detected in Ana, and considerably increased under FW stress conditions (Fig. 4 ; Fig. 6 and Supplementary Table S2). NLR-RPM1 is a plant intracellular immune receptor that specifically detects pathogen-released effectors, initiating effector-triggered immunity (ETI). This activation of ETI by NLR-RPM1 leads to a hypersensitive response (HR), which is a type of localized cell death that helps to restrict pathogen spread and boost disease resistance [ 30 , 31 ]. LYK5-RLK is a major type of chitin receptor from the LRR-RLK class. Upon the detection of chitin, a constituent of fungal cell walls, LYK5 forms a complex with another receptor kinase to stimulate immune signaling pathways [ 32 ]. PR5-RLK is involved in distinguishing pathogen-associated molecular patterns (PAMPs) and triggering immune responses in plants [ 33 ]. RLP-EIX2 is known for recognizing and responding to the fungal protein ethylene-inducing xylanase (EIX). This interaction triggers defense mechanisms in plants, helping them fend off fungal pathogens [ 34 ]. RLP-EIX2 is structurally similar to other receptor-like proteins found in various plants, which rely on pattern recognition receptors (PRRs) to detect PAMPs and initiate defense responses [ 35 ]. DEGs involved in signaling pathways Several genes involved in signaling pathways were upregulated under FW stress either exclusively in the resistant cultivar or to a greater extent than in the susceptible cultivar (Fig. 5 , 6 and Supplementary Table S2). For example, serine/threonine-protein phosphatase 7 ( CaPP7 : LOC105852653) and heat shock cognate 70 kDa protein 2 ( Ca HSC70s ; LOC101501931) might play roles in MAPK (mitogen-activated protein kinase) signaling. PP7 is implicated in the dephosphorylation of specific proteins, which can activate or deactivate signaling pathways related to plant defense mechanisms such as MAPK and oxidative stress signaling [ 36 ]. HSC70 belongs to the heat shock protein 70 (Hsp70) family and operates as a molecular chaperone. It can interact with various components of the MAPK pathway, maintaining its activity [ 37 ]. It has been reported that HSC70s are highly upregulated in chickpea, sunflower, and cabbage after infection with Foc [ 16 , 38 , 39 ]. Several genes associated with the hormone signaling pathway, including components of jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), ethylene (ET) and auxin (AUX), were differentially expressed after Foc infection (Figure S4). Among them, some components of SA were found in Ana, such as ENHANCED PSEUDOMONAS SUSCEPTIBILITY 1 ( CaEPS1 : LOC101493121) (log2 FC = 1.78), whereas it was not expressed in Hashem. EPS1 is an isochorismate-9-glutamate pyruvoyl-glutamate lyase that can degrade N-pyruvoyl-L-glutamate to generate SA [ 40 ]. Salicylic acid, an important signaling molecule, can induce resistance to diseases such as Fusarium. SA is reported to be a mediator between plants and microbes, which activates resistance against Fusarium [ 41 ]. Moreover, two genes encoding pathogenesis-related (PR) proteins ( CaPR-1 : LOC101503659, CaPR-4 : LOC101511048) were significantly induced in Ana (Fig. 6 and Supplementary Table S2). PR-1-like proteins are part of a larger family of PR proteins that are typically induced in response to pathogen attack and are involved in SAR (systemic acquired resistance). They are often associated with the SA signaling pathway, which is crucial for activating defense responses [ 42 ]. PR-4 proteins constitute another class of PR proteins that are often associated with the JA signaling pathway, which is also crucial for defense against pathogens [ 43 ]. Both the PR-1-like and PR-4 proteins have antimicrobial activity. PR-4 proteins often exhibit chitinase activity, which allows them to break down chitin. This activity helps prevent the growth and spread of fungi [ 42 , 43 ]. Furthermore, we identified several genes associated with the PR5 (Pathogenesis-related 5) family in Ana that are known as thaumatin-like proteins (TLPs; CaTLP1b (LOC101495985) and CansLTP-like (LOC101503860)). TLPs have been increasingly demonstrated to contribute to resistance against various fungal diseases, including Fusarium, in numerous crop plants, especially legumes. They may also play a role in the crosstalk between different hormone responses [ 44 ]. Several genes related to TOR (target of rapamycin) signaling pathway, including CaSTY13 (LOC101511109) and CaSTY-OXI1 (LOC101501979), were highly upregulated in the resistant cultivar (Fig. 6 and Supplementary Table S2). Serine/threonine-protein kinase TOR proteins are reported to be significantly expressed during infection by pathogens in chickpeas and regulate both catabolic and anabolic processes, such as cell cycle regulation, cell growth, mitochondrial signaling, secondary metabolism and apoptosis, cell wall structure, and development [ 17 , 45 ]. The overexpression of serine/threonine-protein kinases in chickpea-Foc1 interaction has also been reported in various resistant genotypes at different time points [ 16 , 17 ]. This excessive expression was predominantly found in the cell wall, which causes cell wall integrity after the onset of infection [ 46 ]. DEGs involved in transcription regulation Transcription factors (TFs) are essential in plant defense, regulating the expression of genes that react to pathogen attacks [ 47 ]. Transcriptional reprogramming happens after triggering a signaling cascade by various transcription factors (TFs), which activate genes involved in hormonal control and other processes, including PR genes and structural genes. [ 19 ]. GO analysis showed that the term ‘transcription regulator activity’ was dramatically enriched in the Ana cultivar (Fig. 2 ). Among them, some MYBs ( CaMYB41 : LOC101497118; CaMYB108 : LOC101490747; LOC101492267), MYB-related (LOC101507725) and G2. Like ( CaGLK : LOC101491042) was significantly upregulated by FW only in the resistant cultivar (Figs. 4 and 6 ; Supplementary Table S2). MYBs are a major group of TFs that have a variety of roles in eukaryotes, including responses to wounding and pathogens [ 48 ]. MYB108 was previously reported in Arabidopsis, which controls the infection of two pathogens by stimulating defense-related genes (DR Genes); PDF1–2 and PR-1 , through ethylene and JA signaling pathways [ 49 ]. AtMYB108 is an R2R3MYB protein that modulates responses to both biotic and abiotic stresses [ 49 ]. R2R3MYB has been found to increase resistance to Bipolaris sorokiniana root rot fungus, as well as enhancing the expression of PR1a, PR2, and TLP4 genes through the SA and ABA signaling pathways [ 50 ]. Furthermore, overexpression of AtMYB41 has been reported to activate monolignol and suberin-associated wax biosynthesis, as well as the formation of suberin-like lamellae in the cell walls of both epidermal and mesophyll cells, which eventually protects against biotic and abiotic stresses [ 51 ]. Furthermore, we found a gene coding GOLDEN2-LIKE (GLK) belonging to the MYB family in Ana. GOLDEN2-LIKE ( GLK ) plays a significant role in regulating plastid development and stress tolerance [ 52 ]. GLKs play a positive role in virus resistance against cucumber mosaic virus (CMV) in Arabidopsis by modulating the expression of defense-associated genes and the antioxidant system, which is partially associated with the accumulation of JA and SA [ 53 ]. Some ERFs ( CaERF9 : LOC101502158, CaERF113 : LOC101515629, and CaERF113-like : LOC101513362) were also significantly upregulated by FW, specifically in Ana (Figs. 4 and 6 ; Supplementary Table S2). The ERF (ethylene-responsive transcription factor) is a subfamily of the AP2/ERF family and plays essential roles in the regulation of biotic stress responses. Utmost ERF proteins can bind to GCC box-containing promoters, which are found in the promoters of many pathogenesis-related ( PR ) genes, such as PRb-1b (PR1), β-1,3-glucanase ( PR2 ), chitinase ( PR3 ) and osmotin ( PR5 ), and mediate the vital role of these genes in plant responses to biotic stress [ 54 , 55 ]. It has been reported that ethylene signaling acts a vital role in cucumber resistance against Foc [ 56 ]. Consistent with the findings of a previous study [ 19 ], we also found that the CaERF113 gene (LOC101515629) was upregulated in the resistant cultivar under FW stress. Furthermore, some C2H2s ( CaZAT11-like : LOC101498044 and LOC101492538) were exclusively shown significant upregulation by FW in Ana (Figs. 4 and 6 ; Supplementary Table S2). C2-H2-type proteins (TFs) are involved in regulating the signaling pathway during biotic stress [ 57 ]. Previous reports have demonstrated that the transcript abundance of ZAT11 can be highly induced by H2O2; ZAT11 was shown to be involved in paraquat-induced oxidative stress, which leads to programmed cell death [ 58 ]. CaNAC6 (LOC101514169) was significantly FW inducible only in Ana (Figs. 4 and 6 ; Supplementary Table S2). NAC transcription factors are encoded in plants by a gene family with proposed functions in both biotic and abiotic stress adaptation, also in developmental procedures [ 59 ]. It is reported that expression of OsNAC6 ( Oryza sativa NAC6 ) in rice is induced by blast disease [ 60 ]. Upregulation of the NAC6 gene has previously been reported in barley, which promotes basal resistance against the virulent Blumeria graminis f. sp. hordei [ 59 , 61 ]. DEGs involved in cell wall integrity Some genes associated with cell wall modification and organization were either exclusively upregulated in the resistant cultivar (Ana) or more strongly upregulated in the resistant cultivar than in the susceptible cultivar, including polygalacturonase inhibitor 2-like ( CaPGI2-like : LOC105852278) (Fig. 6 ; Supplementary Table S2). The upregulation of a PGI gene has been previously reported in the FW-resistant desi landrace of chickpea in response to Foc race 2 [ 19 ]. Fungal pathogens often produce polygalacturonases (PGs) to break down pectin polymers and weaken the plant cell wall. Polygalacturonase-inhibiting proteins (PGIPs) are cell wall glycoproteins that can recognize and inhibit PGs, thereby reducing their hydrolytic activity and helping control fungal progression [ 62 , 63 ]. PGIPs interact with PGs via the Leu-rich repeat (LRR) structure. This characteristic of PGIPs is evolutionarily linked to many plant resistance genes (R genes) [ 64 , 65 ]. The PG–PGIP interaction also navigates the production of oligogalacturonides that elicit diverse defense responses (DR genes), including the expression of PR1 and salicylic acid-regulated genes [ 62 , 63 ]. The upregulation of a PGI gene has been previously reported in the FW-resistant desi landrace of chickpea in response to Foc2 [ 19 ]. Pectinesterase 2-like ( CaPE2 : LOC101508209) and probable pectinesterase/pectinesterase inhibitor 7 ( CaPME7 : LOC101489717) were upregulated in both cultivars while the induction was higher in the resistant cultivar. It has been reported that a Pectinesterase-like gene is involved in the synthesis and modification of cellulose, lignin, and other components found in different layers of the cell wall [ 66 , 67 ]. A pectinesterase-like gene was significantly upregulated in Musa acuminata under Pseudocercospora musae disease [ 68 ]. It is related to epicuticular wax, pectin biosynthesis, cell wall organization, and cell wall biogenesis [ 68 ]. Pectinesterase inhibitor genes play a role in reorganizing the cell wall and in the plant's defense against pathogen attacks [ 69 , 70 ]. Several expansin-like genes ( CaEXLB1 : LOC101489892 and LOC101507544; CaEXLA2 : LOC101514490) were exclusively expressed in Ana or were more highly upregulated in Ana than in Hashem (Fig. 6 ; Supplementary Table S2). Expansins (EXPs) are involved in plant development and responses to diverse stresses [ 71 ]. They are extracellular proteins that loosen plant cell walls in novel ways [ 72 ]. A role in the disease response was reported for EXLB1 , and the expression pattern of most EXP genes significantly changed during diverse infection times [ 73 ]. Three genes encoding cellulose synthase ( CaCSLD , such as LOC101509896, LOC101488214, and LOC101499287) were exclusively expressed/induced in Ana (Fig. 6 ; Supplementary Table S2). CSLD (cellulose synthase) contributes to glucan deposition and maintaining cell wall integrity during pathogen invasion [ 74 ]. It has been reported that the overexpression of type 3 CSLD prevents damage to the cell wall in resistant genotypes [ 17 ]. A gene encoding the cytochrome P450 CYP73A100-like (LOC101503511) was upregulated (logFC = 3.89) only in the Ana cultivar under Fusarium wilt (race 6). It has been reported that CYP73A100 is upregulated during Fusarium oxysporum infection and contributes to lignin synthesis and accumulation [ 75 ]. The expression of some CYP genes is controlled in response to environmental stresses, and they play a significant role in the crosstalk between biotic and abiotic stress responses [ 26 ]. CYPs hold significant potential as candidates for engineering crop species that are resilient to both abiotic and biotic stresses [ 26 ]. Transport-related DEGs The transport of essential elements to primary locations and during critical hours after infection affects the resistance network, where various groups of transporters play fundamental roles [ 17 ]. Several transport-related genes were upregulated in Ana, including calcium-transporting ATPase ( CaCa 2+ -ATPase : LOC101512366), cationic amino acid transporter 5 ( CaCAT5 : LOC101509123), and sulfate transporter 3.5 ( CaSULTR 3.5 : LOC101512274) (Fig. 6 ; Supplementary Table S2). Interestingly, the Ca 2+ -ATPase gene was also upregulated in previous studies on Foc races 1, 2, and 4 in resistant chickpea cultivars [ 18 , 19 ]. Some amino acid transporters (AATs), such as AtCAT1 ( Arabidopsis thaliana cationic amino acid transporter 1 ), positively affect the plant immune system. It has been reported that the overexpression of AtCAT1 results in the continuous expression of PR1 and SA-related genes, along with an increase in SA rates. Given that AtCAT1 expression rapidly responds to infection, AtCAT1 plays a role in plant systemic resistance [ 76 ]. Additionally, sulfur (SULTR) is considered a crucial macronutrient for plant growth, development, and response to several abiotic and biotic stresses [ 77 ]. In addition, GO analysis of molecular function showed that the term ‘nitrate transmembrane transporter activity’ was more enriched in Ana compared to the susceptible cultivar (Fig. 2 ). It has been reported that the tolerance of cucumbers to Fusarium wilt is enhanced by nitrate, which controls the production and distribution of fungal toxins [ 78 ]. Several transport-related genes were downregulated in Ana including nitrate reductase [NADH]-like ( CaNR/NADH : LOC101498580), bidirectional sugar transporter SWEETs ( CaSWEET13-like : LOC101491054, CaSWEET17 : LOC101509872 and CaSWEET1 : LOC101498274) and metal transporter Nramp5-like ( CaNRAMP5 : LOC101489317) (Fig. 6 ; Supplementary Table S2). Nitrate reductase (NIA2) is recognized for its role in regulating the biosynthesis and transport of nitric oxide (NO). It has been reported that the downregulation of NR/NADH in resistant plants is a probable strategy of the resistant host to counteract drought stress caused by phenolic deposition due to Foc1 invasion [ 17 ]. Furthermore, the regulation of sugar transporter and SWEET genes may play a role in plant defense against pathogen infection by adjusting the availability of sugar in the apoplasm [ 79 ]. Similar results were also reported during Foc race 2 infection in resistant and susceptible chickpea genotypes [ 19 ]. Additionally, the natural resistance-associated macrophage protein (NRAMP) gene family facilitates the transport of metal ions (NRAMP5 is a good example) in plants [ 80 ]. It has been reported that the downregulation of NRAMP5 significantly decreases the uptake and transport of manganese (Mn), which in turn activates enzymatic antioxidants. This enhances the capacity for ROS scavenging and boosts photosynthesis activity, thereby alleviating Mn toxicity in peach plants. [ 80 ]. Moreover, the protein DETOXIFICATION 27-like ( CaDTX27 : LOC101503133), located in the plasma membrane, was upregulated only in Ana. It belongs to the multiantimicrobial extrusion (MATE) family. MATE genes have been shown to be associated with disease resistance in Arabidopsis [ 81 , 82 ]. Likewise, it has been suggested that the protein DETOXIFICATION 48-like, encoding a MATE family protein, is related to defense activity against Foc (race 5) [ 15 ]. DEGs involved in metabolism Upon infection, the plant and pathogen compete to utilize the host's sugar metabolism, which in turn triggers either resistant or susceptible responses. Sugar-metabolizing enzymes are differentially regulated during plant–pathogen interactions. In the present study, two genes encoding putative UDP-glucose glucosyltransferase ( CaUFGT3 : UGT71S3 and CaUGT : UGT84F2) were upregulated in the resistant genotype (Fig. 6 ; Supplementary Table S2). This finding is consistent with previous reports showing that UDP-glucosyltransferases (UGTs) are involved in FW resistance in wheat and barley through glycosylating the deoxynivalenol produced by the Fusarium spp. fungus [ 83 ]. Furthermore, a cell wall isozyme-like beta-fructofuranosidase ( CaBF-CWI : LOC101513089) was upregulated in Ana (Fig. 6 ; Supplementary Table S2). It belongs to a class of sucrose-hydrolyzing enzymes known as invertases whose role in plant disease resistance has already been reported [ 84 ]. It is believed that CWINV1 (cell wall invertase 1) is the enzyme that plays a crucial role in the reconstruction of damaged cell walls [ 85 ]. Based on the results of the present study, alpha-amylase/subtilisin inhibitor-like ( ASI ; LOC101508812) was also induced in Ana (Fig. 6 ; Supplementary Table S2). ASI proteins play a significant role in plant defense mechanisms against pathogens, including fungi. They inhibit the activity of enzymes such as alpha-amylase and subtilisin, which are substantial for the growth and development of many pathogens [ 86 ]. In particular, these inhibitors can prevent the degradation of plant cell walls by fungal enzymes, thereby limiting the ability of pathogens to invade and cause disease [ 87 ]. Glutathione S-transferase ( CaGST : LOC101494465, LOC101506971, and LOC113787225) was upregulated in the resistant cultivar (Fig. 6 ; Supplementary Table S2). GSTs are involved in the detoxification of a vast variety of xenobiotic compounds [ 88 ]. It has been reported that the increase in GSTs after Foc1 attack impacts the maintenance of redox balance [ 17 , 89 ]. Also, GSTs combat toxin challenges that directly affect the cell cycle and cell division [ 14 ]. KEGG pathway analysis showed that the percentage of genes involved in the glutathione metabolism pathway in the resistant cultivar (Ana) was dramatically higher than that in the susceptible cultivar (Hashem) (Fig. 3 ). Trihydroxycinnamoyl spermidines ( CaSHT-like ; LOC101513347) were also upregulated in both cultivars, while the increase was more in the resistant cultivar (Fig. 6 ; Supplementary Table S2). THCSpds are specialized plant metabolites known for their significant pharmacological properties, including antifungal, antibacterial, and antiviral activities [ 90 ]. Moreover, the carbonic anhydrase 1 ( CaCA1 : LOC101498889) gene was found to be involved in the nitrogen metabolism pathway [ 14 ]; it has also been reported via transcriptome analysis that CA1 was identified in maize in response to Fusarium ear rot [ 91 ]. CAs are widespread enzymes that play crucial roles in essential processes such as photosynthesis, respiration, ion transport, and pH homeostasis [ 92 ]. Furthermore, CYP73A100, which is involved in the phenylpropanoid and flavonoid biosynthesis pathways, was detected (Fig. 6 ; Supplementary Table S2). It has been reported that some genes, such as CaCYP73A100 , are upregulated during treatment with exogenous melatonin and F. oxysporum . These genes are involved in the synthesis of p-coumaric acid, flavonol 3-O-ethyltransferase, and 4-coumarate-CoA ligase, which contribute to the accumulation of lignin [ 75 ]. Melatonin is regarded as a polyfunctional master regulator in both higher plants and animals. Studies have shown that exogenous melatonin treatment can efficiently manage cucumber green mottle mosaic virus (CGMMV) infection and enhance resistance to F. oxysporum in plants [ 75 , 93 ]. Upregulation of the CYP73A100 gene in other plants under biotic stress has also been shown; for instance, it was expressed in soybeans during infection with soybean cyst nematodes [ 94 ]. Conclusion Comparative analysis of the transcriptomic response of resistant and susceptible chickpea cultivars (Ana and Hashem, respectively) to race 6 of F. oxysporum f. sp. ciceris infection has provided some insights into the molecular mechanisms of resistance to FW in Cicer arietinum . Recognition of fungal pathogens by plants is the first critical step, which can lead to prompt activation of downstream defense signaling cascades and finally result in resistance. Remarkably, two receptor genes ( i.e., CaNLR-RPM1 and CaLYK5-RLK ) were exclusively expressed in Ana and upregulated under FW stress conditions. Some other RLKs and RLPs (including CaPR5-RLK , CaLRR-RLK , and CaRLP-EIX2 ) were also significantly induced by FW in the root tissues of Ana. Moreover, several genes involved in signaling (such as CaPP7, CaHSC70s, CaEPS1, CaSTY13 and CaSTY-OXI1 ) and transcription regulation ( CaMYBs , CaGLK , CaERFs , CaZAT11-like , and CaNAC6 ) were found to be overrepresented by FW stress in the resistant genotype. A rich set of genes related to defense responses ( e.g., CaPR-1 and CaPR-4 ) and cell wall integrity ( e.g., CaPGI2-like , CaPE2 , CaPME7 , CaEXLs , CaCSLD , CaCYP73A100-like ) were further identified in Ana, whereas they were not expressed in Hashem. Conclusively, the resistant genotype employs a subtle gene network, which helps in the early detection of pathogens and triggers prompt signaling pathways leading to the activation of an efficient defense response against fungal pathogens, thereby enhancing its disease resistance (Fig. 6 ; Supplementary Table S2). The achieved results could facilitate the use of genetic engineering or molecular breeding approaches to develop chickpea varieties resistant to Fusarium wilt. Methods Plant material The present study employed two chickpea cultivars, designated as Ana and Hashem, which exhibited contrasting resistance and susceptibility to Race 6. Both cultivars are of the Kabuli type, originating from the Dryland Agricultural Research Institute of Iran (DARI) (Supplementary Figures S1 and S2). The seeds of the two cultivars were sterilized for 10 minutes in 0.5% sodium hypochlorite (NaClO), rinsed with distilled water, and placed on dampened filter papers. On the third day, the uniformly germinated seeds were transferred to pots (6×6×8 cm) filled with pasteurized perlite in trays (41×56×12 cm). The plants were grown under controlled conditions at 25 ± 2°C with a 16/8 (day/night) photoperiod under fluorescent light and a relative humidity of 75%. Inoculation of Fusarium oxysporum f. sp. ciceris race 6 and evaluation of the pathogenicity response The race 6 isolate of Foc [ 95 ] was used in this study. The fungus was cultured in potato dextrose broth (PDB, 200 g potato: 20 g dextrose: 1 liter water) at a temperature of 28 to 30°C for 3 to 4 days on a shaker. The medium was then filtered through four layers of clean cloth and centrifuged at 7500 rpm for 14 minutes. The resulting conidia were used to prepare a spore suspension with a concentration of 10 6 conidia per ml. Twenty plants (replicating) of each cultivar along with the same number of susceptible control varieties, Kaka, were inoculated with the pathogen according to the methods of Pouralibaba et al. (2015) [ 96 ]. Approximately 1–3 cm of the root tips of the plants at the 4–5-leaf stage (approximately 12–14 days after planting) were cut with sterilized scissors. The root tips were subsequently immersed in the spore suspension for 10 min before being planted in pots filled with sterilized Perlite. The control plants were subjected to the same procedure but were given sterile water instead. Following inoculation, the pots were irrigated with a complete NPK 20–20–20 + TE solution (20 g/10-liter water). The reaction to the pathogenic fungus was scored based on the percentage of mortality [ 97 ]. The first data recording was done immediately after observing the first symptoms of yellow/wilt on the susceptible control plant, and the plants were evaluated at one-week intervals until the death of all control plants (approximately one month after the first disease evaluation). The last data recorded were considered the final plant reaction to the disease. For genotyping, root samples were collected at 48 hours postinoculation (hpi) from two biological replicates (each replicate included at least three individual plants) of inoculated and noninoculated plants. Previous experiments by several researchers revealed significant transcriptomic and proteomic changes at 48 hpi in chickpea-Foc1 interactions [ 17 , 98 ]. Therefore, a 48-hour period was selected as the ideal time point for sample collection and transcriptome analysis. The root samples from each cultivar were promptly frozen in liquid nitrogen and subsequently stored at -80°C. RNA extraction and mRNA sequencing For each biological replicate, equal amounts of root samples (collected at 48 hpi) from 8 single plants were pooled and ground. Total RNA was extracted from both inoculated and non-inoculated Ana and Hashem cultivars using TRIzol (Bio Basic, Canada) based on the manufacturer’s guidelines. The quality, quantity, and RNA integrity were evaluated by a NanoDrop ND-1000® spectrophotometer, agarose gel electrophoresis, and an Agilent 2100 Bioanalyzer system (Agilent Technologies Co. Ltd., Beijing, China). To avoid any genomic DNA contamination, RNA samples were treated with RNase-free DNase I (Thermo Scientific™) and subjected to PCR. Additionally, paired-end reads of 150 bp were generated with the Illumina HiSeq™ 2500 sequencing platform at Novogene Bioinformatics Institute (Beijing, China) for total root samples. RNA-seq data analysis The quality of the raw sequencing reads in FASTQ format was distinguished by FASTQC [ 99 ] software, and quality reads were confirmed based on phred score ≥ 30 (Q30). The high-quality paired-end reads were then mapped against the chickpea reference genome ( https://www.ncbi.nlm.nih.gov/assembly/GCF_000331145.1 ) utilizing HISAT2 [ 100 ]. A reference annotation-based transcript (RABT) assembly and the genome GFF were created by Cufflinks [ 101 , 102 ] using the aligned reads from each sample. The single assemblies were merged into a complete assembly using Cuffmerge with default parameters. Additionally, Cuffmerge was used to identify novel transcripts [ 101 ]. Differentially expressed genes (DEGs) were identified using Cuffdiff from the Cufflinks package, with thresholds set at − 1 ≤ log2-fold change ≥ 1 and a Q value cutoff ≤ 0.01. Also, Blastx was utilized for functional annotation of significant DEGs against the TAIR protein database using the ENSEMBL Genome Browser ( https://ensembl.gramene.org/Arabidopsis_thaliana/Tools/Blast ). Functional annotation and pathway analysis of significant DEGs For each cultivar, GO terms were assigned to significant DEGs using AgriGO website ( http://systemsbiology.cau.edu.cn/agriGOv2/ ) with an FDR cutoff ≤ 0.05. The contributions of significant DEGs to KEGG pathways were identified via the online KEGG automatic annotation server (KAAS) ( https://www.genome.jp/kegg/kaas/ ). Moreover, for pathway analysis of significant DEGs, MapMan (version 3.5.1) with a Q value cutoff of ≤ 0.01 and − 1 ≤ Log2-fold change ≥ 1 was used [ 103 ]. Mapping significant DEGs to Arabidopsis pathway genes led to the identification of genes involved in specific pathways [ 103 ]. Realtime PCR analysis Real-time PCR was applied to confirm the RNA-seq results. Twelve genes were selected from the panel of Fusarium wilt-responsive genes identified through the RNA-seq results. Gene-specific primers were designed using Oligo 7 (version 7.60; Molecular Biology Insights, Inc.; USA). The primers used for the selected genes are provided in Supplementary Table S1 . cDNA synthesis was done using a SinaClon cDNA synthesis kit (Cat. No: RT5201). Quantitative real-time PCR (qRT‒PCR) was performed on three biological replicates of both noninoculated and inoculated root samples using a LightCycler® 96 Real-Time PCR System (Roche Life Science, Germany) and HS‒qPCR Mix, 2x (SinaClon, Iran). GAPDH served as an internal control gene to normalize the gene expression values. The relative expression of the candidate genes was analyzed using the 2 − ΔΔCt method [ 104 ]. Declarations Acknowledgment The authors thank Dr. Fateme Loni, Dr. Nazanin Amirbakhtiar and Mr. Amir-Hossein Sadri for their valuable contributions/expert assistance. Data availability All the sequencing reads generated from Illumina HiSeq 2500 RNA-Seq are available from NCBI SRA under BioProject ID: PRJNA1050654 (https://submit.ncbi.nlm.nih.gov/subs/bioproject/SUB14017589/overview). All other data sets supporting this study are included in the article and its supplementary data. Author Contributions Z-S.S. designed the lab experiments and supervised the molecular part of the research. H.H-K. and H-R.P. supervised the plant culture, inoculation and phenotyping part of the research. A.F. performed the experiments and drafted the manuscript. A.F., S.D. and R.M-M. analyzed the data. Z-S.S. and R.M-M. revised the manuscript. All authors read and approved the final manuscript. 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Supplementary Files SupplementarydataFWTBMCS.docx Cite Share Download PDF Status: Published Journal Publication published 04 Feb, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 15 Oct, 2024 Editor assigned by journal 08 Oct, 2024 Submission checks completed at journal 08 Oct, 2024 First submitted to journal 06 Oct, 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5212429\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":366280892,\"identity\":\"3f00dc16-9443-42b2-8027-8176c35f6e72\",\"order_by\":0,\"name\":\"Aliakbar Faramarzpour\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Mohaghegh Ardabili\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Aliakbar\",\"middleName\":\"\",\"lastName\":\"Faramarzpour\",\"suffix\":\"\"},{\"id\":366280893,\"identity\":\"515ba23b-9764-4197-84c1-6dac8ddcac44\",\"order_by\":1,\"name\":\"Sara Dezhsetan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Mohaghegh Ardabili\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sara\",\"middleName\":\"\",\"lastName\":\"Dezhsetan\",\"suffix\":\"\"},{\"id\":366280894,\"identity\":\"c6653e10-20df-4233-81ce-eec1064faa09\",\"order_by\":2,\"name\":\"Hamid Hassaneian Khoshro\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Dryland Agricultural Research Institute (DARI)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hamid\",\"middleName\":\"Hassaneian\",\"lastName\":\"Khoshro\",\"suffix\":\"\"},{\"id\":366280895,\"identity\":\"11a67acf-c7da-4ef8-bc16-5a948a0fd5ab\",\"order_by\":3,\"name\":\"Raheleh Mirdar Mansuri\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Raheleh\",\"middleName\":\"Mirdar\",\"lastName\":\"Mansuri\",\"suffix\":\"\"},{\"id\":366280896,\"identity\":\"f05a02c2-775f-48c5-af89-783c97afde06\",\"order_by\":4,\"name\":\"Hamid Reza Pouralibaba\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Dryland Agricultural Research Institute (DARI)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hamid\",\"middleName\":\"Reza\",\"lastName\":\"Pouralibaba\",\"suffix\":\"\"},{\"id\":366280897,\"identity\":\"1c316fc6-0abe-486f-afed-23bb6978df49\",\"order_by\":5,\"name\":\"Zahra-Sadat Shobbar\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACCQY2ZiAlB2QwHEgAiTATqcWYdC2JDRLEukt+dvOxxwU199L7Z/c+PPCAwU6egZ33AV4tBneOpRvPOFacO+POcQOgw5ING5jZDfBrkcgxk+ZhS8htuJEG8gszELERcNgMkJZ/CenyEC31hLUw3ABq4W1LSDCAaDlMWAtQZbrxzL4Ew413jgG1GBw3bCPssGRgiH1LkJe73cb88UdFtTw//zECDkOzlIGBkE9GwSgYBaNgFBABABgaPers3jbFAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO)\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Zahra-Sadat\",\"middleName\":\"\",\"lastName\":\"Shobbar\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-10-06 10:38:09\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5212429/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5212429/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12864-025-11308-3\",\"type\":\"published\",\"date\":\"2025-02-04T15:57:49+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":70581031,\"identity\":\"663bb871-a189-4062-ad37-928f6ce16018\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:10:03\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":299903,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eA Venn diagram of the DEGs under Fusarium wilt stress revealed the genes that were exclusively expressed in each cultivar. Up: Upregulated; Down: Downregulated.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/6fd7153ca1e5a7f14d86d23f.png\"},{\"id\":70583612,\"identity\":\"99bcf777-60f2-4e0b-9ea3-e2d0b6bbd6a4\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:26:03\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":586459,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eGene Ontology (GO) classification of differentially expressed genes (DEGs) in the Ana (A) and Hashem (H) cultivars based on three main categories: biological process (BP), molecular function (MF) and cellular component (CC). The X-axis represents the percentage of transcripts, and the Y-axis represents the three main ontologies. Red, blue and pink bars represent the percentage of transcripts in the Ana cultivar (A). Yellow, green and light blue bars represent the percentage of transcripts in the Hashem cultivar (H).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/1dc252c0b3cad74d07a5a67b.png\"},{\"id\":70581720,\"identity\":\"029f2a8a-8fe9-4744-837d-d8c560925330\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:18:03\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":147303,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe top eight pathways with the greatest number of genes in the KEGG protein database.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/2c63e85846140a88334d2ff4.png\"},{\"id\":70583928,\"identity\":\"67c5c576-b06e-49bd-ba10-39ae7d6afce8\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:34:04\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1413396,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eHeatmap analysis of important differentially expressed genes (DEGs) with a Q value cutoff of ≤0.01 and a −1≤Log2-fold change ≥1 under Fusarium wilt (race 6) stress conditions at 48 hpi in the resistant versus susceptible chickpea cultivars. Blue indicates upregulated expression, and green indicates downregulated expression upon stress.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/fedeff4e6d38595ae2e6dfb8.png\"},{\"id\":70579826,\"identity\":\"60f99066-7575-413c-a583-6661add12e27\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:02:03\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":273384,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eValidation of twelve candidate genes via qRT‒PCR.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/9965566217804a006541f955.png\"},{\"id\":70581035,\"identity\":\"6eb38b1d-6af8-4b38-9d83-4e0bd4f903a2\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:10:04\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":987986,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAn eagle view of significant genes and functional pathways involved in chickpea‒Fusarium interactions in resistant cultivars (Ana). Up arrow: upregulation; down arrow: downregulation.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/0e7e589965edcddd23c2dab2.png\"},{\"id\":75931198,\"identity\":\"2b011bec-fa35-4911-81e8-5a48562600db\",\"added_by\":\"auto\",\"created_at\":\"2025-02-10 16:14:03\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":4842672,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/ea6d0b83-7661-40d1-adbc-fbf488170452.pdf\"},{\"id\":70579832,\"identity\":\"1c024dfa-99ef-4210-8385-29e5d55b4ccb\",\"added_by\":\"auto\",\"created_at\":\"2024-12-04 15:02:04\",\"extension\":\"docx\",\"order_by\":9,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":6529365,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementarydataFWTBMCS.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5212429/v1/ffca79d831cacaba4692ebfa.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Unraveling the transcriptional response mechanisms to yellow and wilt disease, caused by race 6 of Fusarium oxysporum f.sp. ciceris in two contrasting chickpea cultivars\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eChickpea (\\u003cem\\u003eCicer arientinum\\u003c/em\\u003e L.), classified as the third most important grain legume, is commonly known as a low-cost protein source for both livestock feed and human consumption [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. It contains many carbohydrates, lipids, minerals, vitamins, and other nonnutritive compounds that are beneficial to health [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]. Moreover, it has a significant impact on sustaining agricultural systems through nitrogen fixation, similar to other legumes [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Chickpea is produced about 16\\u0026nbsp;million tons annually [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]. It is mainly cultivated in 50 countries and grown in a variety of ecological conditions; however, its yield and quality are affected by several challenges, such as fungal diseases [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAmong the fungal diseases, Fusarium wilt (FW) induced by \\u003cem\\u003eFusarium oxysporum\\u003c/em\\u003e f. sp. \\u003cem\\u003eciceris\\u003c/em\\u003e (Foc) is a widespread soil-borne disease that causes a significant reduction in chickpea production [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. According to reports, Foc penetrates the roots through epidermal cells, and subsequently, hyphae spread to the root cortex region, where they colonize the xylem vessels. All of these factors prevent the upward movement of water and essential solutes, which results in wilting. The initial symptom of the infection is wilting, which ultimately results in death [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. Fusarium wilt epidemics can result in the destruction or complete loss of crops in fields that are highly infested under favorable conditions [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eEight distinct physiological races of the pathogen, identified as 0, 1A, 1B/C, 2, 3, 4, 5, and 6, have been found to infect chickpea [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Races 1A, 2, 3, 4, 5, and 6 cause wilting symptoms in chickpea, characterized by flaccidity, severe chlorosis, and vascular discoloration, eventually leading to plant death. In contrast, races 1B/C and 0 are less virulent, causing only yellowing symptoms[\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eDespite the availability of complete sequencing of desi and kabuli chickpea genomes [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. The genes responsible for Fusarium resistance are poorly understood. Recently, researchers have employed the RNA-seq technique to identify stress-related genes involved in the response to FW. These authors reported several overrepresented genes related to the defense signaling pathway, disease resistance, and cell wall biogenesis in root tissues [\\u003cspan additionalcitationids=\\\"CR15 CR16 CR17 CR18\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Various attempts have been made to dissect the genetic basis of resistance to different FW races in chickpea. Thus, some genes and quantitative trait loci (QTLs) have been identified in various chickpea genotypes to be associated with resistance to certain Foc races. However, limited data are available regarding the genetics of resistance to some Fusarium races, such as races 6 and 1B/C [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eHerein, we conducted a comparative transcriptome study of root tissues of Iranian contrasting genotypes named Ana (a resistant genotype) and Hashem (a susceptible genotype) to Foc race 6. This research focused on root tissues as the initial organ, which serves as the first line of defense against phytopathogens and is crucial for sensing and signaling during Fusarium infection. Our results revealed differential expression patterns between resistant and susceptible cultivars 48 hours after the onset of infection. This study investigated transcriptome dynamics linked to FW disease in chickpea, highlighting crucial factors that influence disease resistance. Specific and differential expression patterns of genes were identified between resistant and susceptible cultivars. These findings provide a basis for further investigations to elucidate the molecular mechanisms underlying resistance in cultivars compared with susceptibility during Fusarium infection.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePhenotyping\\u003c/h2\\u003e \\u003cp\\u003eThe first Fusarium disease symptoms appeared on the lower leaves of the plants approximately 12 days after inoculation. The symptoms started with slight yellowing at the leaf edges and progressed to twisting and complete yellowing. Finally, the leaves become necrotic and fall. The reaction of two cultivars, Ana and Hashem, to Fusarium disease (Race 6) under controlled conditions was marked by early onset of wilt symptoms (distinct and consistent disease phenotypes), based on the method proposed by Sharma et al. in 2005 [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. The percentages of FW incidence in the Ana and Hashem cultivars were 20% (resistant) and 80% (susceptible), respectively (Supplementary Figure \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e and S2).\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eSequencing metrics and mapping results\\u003c/h3\\u003e\\n\\u003cp\\u003eIn total, 133.5\\u0026nbsp;million raw reads were obtained from the root samples of the Ana and Hashem cultivars under control and FW stress conditions, and more than 89.15% of the raw reads presented Phred quality scores at the Q30 level. Additionally, almost 90% of the clean reads were mapped to the chickpea reference genome (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The assembly of mapped reads led to the recognition of 61997 transcript isoforms and 31177 genes. The results indicated that 518 (317 up- and 201 downregulated) and 1063 (587 up- and 476 downregulated) genes were differentially expressed under Foc race 6 stress in the resistant and susceptible cultivars, respectively (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\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\\u003eSummary statistics of the transcriptome reads and their mapping to the reference genome.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\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 \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eReads mapping\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c4\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eReads number (%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAna Control\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAna Treated 1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eAna Treated 2\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal reads\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20974728\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22881594\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e21195569\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal mapped reads\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19069583 (90.92%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20879587 (91.25%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e19082588 (90.03%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnique match\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18203933 (86.79%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e19924028 (87.07%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e18397275 (86.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMultiposition match\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e865650 (4.13%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e955559 (4.18%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e685313 (3.23%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal unmapped reads\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1905145 (9.08%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2002007 (8.75%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2112981 (9.97%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSample\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHashem Control\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eHashem Treated 1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eHashem Treated 2\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal reads\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e23529811\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e23872344\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e21044139\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal mapped reads\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e21229993 (90.22%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e21429429 (89.77%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e18890896 (89.76%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnique match\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20299725 (86.27%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20633219 (86.43%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e18132422 (86.16%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMultiposition match\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e930268 (3.95%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e796210 (3.34%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e758474 (3.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal unmapped reads\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2299818 (9.77%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2442915 (10.23%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2153243 (10.23%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eGene Ontology classification analysis for DEGs\\u003c/h3\\u003e\\n\\u003cp\\u003eBased on the GO analysis, significant GO terms were assigned to 193 (of 558) DEGs Ana and 333 (of 1085) DEGs Hashem. Moreover, the results demonstrated that several biological procedures, including defense response, response to stress, response to biotic stimulus, metabolic process, and primary metabolic process, were significantly enriched in both cultivars, with their percentages being somewhat greater in the Ana cultivar than in the Hashem cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Remarkably, some biological processes, such as the response to ethylene stimulus and the regulation of flavonoid biosynthetic processes, were significantly enriched only in the resistant cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). In the molecular function category, hydrolase activity, catalytic activity, oxidoreductase activity, transferase activity, transcription regulator activity and transcription factor activity were highly enriched in both cultivars; however, their percentages in the Ana cultivar were dramatically greater than those in the Hashem cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). The terms lyase activity, lipase activity, cellulose synthase activity, triglyceride lipase activity, triglyceride lipase activity, peptidase inhibitor activity, nitrate transmembrane transporter activity, and chitinase activity were significantly enriched only in the Ana cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). On the one hand, some cellular component terms, including membrane, cell part, cell wall, external encapsulating structure, and extracellular region, were dramatically enriched in the resistant cultivar compared with the susceptible cultivar. Furthermore, the chloroplast part was enriched only in the susceptible cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003ePathway analysis of DEGs\\u003c/h3\\u003e\\n\\u003cp\\u003eTo achieve a more comprehensive understanding of the pathways involved in the response of each cultivar to FW stress, a BLAST search against the KEGG protein database was carried out [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. In total, 218 of the 553 Ana significant DEGs were categorized into 121 KEGG pathways, and 443 of the 1118 Hashem significant DEGs were categorized into 173 KEGG pathways, consisting of five main KEGG classes: genetic information processing, cellular processes, metabolism, environmental information processing, and organismal systems. These genes mainly belong to the following KEGG pathways: MAPK signaling pathway-plant, plant‒pathogen interaction, plant hormone signal transduction, glycolysis/gluconeogenesis, glutathione metabolism, phenylpropanoid biosynthesis, flavonoid biosynthesis, cytochrome P450, nitrogen metabolism, ubiquinone, ABC transporters, other terpenoid‒quinone biosynthesis, transcription factors, glycosyltransferases, protein kinases, transporters and exosomes (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). The phenylpropanoid pathway, which had the most number of genes, is a metabolic pathway responsible for the synthesis of various plant secondary metabolites, containing lignin, flavonoids, lignans, phenylpropanoid esters, sporopollenin and hydroxycinnamic acid amides[\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. The cytochrome P450 pathway, which had the second most number of genes in the Ana cultivar, is a transcription factor linked to plant stress responses [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. Additionally, the percentages of genes belonged to cytochrome P450, glutathione metabolism and flavonoid biosynthesis pathways in the Ana cultivar were higher than those in the Hashem cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e). \\\"Proteomic and metabolomic analyses of chickpea\\u0026ndash;Foc interactions showed that numerous metabolic pathways, phenylpropanoid, isoflavonoid, and flavonoid biosynthesis pathways, were significantly upregulated in the resistant genotype. Proteomic and metabolomic studies of chickpea\\u0026ndash;Foc interactions revealed that many metabolic pathways, including the phenylpropanoid, isoflavonoid, and flavonoid biosynthesis pathways, were significantly upregulated in the resistant genotype [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\\n\\u003ch3\\u003eOverview of the biotic stress pathway\\u003c/h3\\u003e\\n\\u003cp\\u003eTo comprehend the various defense responses in the resistant and susceptible cultivars at the initial stage of Foc race 6 infection, MapMan analysis was used to investigate fluctuations in the significant DEGs in both cultivars under biotic stress. Also, the putative involvement of significant DEGs in the biotic stress response pathways was visualized using MapMan software (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figures S4 and S5). On the basis of the MapMan analysis results, several genes located in the cell wall, such as pectinesterase 2-like (LOC101508209), probable pectinesterase/pectinesterase inhibitor 7 (LOC101489717) and expansin-like B1 (LOC101489892 and LOC101507544), were more highly upregulated in the resistant cultivar (Ana) than in the susceptible cultivar (Hashem). In addition, some genes related to the cell wall were upregulated exclusively in the resistant cultivar, including polygalacturonase inhibitor 2-like (LOC105852278) and probable xyloglucan endotransglucosylase/hydrolase protein 23 (\\u003cem\\u003eCaXTH23\\u003c/em\\u003e: LOC101489989 and LOC101490102), which have logFCs of 3.87, 4.55 and 2.9, respectively (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figure S4 and S5). On the other hand, in the GO analysis, some cellular component terms assigned to the cell wall category were more sharply enriched in the resistant cultivar than in the susceptible cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eTwo genes encoding glutathione S-transferase (GST; LOC101494465 and LOC113787225) were upregulated only in the resistant cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figure S4 and S5). One gene encoding the transcription factor MYB41 (LOC101497118) was highly upregulated only in the resistant cultivar under FW stress (logFC\\u0026thinsp;=\\u0026thinsp;4.71) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figure S4 and S5). Furthermore, several genes encoding pathogenesis-related proteins (LOC101499251, LOC105851085, and LOC101510493) were exclusively upregulated in the resistant cultivar. Some individual genes encoding proteolysis components, such as basic 7S globulin-like (\\u003cem\\u003eCaBg7S-like\\u003c/em\\u003e: LOC101509822), senescence-specific cysteine protease Ca\\u003cem\\u003eSAG39-like\\u003c/em\\u003e (LOC101497435) and uncharacterized (ncRNA; LOC113785693), were upregulated only in resistant plants under Fusarium wilt disease stress (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Figure S4 and S5).\\u003c/p\\u003e \\u003cp\\u003eInterestingly, a gene encoding the cytochrome P450 CYP73A100-like (\\u003cem\\u003eCaCYP73A100-like\\u003c/em\\u003e: LOC101503511) was upregulated (logFC\\u0026thinsp;=\\u0026thinsp;3.89) only in the Ana cultivar under Fusarium wilt (race 6). On the other hand, analysis of biotic stress by MapMan software revealed that in the hormone signaling part (Auxins), several genes encoding cytochrome P450 (LOC101510162, LOC101494883, and LOC101510201) were downregulated only in resistant plants (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figure S4 and S5).\\u003c/p\\u003e \\u003cp\\u003eThe results of MapMan showed that genes encoding the protein EXORDIUM-like (LOC101501686 and LOC101502011) were more upregulated in the Ana cultivar (resistant) than in the Hashem cultivar (susceptible). The protein LYK5 (LOC101494861) on chromosome 2 was upregulated only in the resistant cultivar, but another gene encoding the protein LYK5-like (LOC101501405) was downregulated in the susceptible cultivar. On the other hand, we found some uncharacterized genes that were upregulated only in the resistant cultivar (LOC113785810, LOC101496586 and LOC113788231), and some of them were ncRNAs (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figure S4 and S5).\\u003c/p\\u003e \\u003cp\\u003eThe secondary metabolism pathway analysis of differentially expressed genes by MapMan determined that several genes encoding laccase-7-like (LOC101515697), 3-isopropylmalate dehydratase large subunit, chloroplastic-like (LOC101494361) and uncharacterized (LOC101511595) genes were more highly upregulated in the Ana cultivar than in the Hashem cultivar. Moreover, a gene encoding shikimate O-hydroxy cinnamoyl transferase-like (LOC101501659) was upregulated only in the Ana cultivar in response to Fusarium wilt disease (Supplementary Figure S4 and S5). Although a gene encoding chalcone-flavonone isomerase 2-like (LOC101508130) was highly downregulated in the resistant cultivar under Fusarium wilt disease (logFC= -10), another gene encoding chalcone-flavonone isomerase 2 (LOC101500746) was slightly upregulated in the susceptible cultivar (logFC\\u0026thinsp;=\\u0026thinsp;1.59) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Supplementary Figure S4 and S5).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eConfirming DEGs using qRT‒PCR\\u003c/h2\\u003e \\u003cp\\u003eIn order to validate the RNA-seq results, the expression patterns of twelve FW-responsive candidate genes were inspected by qRT‒PCR (quantitative real-time PCR) in the resistant and susceptible cultivars (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The selected genes were as follows; LOC101491624 (linoleate 9S-lipoxygenase-like), LOC101501931 (heat shock cognate 70 kDa protein 2), LOC101495891 (1-aminocyclopropane-1-carboxylate oxidase), LOC101513977 (probable leucine-rich repeat receptor-like serine/threonine-protein kinase), LOC101493121 (protein ENHANCED PSEUDOMONAS SUSCEPTIBILTY 1), LOC101497118 (transcription factor MYB41), LOC101510034 (basic 7S globulin-like), LOC101513347 (spermidine hydroxycinnamoyl transferase-like), LOC101489892 (expansin-like B1), LOC101495793 (MATH and LRR domain-containing protein PFE0570w), LOC101507324 (putative protein TPRXL) and LOC101498889 (carbonic anhydrase 1) (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The results of the qRT‒PCR confirmed the RNA‒Seq results for both chickpea cultivars (in Ana; R\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.999 and in Hashem; R\\u003csup\\u003e2\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.987).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eChickpea is an excellent source of protein for a large population worldwide, especially in Asia. It can serve as an alternative to fallow periods in cereal crop rotations, but FW disease causes significant economic losses in its production. Therefore, identifying the resistance mechanism to this disease in chickpeas is crucial [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. Next-generation RNA-seq provided a comprehensive comparison between Ana (a resistant cultivar) and Hashem (a susceptible cultivar) in this research. Through transcriptome analysis, we identified differential gene expression patterns between Ana and Hashem. Several genes involved in disease resistance pathways that have been previously reported in chickpea and/or other plants were differentially expressed in Ana, as discussed below (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and Supplementary Table S2).\\u003c/p\\u003e\\n\\u003ch3\\u003eDEGs involved in pathogen sensing\\u003c/h3\\u003e\\n\\u003cp\\u003eTo sense pathogens in a timely manner, resistant plants express many RLKs and RLPs as recognition receptors (PRRs), which act as the first layer of inducible defenses during the early stages of tension [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. The downstream defense signaling cascades are activated on time when the resistant cultivar detects the pathogen early [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Interestingly, several receptor genes, including \\u003cem\\u003eCaNLR-RPM1\\u003c/em\\u003e (Nucleotide-binding site leucine-rich repeat-disease resistance protein RPM1; LOC101504665), \\u003cem\\u003eCaLYK5/PR5-RLK\\u003c/em\\u003e (Lysin Motif Receptor-Like Kinase5/Pathogenesis related5-receptor like kinase; OC101494861 and LOC101493461), \\u003cem\\u003eCaLRR-RLK\\u003c/em\\u003e (Leucine-rich repeat-receptor like kinases; LOC101489235 and LOC101513977) and \\u003cem\\u003eCaRLP-EIX2\\u003c/em\\u003e (Receptor-like protein-Ethylene inducing xylanase2; LOC101498360), were significantly induced by FW in the root tissues of Ana (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and Supplementary Table S2). It is noteworthy that transcripts of \\u003cem\\u003eCaNLR-RPM1\\u003c/em\\u003e (LOC101504665) and \\u003cem\\u003eCaLYK5-RLK\\u003c/em\\u003e (LOC101494861) were exclusively detected in Ana, and considerably increased under FW stress conditions (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and Supplementary Table S2).\\u003c/p\\u003e \\u003cp\\u003eNLR-RPM1 is a plant intracellular immune receptor that specifically detects pathogen-released effectors, initiating effector-triggered immunity (ETI). This activation of ETI by NLR-RPM1 leads to a hypersensitive response (HR), which is a type of localized cell death that helps to restrict pathogen spread and boost disease resistance [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]. LYK5-RLK is a major type of chitin receptor from the LRR-RLK class. Upon the detection of chitin, a constituent of fungal cell walls, LYK5 forms a complex with another receptor kinase to stimulate immune signaling pathways [\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. PR5-RLK is involved in distinguishing pathogen-associated molecular patterns (PAMPs) and triggering immune responses in plants [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. RLP-EIX2 is known for recognizing and responding to the fungal protein ethylene-inducing xylanase (EIX). This interaction triggers defense mechanisms in plants, helping them fend off fungal pathogens [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e]. RLP-EIX2 is structurally similar to other receptor-like proteins found in various plants, which rely on pattern recognition receptors (PRRs) to detect PAMPs and initiate defense responses [\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDEGs involved in signaling pathways\\u003c/h2\\u003e \\u003cp\\u003eSeveral genes involved in signaling pathways were upregulated under FW stress either exclusively in the resistant cultivar or to a greater extent than in the susceptible cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and Supplementary Table S2). For example, \\u003cem\\u003eserine/threonine-protein phosphatase 7\\u003c/em\\u003e (\\u003cem\\u003eCaPP7\\u003c/em\\u003e: LOC105852653) and \\u003cem\\u003eheat shock cognate 70 kDa protein 2\\u003c/em\\u003e (\\u003cem\\u003eCa HSC70s\\u003c/em\\u003e; LOC101501931) might play roles in MAPK (mitogen-activated protein kinase) signaling. PP7 is implicated in the dephosphorylation of specific proteins, which can activate or deactivate signaling pathways related to plant defense mechanisms such as MAPK and oxidative stress signaling [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e]. HSC70 belongs to the heat shock protein 70 (Hsp70) family and operates as a molecular chaperone. It can interact with various components of the MAPK pathway, maintaining its activity [\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. It has been reported that \\u003cem\\u003eHSC70s\\u003c/em\\u003e are highly upregulated in chickpea, sunflower, and cabbage after infection with Foc [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSeveral genes associated with the hormone signaling pathway, including components of jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), ethylene (ET) and auxin (AUX), were differentially expressed after Foc infection (Figure S4). Among them, some components of SA were found in Ana, such as \\u003cem\\u003eENHANCED PSEUDOMONAS SUSCEPTIBILITY 1\\u003c/em\\u003e (\\u003cem\\u003eCaEPS1\\u003c/em\\u003e: LOC101493121) (log2 FC\\u0026thinsp;=\\u0026thinsp;1.78), whereas it was not expressed in Hashem. \\u003cem\\u003eEPS1\\u003c/em\\u003e is an isochorismate-9-glutamate pyruvoyl-glutamate lyase that can degrade N-pyruvoyl-L-glutamate to generate SA [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. Salicylic acid, an important signaling molecule, can induce resistance to diseases such as Fusarium. SA is reported to be a mediator between plants and microbes, which activates resistance against Fusarium [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eMoreover, two genes encoding pathogenesis-related (PR) proteins (\\u003cem\\u003eCaPR-1\\u003c/em\\u003e: LOC101503659, \\u003cem\\u003eCaPR-4\\u003c/em\\u003e: LOC101511048) were significantly induced in Ana (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and Supplementary Table S2). PR-1-like proteins are part of a larger family of PR proteins that are typically induced in response to pathogen attack and are involved in SAR (systemic acquired resistance). They are often associated with the SA signaling pathway, which is crucial for activating defense responses [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. PR-4 proteins constitute another class of PR proteins that are often associated with the JA signaling pathway, which is also crucial for defense against pathogens [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. Both the PR-1-like and PR-4 proteins have antimicrobial activity. PR-4 proteins often exhibit chitinase activity, which allows them to break down chitin. This activity helps prevent the growth and spread of fungi [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eFurthermore, we identified several genes associated with the PR5 (Pathogenesis-related 5) family in Ana that are known as thaumatin-like proteins (TLPs; \\u003cem\\u003eCaTLP1b\\u003c/em\\u003e (LOC101495985) and \\u003cem\\u003eCansLTP-like\\u003c/em\\u003e (LOC101503860)). TLPs have been increasingly demonstrated to contribute to resistance against various fungal diseases, including Fusarium, in numerous crop plants, especially legumes. They may also play a role in the crosstalk between different hormone responses [\\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e44\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSeveral genes related to TOR (target of rapamycin) signaling pathway, including \\u003cem\\u003eCaSTY13\\u003c/em\\u003e (LOC101511109) and \\u003cem\\u003eCaSTY-OXI1\\u003c/em\\u003e (LOC101501979), were highly upregulated in the resistant cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e and Supplementary Table S2). Serine/threonine-protein kinase TOR proteins are reported to be significantly expressed during infection by pathogens in chickpeas and regulate both catabolic and anabolic processes, such as cell cycle regulation, cell growth, mitochondrial signaling, secondary metabolism and apoptosis, cell wall structure, and development [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e]. The overexpression of serine/threonine-protein kinases in chickpea-Foc1 interaction has also been reported in various resistant genotypes at different time points [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. This excessive expression was predominantly found in the cell wall, which causes cell wall integrity after the onset of infection [\\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDEGs involved in transcription regulation\\u003c/h2\\u003e \\u003cp\\u003eTranscription factors (TFs) are essential in plant defense, regulating the expression of genes that react to pathogen attacks [\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e]. Transcriptional reprogramming happens after triggering a signaling cascade by various transcription factors (TFs), which activate genes involved in hormonal control and other processes, including PR genes and structural genes. [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. GO analysis showed that the term \\u0026lsquo;transcription regulator activity\\u0026rsquo; was dramatically enriched in the Ana cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eAmong them, some MYBs (\\u003cem\\u003eCaMYB41\\u003c/em\\u003e: LOC101497118; \\u003cem\\u003eCaMYB108\\u003c/em\\u003e: LOC101490747; LOC101492267), MYB-related (LOC101507725) and G2. Like (\\u003cem\\u003eCaGLK\\u003c/em\\u003e: LOC101491042) was significantly upregulated by FW only in the resistant cultivar (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). MYBs are a major group of TFs that have a variety of roles in eukaryotes, including responses to wounding and pathogens [\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e]. \\u003cem\\u003eMYB108\\u003c/em\\u003e was previously reported in Arabidopsis, which controls the infection of two pathogens by stimulating defense-related genes (DR Genes); \\u003cem\\u003ePDF1\\u0026ndash;2\\u003c/em\\u003e and \\u003cem\\u003ePR-1\\u003c/em\\u003e, through ethylene and JA signaling pathways [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. \\u003cem\\u003eAtMYB108\\u003c/em\\u003e is an \\u003cem\\u003eR2R3MYB\\u003c/em\\u003e protein that modulates responses to both biotic and abiotic stresses [\\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e]. R2R3MYB has been found to increase resistance to \\u003cem\\u003eBipolaris sorokiniana\\u003c/em\\u003e root rot fungus, as well as enhancing the expression of PR1a, PR2, and TLP4 genes through the SA and ABA signaling pathways [\\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e]. Furthermore, overexpression of \\u003cem\\u003eAtMYB41\\u003c/em\\u003e has been reported to activate monolignol and suberin-associated wax biosynthesis, as well as the formation of suberin-like lamellae in the cell walls of both epidermal and mesophyll cells, which eventually protects against biotic and abiotic stresses [\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e]. Furthermore, we found a gene coding GOLDEN2-LIKE (GLK) belonging to the MYB family in Ana. \\u003cem\\u003eGOLDEN2-LIKE\\u003c/em\\u003e (\\u003cem\\u003eGLK\\u003c/em\\u003e) plays a significant role in regulating plastid development and stress tolerance [\\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e]. GLKs play a positive role in virus resistance against cucumber mosaic virus (CMV) in Arabidopsis by modulating the expression of defense-associated genes and the antioxidant system, which is partially associated with the accumulation of JA and SA [\\u003cspan citationid=\\\"CR53\\\" class=\\\"CitationRef\\\"\\u003e53\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSome ERFs (\\u003cem\\u003eCaERF9\\u003c/em\\u003e: LOC101502158, \\u003cem\\u003eCaERF113\\u003c/em\\u003e: LOC101515629, and \\u003cem\\u003eCaERF113-like\\u003c/em\\u003e: LOC101513362) were also significantly upregulated by FW, specifically in Ana (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). The ERF (ethylene-responsive transcription factor) is a subfamily of the AP2/ERF family and plays essential roles in the regulation of biotic stress responses. Utmost \\u003cem\\u003eERF\\u003c/em\\u003e proteins can bind to GCC box-containing promoters, which are found in the promoters of many pathogenesis-related (\\u003cem\\u003ePR\\u003c/em\\u003e) genes, such as PRb-1b (PR1), β-1,3-glucanase (\\u003cem\\u003ePR2\\u003c/em\\u003e), chitinase (\\u003cem\\u003ePR3\\u003c/em\\u003e) and osmotin (\\u003cem\\u003ePR5\\u003c/em\\u003e), and mediate the vital role of these genes in plant responses to biotic stress [\\u003cspan citationid=\\\"CR54\\\" class=\\\"CitationRef\\\"\\u003e54\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR55\\\" class=\\\"CitationRef\\\"\\u003e55\\u003c/span\\u003e]. It has been reported that ethylene signaling acts a vital role in cucumber resistance against Foc [\\u003cspan citationid=\\\"CR56\\\" class=\\\"CitationRef\\\"\\u003e56\\u003c/span\\u003e]. Consistent with the findings of a previous study [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e], we also found that the \\u003cem\\u003eCaERF113\\u003c/em\\u003e gene (LOC101515629) was upregulated in the resistant cultivar under FW stress.\\u003c/p\\u003e \\u003cp\\u003eFurthermore, some \\u003cem\\u003eC2H2s\\u003c/em\\u003e (\\u003cem\\u003eCaZAT11-like\\u003c/em\\u003e: LOC101498044 and LOC101492538) were exclusively shown significant upregulation by FW in Ana (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). C2-H2-type proteins (TFs) are involved in regulating the signaling pathway during biotic stress [\\u003cspan citationid=\\\"CR57\\\" class=\\\"CitationRef\\\"\\u003e57\\u003c/span\\u003e]. Previous reports have demonstrated that the transcript abundance of \\u003cem\\u003eZAT11\\u003c/em\\u003e can be highly induced by H2O2; \\u003cem\\u003eZAT11\\u003c/em\\u003e was shown to be involved in paraquat-induced oxidative stress, which leads to programmed cell death [\\u003cspan citationid=\\\"CR58\\\" class=\\\"CitationRef\\\"\\u003e58\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eCaNAC6\\u003c/em\\u003e (LOC101514169) was significantly FW inducible only in Ana (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). NAC transcription factors are encoded in plants by a gene family with proposed functions in both biotic and abiotic stress adaptation, also in developmental procedures [\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e]. It is reported that expression of \\u003cem\\u003eOsNAC6\\u003c/em\\u003e (\\u003cem\\u003eOryza sativa NAC6\\u003c/em\\u003e) in rice is induced by blast disease [\\u003cspan citationid=\\\"CR60\\\" class=\\\"CitationRef\\\"\\u003e60\\u003c/span\\u003e]. Upregulation of the \\u003cem\\u003eNAC6\\u003c/em\\u003e gene has previously been reported in barley, which promotes basal resistance against the virulent \\u003cem\\u003eBlumeria graminis\\u003c/em\\u003e f. sp. \\u003cem\\u003ehordei\\u003c/em\\u003e [\\u003cspan citationid=\\\"CR59\\\" class=\\\"CitationRef\\\"\\u003e59\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR61\\\" class=\\\"CitationRef\\\"\\u003e61\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDEGs involved in cell wall integrity\\u003c/h2\\u003e \\u003cp\\u003eSome genes associated with cell wall modification and organization were either exclusively upregulated in the resistant cultivar (Ana) or more strongly upregulated in the resistant cultivar than in the susceptible cultivar, including polygalacturonase inhibitor 2-like (\\u003cem\\u003eCaPGI2-like\\u003c/em\\u003e: LOC105852278) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). The upregulation of a \\u003cem\\u003ePGI\\u003c/em\\u003e gene has been previously reported in the FW-resistant desi landrace of chickpea in response to Foc race 2 [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Fungal pathogens often produce polygalacturonases (PGs) to break down pectin polymers and weaken the plant cell wall. Polygalacturonase-inhibiting proteins (PGIPs) are cell wall glycoproteins that can recognize and inhibit PGs, thereby reducing their hydrolytic activity and helping control fungal progression [\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. PGIPs interact with PGs via the Leu-rich repeat (LRR) structure. This characteristic of PGIPs is evolutionarily linked to many plant resistance genes (R genes) [\\u003cspan citationid=\\\"CR64\\\" class=\\\"CitationRef\\\"\\u003e64\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR65\\\" class=\\\"CitationRef\\\"\\u003e65\\u003c/span\\u003e]. The PG\\u0026ndash;PGIP interaction also navigates the production of oligogalacturonides that elicit diverse defense responses (DR genes), including the expression of PR1 and salicylic acid-regulated genes [\\u003cspan citationid=\\\"CR62\\\" class=\\\"CitationRef\\\"\\u003e62\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR63\\\" class=\\\"CitationRef\\\"\\u003e63\\u003c/span\\u003e]. The upregulation of a PGI gene has been previously reported in the FW-resistant desi landrace of chickpea in response to Foc2 [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003ePectinesterase 2-like\\u003c/em\\u003e (\\u003cem\\u003eCaPE2\\u003c/em\\u003e: LOC101508209) and probable \\u003cem\\u003epectinesterase/pectinesterase inhibitor 7\\u003c/em\\u003e (\\u003cem\\u003eCaPME7\\u003c/em\\u003e: LOC101489717) were upregulated in both cultivars while the induction was higher in the resistant cultivar. It has been reported that a \\u003cem\\u003ePectinesterase-like\\u003c/em\\u003e gene is involved in the synthesis and modification of cellulose, lignin, and other components found in different layers of the cell wall [\\u003cspan citationid=\\\"CR66\\\" class=\\\"CitationRef\\\"\\u003e66\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR67\\\" class=\\\"CitationRef\\\"\\u003e67\\u003c/span\\u003e]. A pectinesterase-like gene was significantly upregulated in \\u003cem\\u003eMusa acuminata\\u003c/em\\u003e under \\u003cem\\u003ePseudocercospora musae\\u003c/em\\u003e disease [\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e]. It is related to epicuticular wax, pectin biosynthesis, cell wall organization, and cell wall biogenesis [\\u003cspan citationid=\\\"CR68\\\" class=\\\"CitationRef\\\"\\u003e68\\u003c/span\\u003e]. \\u003cem\\u003ePectinesterase inhibitor\\u003c/em\\u003e genes play a role in reorganizing the cell wall and in the plant's defense against pathogen attacks [\\u003cspan citationid=\\\"CR69\\\" class=\\\"CitationRef\\\"\\u003e69\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR70\\\" class=\\\"CitationRef\\\"\\u003e70\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSeveral \\u003cem\\u003eexpansin-like\\u003c/em\\u003e genes (\\u003cem\\u003eCaEXLB1\\u003c/em\\u003e: LOC101489892 and LOC101507544; \\u003cem\\u003eCaEXLA2\\u003c/em\\u003e: LOC101514490) were exclusively expressed in Ana or were more highly upregulated in Ana than in Hashem (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). Expansins (EXPs) are involved in plant development and responses to diverse stresses [\\u003cspan citationid=\\\"CR71\\\" class=\\\"CitationRef\\\"\\u003e71\\u003c/span\\u003e]. They are extracellular proteins that loosen plant cell walls in novel ways [\\u003cspan citationid=\\\"CR72\\\" class=\\\"CitationRef\\\"\\u003e72\\u003c/span\\u003e]. A role in the disease response was reported for \\u003cem\\u003eEXLB1\\u003c/em\\u003e, and the expression pattern of most \\u003cem\\u003eEXP\\u003c/em\\u003e genes significantly changed during diverse infection times [\\u003cspan citationid=\\\"CR73\\\" class=\\\"CitationRef\\\"\\u003e73\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThree genes encoding cellulose synthase (\\u003cem\\u003eCaCSLD\\u003c/em\\u003e, such as LOC101509896, LOC101488214, and LOC101499287) were exclusively expressed/induced in Ana (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). \\u003cem\\u003eCSLD\\u003c/em\\u003e (cellulose synthase) contributes to glucan deposition and maintaining cell wall integrity during pathogen invasion [\\u003cspan citationid=\\\"CR74\\\" class=\\\"CitationRef\\\"\\u003e74\\u003c/span\\u003e]. It has been reported that the overexpression of type 3 \\u003cem\\u003eCSLD\\u003c/em\\u003e prevents damage to the cell wall in resistant genotypes [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eA gene encoding the cytochrome P450 \\u003cem\\u003eCYP73A100-like\\u003c/em\\u003e (LOC101503511) was upregulated (logFC\\u0026thinsp;=\\u0026thinsp;3.89) only in the Ana cultivar under Fusarium wilt (race 6). It has been reported that \\u003cem\\u003eCYP73A100\\u003c/em\\u003e is upregulated during \\u003cem\\u003eFusarium oxysporum\\u003c/em\\u003e infection and contributes to lignin synthesis and accumulation [\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e]. The expression of some CYP genes is controlled in response to environmental stresses, and they play a significant role in the crosstalk between biotic and abiotic stress responses [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. CYPs hold significant potential as candidates for engineering crop species that are resilient to both abiotic and biotic stresses [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eTransport-related DEGs\\u003c/h2\\u003e \\u003cp\\u003eThe transport of essential elements to primary locations and during critical hours after infection affects the resistance network, where various groups of transporters play fundamental roles [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Several transport-related genes were upregulated in Ana, including \\u003cem\\u003ecalcium-transporting ATPase\\u003c/em\\u003e (\\u003cem\\u003eCaCa\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2+\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003e-ATPase\\u003c/em\\u003e: LOC101512366), cationic amino acid transporter 5 (\\u003cem\\u003eCaCAT5\\u003c/em\\u003e: LOC101509123), and sulfate transporter 3.5 (\\u003cem\\u003eCaSULTR\\u003c/em\\u003e\\u003csub\\u003e\\u003cem\\u003e3.5\\u003c/em\\u003e\\u003c/sub\\u003e: LOC101512274) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). Interestingly, the \\u003cem\\u003eCa\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2+\\u003c/em\\u003e\\u003c/sup\\u003e\\u003cem\\u003e-ATPase\\u003c/em\\u003e gene was also upregulated in previous studies on Foc races 1, 2, and 4 in resistant chickpea cultivars [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Some amino acid transporters (AATs), such as \\u003cem\\u003eAtCAT1\\u003c/em\\u003e (\\u003cem\\u003eArabidopsis thaliana cationic amino acid transporter 1\\u003c/em\\u003e), positively affect the plant immune system. It has been reported that the overexpression of \\u003cem\\u003eAtCAT1\\u003c/em\\u003e results in the continuous expression of PR1 and SA-related genes, along with an increase in SA rates. Given that \\u003cem\\u003eAtCAT1\\u003c/em\\u003e expression rapidly responds to infection, AtCAT1 plays a role in plant systemic resistance [\\u003cspan citationid=\\\"CR76\\\" class=\\\"CitationRef\\\"\\u003e76\\u003c/span\\u003e]. Additionally, sulfur (SULTR) is considered a crucial macronutrient for plant growth, development, and response to several abiotic and biotic stresses [\\u003cspan citationid=\\\"CR77\\\" class=\\\"CitationRef\\\"\\u003e77\\u003c/span\\u003e]. In addition, GO analysis of molecular function showed that the term \\u0026lsquo;nitrate transmembrane transporter activity\\u0026rsquo; was more enriched in Ana compared to the susceptible cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). It has been reported that the tolerance of cucumbers to Fusarium wilt is enhanced by nitrate, which controls the production and distribution of fungal toxins [\\u003cspan citationid=\\\"CR78\\\" class=\\\"CitationRef\\\"\\u003e78\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eSeveral transport-related genes were downregulated in Ana including nitrate reductase [NADH]-like (\\u003cem\\u003eCaNR/NADH\\u003c/em\\u003e: LOC101498580), bidirectional sugar transporter \\u003cem\\u003eSWEETs\\u003c/em\\u003e (\\u003cem\\u003eCaSWEET13-like\\u003c/em\\u003e: LOC101491054, \\u003cem\\u003eCaSWEET17\\u003c/em\\u003e: LOC101509872 and \\u003cem\\u003eCaSWEET1\\u003c/em\\u003e: LOC101498274) and metal transporter Nramp5-like (\\u003cem\\u003eCaNRAMP5\\u003c/em\\u003e: LOC101489317) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). Nitrate reductase (NIA2) is recognized for its role in regulating the biosynthesis and transport of nitric oxide (NO). It has been reported that the downregulation of \\u003cem\\u003eNR/NADH\\u003c/em\\u003e in resistant plants is a probable strategy of the resistant host to counteract drought stress caused by phenolic deposition due to Foc1 invasion [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Furthermore, the regulation of sugar transporter and \\u003cem\\u003eSWEET\\u003c/em\\u003e genes may play a role in plant defense against pathogen infection by adjusting the availability of sugar in the apoplasm [\\u003cspan citationid=\\\"CR79\\\" class=\\\"CitationRef\\\"\\u003e79\\u003c/span\\u003e]. Similar results were also reported during Foc race 2 infection in resistant and susceptible chickpea genotypes [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Additionally, the natural resistance-associated macrophage protein (NRAMP) gene family facilitates the transport of metal ions (NRAMP5 is a good example) in plants [\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e]. It has been reported that the downregulation of NRAMP5 significantly decreases the uptake and transport of manganese (Mn), which in turn activates enzymatic antioxidants. This enhances the capacity for ROS scavenging and boosts photosynthesis activity, thereby alleviating Mn toxicity in peach plants. [\\u003cspan citationid=\\\"CR80\\\" class=\\\"CitationRef\\\"\\u003e80\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eMoreover, the protein DETOXIFICATION 27-like (\\u003cem\\u003eCaDTX27\\u003c/em\\u003e: LOC101503133), located in the plasma membrane, was upregulated only in Ana. It belongs to the multiantimicrobial extrusion (MATE) family. MATE genes have been shown to be associated with disease resistance in Arabidopsis [\\u003cspan citationid=\\\"CR81\\\" class=\\\"CitationRef\\\"\\u003e81\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR82\\\" class=\\\"CitationRef\\\"\\u003e82\\u003c/span\\u003e]. Likewise, it has been suggested that the protein DETOXIFICATION 48-like, encoding a MATE family protein, is related to defense activity against Foc (race 5) [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e].\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDEGs involved in metabolism\\u003c/h2\\u003e \\u003cp\\u003eUpon infection, the plant and pathogen compete to utilize the host's sugar metabolism, which in turn triggers either resistant or susceptible responses. Sugar-metabolizing enzymes are differentially regulated during plant\\u0026ndash;pathogen interactions. In the present study, two genes encoding putative UDP-glucose glucosyltransferase (\\u003cem\\u003eCaUFGT3\\u003c/em\\u003e: UGT71S3 and \\u003cem\\u003eCaUGT\\u003c/em\\u003e: UGT84F2) were upregulated in the resistant genotype (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). This finding is consistent with previous reports showing that UDP-glucosyltransferases (UGTs) are involved in FW resistance in wheat and barley through glycosylating the deoxynivalenol produced by the Fusarium spp. fungus [\\u003cspan citationid=\\\"CR83\\\" class=\\\"CitationRef\\\"\\u003e83\\u003c/span\\u003e]. Furthermore, a cell wall isozyme-like beta-fructofuranosidase (\\u003cem\\u003eCaBF-CWI\\u003c/em\\u003e: LOC101513089) was upregulated in Ana (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). It belongs to a class of sucrose-hydrolyzing enzymes known as invertases whose role in plant disease resistance has already been reported [\\u003cspan citationid=\\\"CR84\\\" class=\\\"CitationRef\\\"\\u003e84\\u003c/span\\u003e]. It is believed that \\u003cem\\u003eCWINV1\\u003c/em\\u003e (cell wall invertase 1) is the enzyme that plays a crucial role in the reconstruction of damaged cell walls [\\u003cspan citationid=\\\"CR85\\\" class=\\\"CitationRef\\\"\\u003e85\\u003c/span\\u003e]. Based on the results of the present study, alpha-amylase/subtilisin inhibitor-like (\\u003cem\\u003eASI\\u003c/em\\u003e; LOC101508812) was also induced in Ana (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). \\u003cem\\u003eASI\\u003c/em\\u003e proteins play a significant role in plant defense mechanisms against pathogens, including fungi. They inhibit the activity of enzymes such as alpha-amylase and subtilisin, which are substantial for the growth and development of many pathogens [\\u003cspan citationid=\\\"CR86\\\" class=\\\"CitationRef\\\"\\u003e86\\u003c/span\\u003e]. In particular, these inhibitors can prevent the degradation of plant cell walls by fungal enzymes, thereby limiting the ability of pathogens to invade and cause disease [\\u003cspan citationid=\\\"CR87\\\" class=\\\"CitationRef\\\"\\u003e87\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eGlutathione S-transferase\\u003c/em\\u003e (\\u003cem\\u003eCaGST\\u003c/em\\u003e: LOC101494465, LOC101506971, and LOC113787225) was upregulated in the resistant cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). \\u003cem\\u003eGSTs\\u003c/em\\u003e are involved in the detoxification of a vast variety of xenobiotic compounds [\\u003cspan citationid=\\\"CR88\\\" class=\\\"CitationRef\\\"\\u003e88\\u003c/span\\u003e]. It has been reported that the increase in GSTs after Foc1 attack impacts the maintenance of redox balance [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR89\\\" class=\\\"CitationRef\\\"\\u003e89\\u003c/span\\u003e]. Also, \\u003cem\\u003eGSTs\\u003c/em\\u003e combat toxin challenges that directly affect the cell cycle and cell division [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. KEGG pathway analysis showed that the percentage of genes involved in the glutathione metabolism pathway in the resistant cultivar (Ana) was dramatically higher than that in the susceptible cultivar (Hashem) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cem\\u003eTrihydroxycinnamoyl spermidines\\u003c/em\\u003e (\\u003cem\\u003eCaSHT-like\\u003c/em\\u003e; LOC101513347) were also upregulated in both cultivars, while the increase was more in the resistant cultivar (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). THCSpds are specialized plant metabolites known for their significant pharmacological properties, including antifungal, antibacterial, and antiviral activities [\\u003cspan citationid=\\\"CR90\\\" class=\\\"CitationRef\\\"\\u003e90\\u003c/span\\u003e]. Moreover, the carbonic anhydrase 1 (\\u003cem\\u003eCaCA1\\u003c/em\\u003e: LOC101498889) gene was found to be involved in the nitrogen metabolism pathway [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]; it has also been reported via transcriptome analysis that \\u003cem\\u003eCA1\\u003c/em\\u003e was identified in maize in response to Fusarium ear rot [\\u003cspan citationid=\\\"CR91\\\" class=\\\"CitationRef\\\"\\u003e91\\u003c/span\\u003e]. CAs are widespread enzymes that play crucial roles in essential processes such as photosynthesis, respiration, ion transport, and pH homeostasis [\\u003cspan citationid=\\\"CR92\\\" class=\\\"CitationRef\\\"\\u003e92\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eFurthermore, CYP73A100, which is involved in the phenylpropanoid and flavonoid biosynthesis pathways, was detected (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). It has been reported that some genes, such as \\u003cem\\u003eCaCYP73A100\\u003c/em\\u003e, are upregulated during treatment with exogenous melatonin and \\u003cem\\u003eF. oxysporum\\u003c/em\\u003e. These genes are involved in the synthesis of p-coumaric acid, flavonol 3-O-ethyltransferase, and 4-coumarate-CoA ligase, which contribute to the accumulation of lignin [\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e]. Melatonin is regarded as a polyfunctional master regulator in both higher plants and animals. Studies have shown that exogenous melatonin treatment can efficiently manage cucumber green mottle mosaic virus (CGMMV) infection and enhance resistance to \\u003cem\\u003eF. oxysporum\\u003c/em\\u003e in plants [\\u003cspan citationid=\\\"CR75\\\" class=\\\"CitationRef\\\"\\u003e75\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR93\\\" class=\\\"CitationRef\\\"\\u003e93\\u003c/span\\u003e]. Upregulation of the \\u003cem\\u003eCYP73A100\\u003c/em\\u003e gene in other plants under biotic stress has also been shown; for instance, it was expressed in soybeans during infection with soybean cyst nematodes [\\u003cspan citationid=\\\"CR94\\\" class=\\\"CitationRef\\\"\\u003e94\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eComparative analysis of the transcriptomic response of resistant and susceptible chickpea cultivars (Ana and Hashem, respectively) to race 6 of \\u003cem\\u003eF. oxysporum\\u003c/em\\u003e f. sp. \\u003cem\\u003eciceris\\u003c/em\\u003e infection has provided some insights into the molecular mechanisms of resistance to FW in \\u003cem\\u003eCicer arietinum\\u003c/em\\u003e. Recognition of fungal pathogens by plants is the first critical step, which can lead to prompt activation of downstream defense signaling cascades and finally result in resistance. Remarkably, two receptor genes (\\u003cem\\u003ei.e., CaNLR-RPM1\\u003c/em\\u003e and \\u003cem\\u003eCaLYK5-RLK\\u003c/em\\u003e) were exclusively expressed in Ana and upregulated under FW stress conditions. Some other RLKs and RLPs (including \\u003cem\\u003eCaPR5-RLK\\u003c/em\\u003e, \\u003cem\\u003eCaLRR-RLK\\u003c/em\\u003e, and \\u003cem\\u003eCaRLP-EIX2\\u003c/em\\u003e) were also significantly induced by FW in the root tissues of Ana. Moreover, several genes involved in signaling (such as \\u003cem\\u003eCaPP7, CaHSC70s, CaEPS1, CaSTY13\\u003c/em\\u003e and \\u003cem\\u003eCaSTY-OXI1\\u003c/em\\u003e) and transcription regulation (\\u003cem\\u003eCaMYBs\\u003c/em\\u003e, \\u003cem\\u003eCaGLK\\u003c/em\\u003e, \\u003cem\\u003eCaERFs\\u003c/em\\u003e, \\u003cem\\u003eCaZAT11-like\\u003c/em\\u003e, and \\u003cem\\u003eCaNAC6\\u003c/em\\u003e) were found to be overrepresented by FW stress in the resistant genotype. A rich set of genes related to defense responses (\\u003cem\\u003ee.g., CaPR-1\\u003c/em\\u003e and \\u003cem\\u003eCaPR-4\\u003c/em\\u003e) and cell wall integrity (\\u003cem\\u003ee.g., CaPGI2-like\\u003c/em\\u003e, \\u003cem\\u003eCaPE2\\u003c/em\\u003e, \\u003cem\\u003eCaPME7\\u003c/em\\u003e, \\u003cem\\u003eCaEXLs\\u003c/em\\u003e, \\u003cem\\u003eCaCSLD\\u003c/em\\u003e, \\u003cem\\u003eCaCYP73A100-like\\u003c/em\\u003e) were further identified in Ana, whereas they were not expressed in Hashem. Conclusively, the resistant genotype employs a subtle gene network, which helps in the early detection of pathogens and triggers prompt signaling pathways leading to the activation of an efficient defense response against fungal pathogens, thereby enhancing its disease resistance (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e; Supplementary Table S2). The achieved results could facilitate the use of genetic engineering or molecular breeding approaches to develop chickpea varieties resistant to Fusarium wilt.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section3\\\"\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \"},{\"header\":\"Methods\",\"content\":\"\\u003ch2\\u003ePlant material\\u003c/h2\\u003e\\u003cp\\u003eThe present study employed two chickpea cultivars, designated as Ana and Hashem, which exhibited contrasting resistance and susceptibility to Race 6. Both cultivars are of the Kabuli type, originating from the Dryland Agricultural Research Institute of Iran (DARI) (Supplementary Figures \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e and S2).\\u003c/p\\u003e\\u003cp\\u003eThe seeds of the two cultivars were sterilized for 10 minutes in 0.5% sodium hypochlorite (NaClO), rinsed with distilled water, and placed on dampened filter papers. On the third day, the uniformly germinated seeds were transferred to pots (6×6×8 cm) filled with pasteurized perlite in trays (41×56×12 cm). The plants were grown under controlled conditions at 25 ± 2°C with a 16/8 (day/night) photoperiod under fluorescent light and a relative humidity of 75%.\\u003c/p\\u003e\\u003cp\\u003e \\u003cb\\u003eInoculation of\\u003c/b\\u003e \\u003cb\\u003eFusarium oxysporum\\u003c/b\\u003e \\u003cb\\u003ef. sp. ciceris race 6 and evaluation of the pathogenicity response\\u003c/b\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe race 6 isolate of Foc [\\u003cspan citationid=\\\"CR95\\\" class=\\\"CitationRef\\\"\\u003e95\\u003c/span\\u003e] was used in this study. The fungus was cultured in potato dextrose broth (PDB, 200 g potato: 20 g dextrose: 1 liter water) at a temperature of 28 to 30°C for 3 to 4 days on a shaker. The medium was then filtered through four layers of clean cloth and centrifuged at 7500 rpm for 14 minutes. The resulting conidia were used to prepare a spore suspension with a concentration of 10\\u003csup\\u003e6\\u003c/sup\\u003e conidia per ml. Twenty plants (replicating) of each cultivar along with the same number of susceptible control varieties, Kaka, were inoculated with the pathogen according to the methods of Pouralibaba et al. (2015) [\\u003cspan citationid=\\\"CR96\\\" class=\\\"CitationRef\\\"\\u003e96\\u003c/span\\u003e]. Approximately 1–3 cm of the root tips of the plants at the 4–5-leaf stage (approximately 12–14 days after planting) were cut with sterilized scissors. The root tips were subsequently immersed in the spore suspension for 10 min before being planted in pots filled with sterilized Perlite. The control plants were subjected to the same procedure but were given sterile water instead. Following inoculation, the pots were irrigated with a complete NPK 20–20–20 + TE solution (20 g/10-liter water). The reaction to the pathogenic fungus was scored based on the percentage of mortality [\\u003cspan citationid=\\\"CR97\\\" class=\\\"CitationRef\\\"\\u003e97\\u003c/span\\u003e]. The first data recording was done immediately after observing the first symptoms of yellow/wilt on the susceptible control plant, and the plants were evaluated at one-week intervals until the death of all control plants (approximately one month after the first disease evaluation). The last data recorded were considered the final plant reaction to the disease.\\u003c/p\\u003e\\u003cp\\u003eFor genotyping, root samples were collected at 48 hours postinoculation (hpi) from two biological replicates (each replicate included at least three individual plants) of inoculated and noninoculated plants. Previous experiments by several researchers revealed significant transcriptomic and proteomic changes at 48 hpi in chickpea-Foc1 interactions [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR98\\\" class=\\\"CitationRef\\\"\\u003e98\\u003c/span\\u003e]. Therefore, a 48-hour period was selected as the ideal time point for sample collection and transcriptome analysis. The root samples from each cultivar were promptly frozen in liquid nitrogen and subsequently stored at -80°C.\\u003c/p\\u003e\\u003ch2\\u003eRNA extraction and mRNA sequencing\\u003c/h2\\u003e\\u003cp\\u003eFor each biological replicate, equal amounts of root samples (collected at 48 hpi) from 8 single plants were pooled and ground. Total RNA was extracted from both inoculated and non-inoculated Ana and Hashem cultivars using TRIzol (Bio Basic, Canada) based on the manufacturer’s guidelines. The quality, quantity, and RNA integrity were evaluated by a NanoDrop ND-1000® spectrophotometer, agarose gel electrophoresis, and an Agilent 2100 Bioanalyzer system (Agilent Technologies Co. Ltd., Beijing, China). To avoid any genomic DNA contamination, RNA samples were treated with RNase-free DNase I (Thermo Scientific™) and subjected to PCR. Additionally, paired-end reads of 150 bp were generated with the Illumina HiSeq™ 2500 sequencing platform at Novogene Bioinformatics Institute (Beijing, China) for total root samples.\\u003c/p\\u003e\\u003ch2\\u003eRNA-seq data analysis\\u003c/h2\\u003e\\u003cp\\u003eThe quality of the raw sequencing reads in FASTQ format was distinguished by FASTQC [\\u003cspan citationid=\\\"CR99\\\" class=\\\"CitationRef\\\"\\u003e99\\u003c/span\\u003e] software, and quality reads were confirmed based on phred score ≥ 30 (Q30). The high-quality paired-end reads were then mapped against the chickpea reference genome (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.ncbi.nlm.nih.gov/assembly/GCF_000331145.1\\u003c/span\\u003e\\u003cspan address=\\\"https://www.ncbi.nlm.nih.gov/assembly/GCF_000331145.1\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) utilizing HISAT2 [\\u003cspan citationid=\\\"CR100\\\" class=\\\"CitationRef\\\"\\u003e100\\u003c/span\\u003e]. A reference annotation-based transcript (RABT) assembly and the genome GFF were created by Cufflinks [\\u003cspan citationid=\\\"CR101\\\" class=\\\"CitationRef\\\"\\u003e101\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR102\\\" class=\\\"CitationRef\\\"\\u003e102\\u003c/span\\u003e] using the aligned reads from each sample. The single assemblies were merged into a complete assembly using Cuffmerge with default parameters. Additionally, Cuffmerge was used to identify novel transcripts [\\u003cspan citationid=\\\"CR101\\\" class=\\\"CitationRef\\\"\\u003e101\\u003c/span\\u003e]. Differentially expressed genes (DEGs) were identified using Cuffdiff from the Cufflinks package, with thresholds set at − 1 ≤ log2-fold change ≥ 1 and a Q value cutoff ≤ 0.01. Also, Blastx was utilized for functional annotation of significant DEGs against the TAIR protein database using the ENSEMBL Genome Browser (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://ensembl.gramene.org/Arabidopsis_thaliana/Tools/Blast\\u003c/span\\u003e\\u003cspan address=\\\"https://ensembl.gramene.org/Arabidopsis_thaliana/Tools/Blast\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e).\\u003c/p\\u003e\\u003ch2\\u003eFunctional annotation and pathway analysis of significant DEGs\\u003c/h2\\u003e\\u003cp\\u003eFor each cultivar, GO terms were assigned to significant DEGs using AgriGO website (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://systemsbiology.cau.edu.cn/agriGOv2/\\u003c/span\\u003e\\u003cspan address=\\\"http://systemsbiology.cau.edu.cn/agriGOv2/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) with an FDR cutoff ≤ 0.05. The contributions of significant DEGs to KEGG pathways were identified via the online KEGG automatic annotation server (KAAS) (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.genome.jp/kegg/kaas/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.genome.jp/kegg/kaas/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e). Moreover, for pathway analysis of significant DEGs, MapMan (version 3.5.1) with a Q value cutoff of ≤ 0.01 and − 1 ≤ Log2-fold change ≥ 1 was used [\\u003cspan citationid=\\\"CR103\\\" class=\\\"CitationRef\\\"\\u003e103\\u003c/span\\u003e]. Mapping significant DEGs to Arabidopsis pathway genes led to the identification of genes involved in specific pathways [\\u003cspan citationid=\\\"CR103\\\" class=\\\"CitationRef\\\"\\u003e103\\u003c/span\\u003e].\\u003c/p\\u003e\\u003ch2\\u003eRealtime PCR analysis\\u003c/h2\\u003e\\u003cp\\u003eReal-time PCR was applied to confirm the RNA-seq results. Twelve genes were selected from the panel of Fusarium wilt-responsive genes identified through the RNA-seq results. Gene-specific primers were designed using Oligo 7 (version 7.60; Molecular Biology Insights, Inc.; USA). The primers used for the selected genes are provided in Supplementary Table \\u003cspan refid=\\\"MOESM1\\\" class=\\\"InternalRef\\\"\\u003eS1\\u003c/span\\u003e. cDNA synthesis was done using a SinaClon cDNA synthesis kit (Cat. No: RT5201). Quantitative real-time PCR (qRT‒PCR) was performed on three biological replicates of both noninoculated and inoculated root samples using a LightCycler® 96 Real-Time PCR System (Roche Life Science, Germany) and HS‒qPCR Mix, 2x (SinaClon, Iran). GAPDH served as an internal control gene to normalize the gene expression values. The relative expression of the candidate genes was analyzed using the 2 − ΔΔCt method [\\u003cspan citationid=\\\"CR104\\\" class=\\\"CitationRef\\\"\\u003e104\\u003c/span\\u003e].\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgment\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors thank Dr. Fateme Loni, Dr. Nazanin Amirbakhtiar and Mr. Amir-Hossein Sadri for their valuable contributions/expert assistance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll the sequencing reads generated from Illumina HiSeq 2500 RNA-Seq are available from NCBI SRA under BioProject ID: PRJNA1050654 (https://submit.ncbi.nlm.nih.gov/subs/bioproject/SUB14017589/overview). All other data sets supporting this study are included in the article and its supplementary data.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor Contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eZ-S.S. designed the lab experiments and supervised the molecular part of the research. H.H-K. and H-R.P. supervised the plant culture, inoculation and phenotyping part of the research. A.F. performed the experiments and drafted the manuscript. A.F., S.D. and R.M-M. analyzed the data. Z-S.S. and R.M-M. revised the manuscript. All authors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding Declaration\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors thank Agricultural Biotechnology Research Institute of Iran (ABRII) for the financial supports (grant#\\u0026nbsp;013-15-1505-114-97027-971295).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe declare that the authors have no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eRani A, Devi P, Jha UC, Sharma KD, Siddique KHM, Nayyar H. Developing Climate-Resilient Chickpea Involving Physiological and Molecular Approaches With a Focus on Temperature and Drought Stresses. Front Plant Sci [Internet]. 2020;10(February):1\\u0026ndash;29. https://doi.org/10.3389/fpls.2019.01759\\u003c/li\\u003e\\n\\u003cli\\u003eWood JA, Grusak MA. Nutritional value of chickpea. Chickpea Breed Manag [Internet]. 2007;101\\u0026ndash;42. https://doi.org/10.1079/9781845932138.005\\u003c/li\\u003e\\n\\u003cli\\u003eShiade G, Roghie S, Fathi A, Kardoni F, Pandey R, Pessarakli. and M. Nitrogen contribution in plants: recent agronomic approaches to improve nitrogen use efficiency. J Plant Nutr [Internet]. 2024 [cited 2021 Oct 16];47(2):314\\u0026ndash;31. https://doi.org/10.1080/01904167.2023.2278656\\u003c/li\\u003e\\n\\u003cli\\u003eFAO. FAOSTAT [Internet]. FAOSTAT. 2021. https://www.fao.org/faostat \\u003c/li\\u003e\\n\\u003cli\\u003eHamida D, Gowda VT, Kundu A, Kaur R, Bag. and TK. Effect of culture filtrate containing fusaric acid of Fusarium oxysporum f. sp. ciceris on defence enzymes in chickpea. Indian Phytopathol [Internet]. 2024;1\\u0026ndash;9. https://doi.org/10.1007/s42360-023-00702-0\\u003c/li\\u003e\\n\\u003cli\\u003eAlsamman AM, H. Mousa K, Istanbuli T, Abd El-Maksoud MM, Tawkaz S, Hamwieh A. Unveiling the genetic basis of Fusarium wilt resistance in chickpea using GWAS analysis and characterization of candidate genes. Front Genet [Internet]. 2024;14(January):1\\u0026ndash;11. https://doi.org/10.3389/fgene.2023.1292009\\u003c/li\\u003e\\n\\u003cli\\u003eRecorbet G, Steinberg C, Olivain C, Edel V, Trouvelot S, Dumas-Gaudot E, et al. Wanted: Pathogenesis-related marker molecules for Fusarium oxysporum. New Phytol [Internet]. 2003;159(1):73\\u0026ndash;92. https://doi.org/10.1046/j.1469-8137.2003.00795.x\\u003c/li\\u003e\\n\\u003cli\\u003eJoshi NS, Rao KS, Subramanian RB. Anatomical and biochemical aspects of interaction between roots of chickpea and Fusarium oxysporum f. sp. ciceris race 2. Arch Phytopathol Plant Prot [Internet]. 2012;45(15):1773\\u0026ndash;89. https://doi.org/10.1080/03235408.2012.674709\\u003c/li\\u003e\\n\\u003cli\\u003eUpasani ML, Gurjar GS, Kadoo NY, Gupta VS. Dynamics of Colonization and Expression of Pathogenicity Related Genes in Fusarium oxysporum f.sp. ciceri during Chickpea Vascular Wilt Disease Progression. PLoS One [Internet]. 2016;11(5):1\\u0026ndash;21. https://doi.org/10.1371/journal.pone.0156490\\u003c/li\\u003e\\n\\u003cli\\u003eJendoubi W, Bouhadida M, Boukteb A, B\\u0026eacute;ji M, Kharrat M. Fusarium wilt affecting chickpea crop. Agric [Internet]. 2017;7(3):1\\u0026ndash;16. https://doi.org/10.3390/agriculture7030023\\u003c/li\\u003e\\n\\u003cli\\u003eAchari SR, Mann RC, Sharma M, Edwards J. Diagnosis of Fusarium oxysporum f. sp. ciceris causing Fusarium wilt of chickpea using loop-mediated isothermal amplification (LAMP) and conventional end-point PCR. 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Biotechnol Lett [Internet]. 2017;39(1):141\\u0026ndash;8. https://doi.org/10.1007/s10529-016-2227-8\\u003c/li\\u003e\\n\\u003cli\\u003eMarrs KA. The functions and regulation of glutathione s-transferases in plants. Annu Rev Plant Physiol Plant Mol Biol [Internet]. 1996;47(1):127\\u0026ndash;58. https://doi.org/10.1146/annurev.arplant.47.1.127\\u003c/li\\u003e\\n\\u003cli\\u003eGupta S, Bhar A, Chatterjee M, Das S. Fusarium oxysporum f.sp. ciceri Race 1 Induced Redox State Alterations Are Coupled to Downstream Defense Signaling in Root Tissues of Chickpea (Cicer arietinum L.). PLoS One [Internet]. 2013;8(9). https://doi.org/10.1371/journal.pone.0073163\\u003c/li\\u003e\\n\\u003cli\\u003ePerrin J, Kulagina N, Unlubayir M, Munsch T, Carqueijeiro I, Dug\\u0026eacute; De Bernonville T, et al. Exploiting Spermidine N-Hydroxycinnamoyltransferase Diversity and Substrate Promiscuity to Produce Various Trihydroxycinnamoyl Spermidines and Analogues in Engineered Yeast. ACS Synth Biol [Internet]. 2021;10(2):286\\u0026ndash;96. https://doi.org/10.1021/acssynbio.0c00391\\u003c/li\\u003e\\n\\u003cli\\u003eGuangsheng Y, Zhiming Z, Kui X, Maojun Z, Yaou S, Guangtang P. Large-scale identification of differentially expressed genes in maize inbreds susceptible and resistant to Fusarium ear rot. Plant Omics [Internet]. 2012;5(5):471\\u0026ndash;5. https://search.informit.org/doi/10.3316/informit.777226738861387%0A\\u003c/li\\u003e\\n\\u003cli\\u003eDreher K, Callis J. Ubiquitin, hormones and biotic stress in plants. Ann Bot [Internet]. 2007;99(5):787\\u0026ndash;822. https://doi.org/10.1093/aob/mcl255\\u003c/li\\u003e\\n\\u003cli\\u003eYang LL, Li QL, Han XY, Jiang XL, Wang H, Shi YJ, et al. A cysteine-rich secretory protein involves in phytohormone melatonin mediated plant resistance to CGMMV. BMC Plant Biol [Internet]. 2023;23(1):1\\u0026ndash;15. https://doi.org/10.1186/s12870-023-04226-7\\u003c/li\\u003e\\n\\u003cli\\u003eKang W, Zhu X, Wang Y, Chen L, Duan Y. Transcriptomic and metabolomic analyses reveal that bacteria promote plant defense during infection of soybean cyst nematode in soybean. BMC Plant Biol [Internet]. 2018;18(1):1\\u0026ndash;14. https://doi.org/10.1186/s12870-018-1302-9\\u003c/li\\u003e\\n\\u003cli\\u003ePouralibaba HR, Tabrizivand Taheri M, Mahmodi F, , Ravanlou AA, , Bahrami Kamangar S, , Kowkab S, et al. First report of existence races 2 and 4 of Fusarium oxysporum f. sp. ciceris, causing agent of yellow and wilt disease of chickpea in Iran. Iran Dryl Agron Journal [Internet]. 2024;12(2). 10.22092/idaj.2023.363198.408\\u003c/li\\u003e\\n\\u003cli\\u003ePouralibaba HR, Rubiales D, Fondevilla S. Identification of resistance to Fusarium oxysporum f.sp. lentis in Spanish lentil germplasm. Eur J Plant Pathol [Internet]. 2015;143(2):399\\u0026ndash;405. https://doi.org/10.1007/s10658-015-0692-x\\u003c/li\\u003e\\n\\u003cli\\u003eIqbal M, Iftikhar K, Ilyas M. Evaluation of chickpea germplasm for resistance against wilt disease (Fusarium oxysporum). J Agric Res. 1993;31(4):449\\u0026ndash;53. \\u003c/li\\u003e\\n\\u003cli\\u003eGupta S, Chakraborti D, Sengupta A, Basu D, Das S. Primary metabolism of chickpea is the initial target of wound inducing early sensed Fusarium oxysporum f. sp. ciceri race I. PLoS One [Internet]. 2010;5(2). https://doi.org/10.1371/journal.pone.0009030\\u003c/li\\u003e\\n\\u003cli\\u003ePlasterer TN. Sequence Data Analysis Guidebook [Internet]. Swindell. ESR, editor. Humana Press. Vol. 70. New York, USA; 1997. 321 p. https://link.springer.com/book/10.1385/0896033589?page=2\\u0026amp;oscar-books=true#back-to-top\\u003c/li\\u003e\\n\\u003cli\\u003ePertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc [Internet]. 2016;11(9):1650\\u0026ndash;67. http://dx.doi.org/10.1038/nprot.2016-095\\u003c/li\\u003e\\n\\u003cli\\u003eTrapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, Van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol [Internet]. 2010;28(5):511\\u0026ndash;5. https://doi.org/10.1038/nbt.1621\\u003c/li\\u003e\\n\\u003cli\\u003eTrapnell C, Hendrickson D, Sauvageau M, Goff L, Rinn, John. Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol [Internet]. 2013;31(1):46\\u0026ndash;53. http://dx.doi.org/10.1038/nbt.2450\\u003c/li\\u003e\\n\\u003cli\\u003eThimm O, Bl\\u0026auml;sing O, Gibon Y, Nagel A, Meyer S, Kr\\u0026uuml;ger P, et al. MAPMAN: A user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J. 2004;37(6):914\\u0026ndash;39. \\u003c/li\\u003e\\n\\u003cli\\u003eLivak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-\\u0026Delta;\\u0026Delta;CT method. Methods [Internet]. 2001;25(4):402\\u0026ndash;8. https://doi.org/10.1006/meth.2001.1262\\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\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-genomics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"gics\",\"sideBox\":\"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/gics\",\"title\":\"BMC Genomics\",\"twitterHandle\":\"#BMCGenomics\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Chickpea, Biotic stress, Fusarium wilt (Race 6), RNA sequencing\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5212429/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5212429/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eChickpea (\\u003cem\\u003eCicer arietinum\\u003c/em\\u003e L.) ranks as the third most crucial grain legume worldwide. Fusarium wilt (\\u003cem\\u003eFusarium oxysporum\\u003c/em\\u003e f. sp. \\u003cem\\u003eciceri\\u003c/em\\u003e (Foc)) is a devastating fungal disease that prevents the maximum potential for chickpea production.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eTo identify genes and pathways involved in resistance to race 6 of Foc, this study utilized transcriptome sequencing of two chickpea cultivars: resistant (Ana) and susceptible (Hashem) to Foc race 6. Illumina sequencing of the root samples yielded 133.5\\u0026nbsp;million raw reads, with about 90% of the clean reads mapped to the chickpea reference genome. The analysis revealed that 518 genes (317 upregulated and 201 downregulated) in the resistant genotype (Ana) and 1063 genes (587 upregulated and 476 downregulated) in the susceptible genotype (Hashem) were differentially expressed under Fusarium wilt (FW) disease stress caused by Foc race 6. The expression patterns of some differentially expressed genes (DEGs) were validated using quantitative real-time PCR. A total of 127 genes were exclusively upregulated under FW stress in the resistant cultivar, including several genes involved in sensing (e.g., \\u003cem\\u003eCaNLR-RPM1\\u003c/em\\u003e, \\u003cem\\u003eCaLYK5-RLK\\u003c/em\\u003e, \\u003cem\\u003eCaPR5-RLK\\u003c/em\\u003e, \\u003cem\\u003eCaLRR-RLK\\u003c/em\\u003e, and \\u003cem\\u003eCaRLP-EIX2\\u003c/em\\u003e), signaling (e.g., \\u003cem\\u003eCaPP7\\u003c/em\\u003e, \\u003cem\\u003eCaEPS1\\u003c/em\\u003e, \\u003cem\\u003eCaSTY13\\u003c/em\\u003e, and \\u003cem\\u003eCaPR-1\\u003c/em\\u003e), transcription regulation (e.g., \\u003cem\\u003eCaMYBs\\u003c/em\\u003e, \\u003cem\\u003eCaGLK\\u003c/em\\u003e, \\u003cem\\u003eCaERFs\\u003c/em\\u003e, \\u003cem\\u003eCaZAT11-like\\u003c/em\\u003e, and \\u003cem\\u003eCaNAC6\\u003c/em\\u003e) and cell wall integrity (e.g., \\u003cem\\u003eCaPGI2-like\\u003c/em\\u003e, \\u003cem\\u003eCaEXLs\\u003c/em\\u003e, \\u003cem\\u003eCaCSLD\\u003c/em\\u003e and \\u003cem\\u003eCaCYP73A100-like\\u003c/em\\u003e).\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThe achieved results could provide significant insights into the molecular mechanism underlying resistance to FW and could be valuable for breeding programs aimed at developing FW-resistant chickpea varieties.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Unraveling the transcriptional response mechanisms to yellow and wilt disease, caused by race 6 of Fusarium oxysporum f.sp. ciceris in two contrasting chickpea cultivars\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-12-04 15:01:58\",\"doi\":\"10.21203/rs.3.rs-5212429/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-10-15T11:42:22+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-10-08T22:33:35+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-10-08T22:32:50+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Genomics\",\"date\":\"2024-10-06T10:24:16+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-genomics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"gics\",\"sideBox\":\"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/gics\",\"title\":\"BMC Genomics\",\"twitterHandle\":\"#BMCGenomics\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"f7f995a3-4974-4016-a451-46f73c748908\",\"owner\":[],\"postedDate\":\"December 4th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-02-10T16:08:33+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-5212429\",\"link\":\"https://doi.org/10.1186/s12864-025-11308-3\",\"journal\":{\"identity\":\"bmc-genomics\",\"isVorOnly\":false,\"title\":\"BMC Genomics\"},\"publishedOn\":\"2025-02-04 15:57:49\",\"publishedOnDateReadable\":\"February 4th, 2025\"},\"versionCreatedAt\":\"2024-12-04 15:01:58\",\"video\":\"\",\"vorDoi\":\"10.1186/s12864-025-11308-3\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12864-025-11308-3\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5212429\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5212429\",\"identity\":\"rs-5212429\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}