The landscape of cotton DNA methylation and its epigenetic regulation in Verticillium wilt resistance

The landscape of cotton DNA methylation and its epigenetic regulation in Verticillium wilt resistance | 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 The landscape of cotton DNA methylation and its epigenetic regulation in Verticillium wilt resistance Zixu Zhang, Xingfen Wang, Zhicheng Wang, Xinyu Zhang, Weiyi Chen, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7531123/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Verticillium wilt (VW) is a devastating disease that causes severe losses in cotton yield and fiber quality. While DNA methylation is known to regulate various processes in plant development and stress responses, its specific role in conferring host resistance remains unclear. To elucidate the regulatory mechanism of DNA methylation in VW resistance, we compared the genome-wide DNA methylation profiles of a resistant cotton cultivar (NDM8) and a susceptible cultivar (TM-1) under both normal and V. dahliae -infected conditions using whole-genome bisulfite sequencing. Our results revealed that a lower overall level of DNA methylation was associated with enhanced VW resistance. We also found that the A-subgenome exhibited a higher methylation level than the D-subgenome, indicating an asymmetric methylation distribution between subgenomes. Furthermore, except for chromosomes A09, D07, D09, and D10, the chromosomal arms consistently showed significantly lower methylation levels than the centromeric regions. Upon V. dahliae infection, altered DNA methylation patterns predominantly led to reduced gene expression. Analyses of differentially methylated regions (DMRs) and genes (DMGs), combined with gene silencing assays, demonstrated that the RNA-directed DNA methylation (RdDM) pathway plays a central regulatory role in cotton resistance to VW. Key components of this pathway, including Pol IV, Pol V, AGO4, RDR2, and DCL3, were implicated in this process. Moreover, we confirmed that AGO4 interacts with four proteins, including ADH1, to collectively regulate VW resistance. In summary, our study unveils an epigenetic mechanism underlying disease resistance in cotton, providing new insights into the defense response against Verticillium wilt. Cotton DNA methylation Verticillium wilt RdDM pathway AGO protein Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Cotton, a globally significant economic crop, plays a vital role in both agricultural and industrial sectors. However, cotton production has long been severely threatened by Verticillium wilt (VW), a devastating soil-borne disease caused by the fungus Verticillium dahliae . This disease is among the most destructive to cotton cultivation, greatly hindering the sustainable development of the global cotton industry (Zhang et al., 2019b ; Zhang et al., 2022 ). Infection leads to substantial yield losses and reduced fiber quality, resulting in considerable economic damage to growers (Gong et al., 2018 ; Zhang et al., 2019a ). Given the broad host range, prolonged persistence in soil, and ability of V. dahliae to produce resilient dormant structures such as microsclerotia, controlling the pathogen is extremely challenging. Consequently, the use of resistant cotton cultivars has emerged as the most economical, environmentally safe, and effective strategy for managing Verticillium wilt (Xu et al., 2022 ; Zhang et al., 2023a ). Ongoing research in breeding and genetic resistance remains essential to alleviating the impact of this persistent and widespread disease. In recent years, significant progress has been made in understanding the genetic basis and molecular mechanisms of cotton resistance to Verticillium wilt at the genomic, transcriptomic, and proteomic levels. For example, the molecular mechanisms underlying this resistance have been further elucidated through GWAS, revealing the involvement of NLR proteins containing dual TIR domains and leading to the identification of key resistance genes such as GhRVD1 (Zhang et al., 2023b ). Additionally, studies have uncovered the critical role of laccase-mediated defense-induced lignification in enhancing cotton VW resistance (Zhang et al., 2019a ). Recent advances also include the discovery of novel resistance-related genes and pathways through transcriptomic and proteomic analyses, providing a more comprehensive landscape of cotton's immune response to V. dahliae infection. However, the role of epigenetic regulation, particularly DNA methylation, in mediating resistance to this disease remains largely unexplored and poorly understood. Epigenetic modifications constitute a fundamental mechanism for regulating gene expression without altering the underlying DNA sequence, playing a critical role in mediating plant responses to both biotic and abiotic stresses (Lenin et al., 2015 ; Chen et al., 2025 ). Among these modifications, DNA methylation stands out as a key epigenetic mark. It involves the covalent addition of a methyl group to the 5' carbon of cytosine, a reaction catalyzed by DNA methyltransferases using S-adenosylmethionine as the methyl donor. This modification is not only stable but can also be heritable across generations. It is categorized into three sequence contexts-CG, CHG, and CHH (where H represents A, T, or C)-based on the nucleotides immediately following the cytosine (Cokus et al., 2008 ; Lister et al., 2008 ). DNA methylation plays a multifaceted role in regulating plant growth, development, and gene expression, and is increasingly recognized for its importance in response to environmental stresses (He et al., 2011 ; Saze and Kakutani, 2011 ; Song et al., 2015 ; Zhang et al., 2020 ). Under biotic stress, dynamic changes in DNA methylation patterns of stress-related genes can activate the expression of defense genes. For example, pronounced DNA hypomethylation has been observed in the roots of soybean and Arabidopsis following infection with cyst nematodes (Aditi et al., 2015 ; Tarek et al., 2017 ). Likewise, abiotic stresses can trigger substantial changes in DNA methylation levels, as demonstrated in cotton anthers under high-temperature stress (Ma et al., 2018 ). However, despite these insights, the role of DNA methylation in cotton resistance to VW remains poorly understood. Consequently, elucidating the mechanistic basis of DNA methylation in cotton's defense against VW is of considerable importance. This study aims to comprehensively elucidate the mechanisms of DNA methylation in cotton VW resistance. Here we systematically investigated the dynamic changes in DNA methylation and their association with gene expression under V. dahliae stress. Especially, we explored the functional roles and regulatory mechanisms of DNA methylation-related genes and signaling pathways in cotton VW resistance. This research provides novel theoretical insights into the molecular mechanisms underlying cotton VW resistance and offers a foundation for developing strategies to control Verticillium wilt and breed resistant cotton varieties. Results DNA demethylation played an important role in cotton Verticillium wilt resistance To investigate the influence of 5-mC in the cotton resistance against V. dahliae , we identified all the genes that responded to regulating DNA methylation status in cotton, including DNA methyltransferase and DNA demethylase (Hu et al., 2021 ; Faiza et al., 2022 ). Totally, we identified six methylase homologous families (comprising 15 genes) and three demethylase homologous genes (comprising 12 genes) within the cotton genome using https://cottonfgd.org . Under V. dahliae stress, we employed qRT-PCR to detect expression changes of these methylase-related genes and discovered that the expression levels of both DNA methyltransferase and DNA demethylase genes significantly increased compared to the mock plants of resistant NDM8 (Fig. 1 a, b), and similar results were also observed in susceptible TM-1 (Fig. S1 ). This result indicated that DNA demethylation may play an important role in cotton Verticillium wilt resistance. To further confirm whether changes in DNA methylation affect the response of cotton to V. dahliae , we treated NDM8 (resistant variety) and TM-1 (susceptible variety) with the DNA methylation accelerator methyl trifluoromethanesulfonate (MTFMS) and the DNA methyltransferase inhibitor 5-azacitidine (5-azaC) (Hideki et al., 2019 ), respectively. As shown in Fig. 1 c, the resistant cotton seedlings treated by MTFMS with increased global DNA methylation, displayed compromised resistance under different concentrations in NDM8 (Fig. 1 d). Whereas the susceptible cotton seedlings treated by 5-azaC with decreased global DNA methylation, showed improved resistance in TM-1 (Fig. 1 e, f). We also sprayed MTFMS and 5-azaC in the susceptible TM-1 and resistant NDM8, respectively. However, neither the treated TM-1 nor NDM8 displayed obvious altered disease resistance, indicating that global hypomethylation or hypermethylation maybe have a limited effect on VW resistance. Collectively, these results demonstrated that the DNA methylation level was an important influence factor in regulating VW resistance, and the relative lower DNA methylation level could help for enhancing cotton resistance. Furtherly, we successfully suppressed the expression of homologous genes for key DNA methyltransferase genes ( DRM2 , DRM1 , CTM1 , CTM2 , and CTM3 ) and DNA demethylase genes ( ROS1 and DML ) under NDM8 background by using VIGS assay. qRT-PCR results showed that the expression level of each target gene decreased to 28.9%-41.9% compared to the control plants (Fig. 2 ). The silenced seedlings were inoculated with virulence strain LX2-1 and phenotypic investigation was performed. At 25 dpi, the silenced plants of each target gene exhibited more severe symptoms than the control plants, with disease index (DI) over 50.0 that regarded as susceptible (Fig. 2 ). This result also demonstrated that extremely changed the methylation level would destroy cotton defense system. Correlation between different DNA methylation patterns and gene expression during VW resistance To study the influence of different DNA methylation patterns on gene expressions during cotton responded to V. dahliae , we investigated the transcriptome dynamics using the RNA-seq data of NDM8 CK , NDM8 Vd , TM-1 CK , TM-1 Vd . A total of 4116 up-regulated genes and 20655 down-regulated genes were identified in the comparison of NDM8-CK vs NDM8-Vd, while a total of 5435 up-regulated genes and 22602 down-regulated genes were identified in the comparison of TM-1-CK vs TM-1-Vd. It was reported that the expression level of genes is often related to their methylation status. As expected, we observed that nonexpressed genes (fpkm ≤ 1) showed relatively high methylation levels across different regions in all sequence contexts. Then we further focused on the expressed genes and divided them into three subsets according to expression levels ranked from high to low: low expression (1 < fpkm ≤ 10), medium expression (10 100) (Xu et al., 2018 ). In gene body region, all the genes in CG context display relatively high methylation level compared to CHG and CHH contexts. In the upstream region, the higher the methylation level, the lower the gene expression level in CG context, indicating a positive correlation between CG methylation levels in the promoter region were negatively correlated with expression (Fig. 5 a, b). In contrast, gene CHH methylation in promoter region was positively correlated with expression (Fig. 5 c). In the downstream, all the high expression genes maintained higher methylation levels in three contexts (Fig. 5 a-c). These results would provide important guidance for further studying the function of methylation-mediated gene expression changes in cotton VW defense. Analysis of Genes Associated with DNA methylation involved in VW defense To further explore the potential biological functions of the differentially methylated genes (DMGs) involved in cotton defense against V. dahliae , we performed KEGG analysis based on hyper-DMGs and hypo-DMGs. Totally, there were 6830 and 9669 non-redundant DMGs were identified in NDM8 and TM-1, respectively. The DMGs were unevenly distributed on different chromosomes, with most in At05 of NDM8 and Dt11 of TM-1 (Fig. 5 d). The number of DMGs in At was 0.96 and 0.92 times that in Dt for NMD8 and TM-1, respectively, which did not match with the fact that the genome of At was 1.70 times that of Dt, showing significantly lower density in At. KEGG results showed that photosynthesis, oxidative phosphorylation, RNA polymerase, ribosome biogenesis, sesquiterpenoid and triterpenoid biosynthesis, lipid metabolism etc. were significantly enriched based on hyper-DMG (Fig. 5 e) and folate biosynthesis, glycosphingolipid biosynthesis, taurine and hypotaurine metabolism, phenylalanine/tyrosine/tryptophan biosynthesis, amino acids biosynthesis was also highlighted in hypo-DMGs (Fig. 5 f). During the early stage of cotton defense, our study demonstrated that photosynthesis pathway was the top of the significantly enriched metabolic pathways, which played an important role via by-products of cROS and/or epigenetic modification (Chen et al., 2023a ). Here, we found that the 50 genes involved in photosynthesis hit 150 methylation sites. Of which, except for 39 non- or low expressed genes (averaged FPKM < 0.5), nine out of the left 11 genes were all down regulated, especially for GhM_D05G1239 and GhM_A04G0565 sharply decreased (FPKM value from 133.0 to 17.0 and from 27.2 to 9.3, respectively), suggesting that the repression of these genes was regulated by V. dahliae -induced DNA hypermethylation (Table S6). We also found that 23 hyper-DMR associated genes are enriched in the category of RNA polymerase. Most of them were significantly decreased in expression level except for non- or low expressed genes (Table S7). These results indicated that DNA hyper- and hypo-methylation potentially contributed to cotton VW resistance via modulation of genes in multiple pathways that involved in defense process. The RdDM pathway played a central role in altering DNA methylation in cotton resistance to Verticillium wilt It was reported that de novo DNA methylation was mediated by the RNA directed DNA methylation (RdDM) pathway, which can specifically primer CHH methylation and involved in stress-responsive gene expression (Singh et al., 2019 ; Long et al., 2021 ). In our study, clear increases in CHH context in NDM8 and TM-1 roots upon V. dahliae inoculation (Fig. 4 a ) and many more DMRs occurred in the CHH context, we thus focused on changes in the RdDM pathway during cotton defense against V. dahliae . Based on the above KEGG result, RNA polymerase was significantly enriched. It was proved that RNA polymerase IV (Pol IV) and polymerase V (Pol V), ARGONAUTE 4 (AGO4), RDR2, DCL3 were required in RdDM pathway (Matzke and Mosher, 2014 ; Wang and Axtell, 2017 ; Liu et al., 2018b ; Liu et al., 2023 ). Among them, 24- nt siRNA is loaded onto AGO4, which complements the RNA polymerase V transcripts and recruits the methylase DRM2 to complete the DNA methylation reaction. RNA polymerase IV forms a complex with RDR2 to synthesize double stranded RNA. After being processed into 24- nt siRNA, it pairs with the RNA produced by RNA polymerase V and recruits DRM2 to complete DNA methylation. The protein encoded by DCL3 is essential for the formation of endogenous RDR2 dependent siRNA (Liu et al., 2018b ). We identified 31 AGO4 genes, two RDR2 genes and eight DCL3 genes in cotton genome. Transcriptional data showed that the expression levels of three AGO4 ( GhM_A05G1120 , GhM_A08G2555 , GhM_D05G1135 ), two RDR2 ( GhM_D12G3249 , GhM_A12G3363 ) and three DCL3 ( GhM_A05G0544 , GhM_A06G0971 , GhM_D06G0977 ) genes significantly changed after V. dahliae infection, especially at 6 hpi (Fig. 6 a). All above genes displayed decreased expression levels than the mock plants. This result indicated that these genes were involved in regulating DNA methylation and participated in the response of cotton to V. dahliae stress. To verify this hypothesis, we used VIGS to downregulate the expression of above genes in cotton TM-1. We found that the silent plants were more resistant to V. dahliae than the control (Fig. 6 b). These findings proved that the cotton VW resistance was controlled by de novo DNA methylation mediated by small RNAs, RNA polymerase IV, RNA polymerase V, RDR2, AGO4 and DCL3. Considering that AGO4 was a key protein in the RdDM pathway, we investigated the target genes or cooperative partners of AGO4 via yeast hybrid assay. We identified four proteins, ADH1, PER21, At5g56590, and EXLB1, interacted with AGO4. And all these four genes could respond to V. dahliae infection (Fig. 7 a-f). For example, the FPKM values of ADH1 and EXLB1 in NDM8 increased sharply from 452.9 to 2047.9 and from 62.0 to 2841.4 at 12 hpi, respectively. It was reported that ADH could regulate the balance of intracellular redox and participated in plant hormone signal transduction, playing important roles in plant stress resistance (Zeng et al., 2020 ). These result suggested a microcosm of cotton AGO4 and its interacting protein regulating VW resistance. To further investigate the possible transcriptome alteration regulated by AGO4 in cotton, we performed RNA-seq of AGO4 silenced cotton and the control plants. We identified a total of 1,136 DEGs, including 220 significantly upregulated and 916 downregulated genes. KEGG pathway enrichment analysis showed that these DEGs were mainly involved in pathways that participated in defense response, such as cutin/suberine and wax biosynthesis, pentose and glucuronate interconversions, brassinosteroid biosynthesis, sesquiterpenoid and triterpenoid biosynthesis, ABC transporters, alanine/aspartate and glutamate metabolism, glycerophospholipid metabolism, fatty acid elongation and phenylalanine metabolism, pentose and glucuronate interconversions etc. Notably, we found pectin methyl esterase (PME) related genes in pentose and glucuronate interconversions pathway. Previous studies have demonstrated that PME could degrade the cell wall and thereby negatively regulated VW resistance (Sarah et al., 2009 ; Liu et al., 2018a ). In this study, silencing AGO4 significantly suppressed the expression of PME related genes (Table S8), which is coordinated with the enhanced VW resistance of silenced- AGO4 compared to the mock plants. The phenylpropanoid biosynthesis pathway was recognized playing crucial role in VW resistance (Li et al.,2011; Sun et al.,2013; Lei et al.,2018), of which, the implicated genes such as phenylalanine ammonia lyase ( PAL ), cinnamyl alcohol dehydrogenase ( CAD ), and chalcone synthase ( CHS ) displayed significant downregulation in AGO4 silenced plants (Table S8). Furthermore, genome-wide methylation analysis revealed significant changes in CHH methylation levels of PAL genes ( GhM_A11G4070 , GhM_D11G3967 , GhM_A01G2656 ) and the PME gene ( GhM_A12G3073 ) under V. dahliae stress (Fig. 8 ). These findings reflected that the AGO4 medicated VW resistance depends on directly or indirectly changing the DNA methylation status of multiple defense genes, which may provide important evidence for the core regulatory role of the small RNA-mediated DNA methylation (RdDM) pathway in the process of VW resistance in cotton. Discussion DNA methylation and other epigenetic modifications are of great significance for genomic stability, genomic imprinting, transposon silencing, and gene expression regulation in plant development and stress defense (Zhang et al., 2018 ). This study focuses on the role of DNA methylation in cotton VW resistance, and the research findings are of great significance and practical value. In this study, we found that the expression of DNA methyltransferase and demethylase genes increased significantly under the stress of V. dahliae . This revealed a possible causal relationship of DNA demethylation in cotton VW resistance, providing a new perspective for understanding the disease resistance mechanism. We also confirmed that a relative lower DNA methylation level is conducive to enhancing resistance, which provides potential molecular targets for breeding disease resistant varieties. Through the analysis of the whole genome DNA methylation profile, it was discovered that there are asymmetric methylation variations in the cotton genome. The methylation level of the A-subgenome is higher than that of the D-subgenome, and there are also differences among different chromosomes. This provides clues for studying the evolution and function of the cotton genome. This study has clarified that de novo DNA methylation mediated by the RdDM pathway plays a core regulatory role in cotton VW resistance. It was found that after inoculation with V. dahliae , CHH methylation in cotton roots increased significantly, and more DMRs (Differentially Methylated Regions) were generated in the CHH context. Through analysis, several key genes involved in the RdDM pathway were identified, such as AGO4 , RDR2 , and DCL3 . Transcriptome data showed that the expression levels of these genes changed significantly after V. dahliae infection, especially 6 hours post infection, when the expression decreased significantly. After down regulating the expression of related genes using VIGS (Virus Induced Gene Silencing), the silenced plants exhibited enhanced resistance to VW, reaching a disease tolerant level. This fully demonstrates the crucial role of the RdDM pathway in cotton VW resistance. However, this study also has certain limitations. The samples only involve two cotton varieties, which are somewhat limited in terms of diversity. In subsequent research, more varieties with different genetic backgrounds and resistance levels can be added to further explore the DNA methylation regulatory network. In future research directions, on the one hand, it is necessary to investigate the dynamic changes of DNA methylation in different cotton varieties under various environmental conditions to clarify the influence of environmental factors. On the other hand, gene editing technologies can be utilized to precisely edit related genes, aiming to cultivate new cotton varieties with high resistance and promote the development of the cotton industry. Materials and Methods Plant materials and VW stress treatment In this study, two cotton varieties with significant differences in VW resistance were selected: the disease tolerant variety NDM8 and the disease susceptible variety TM- 1. These cotton plants were cultivated hydroponically in the artificial culture room of the College of Agronomy, Hebei Agricultural University (Zhang et al., 2022 ). The light cycle was set to 16 h, the temperature was controlled at (25 ± 2) °C during the day and (23 ± 2) °C at night, and the relative humidity was maintained at 75%. When the seedlings grew to the stage of two- leaf- one- heart, robust and uniformly growing plants were selected (Mo et al., 2021 ). The highly virulent strain LX2- 1 was inoculated, and plants inoculated with distilled water served as the control. Each group retained 90 plants. Cotton roots were collected at 6, 12, 24, 36, and 48 h after inoculation, and samples were taken from the control group at the same time. The roots of every three evenly growing seedlings were pooled as one biological replicate, and three biological replicates were set for each treatment. After sample collection, they were quickly frozen in liquid nitrogen and stored in a -80°C freezer for future use. Treatments with DNA methylation inhibitor and promoter under pathogen stress Under the stress of V. dahliae , the cotton varieties NDM8 and TM-1 were treated with the DNA methylation promoter’s methyl trifluoromethanesulfonate (MTFMS) and 5- azacytidine (5- azaC), and the plants treated with dH₂O served as the negative control (Zhang et al., 2024 ). To determine the optimal spraying concentration, different concentration gradients of 5- azaC (10 mg/L, 50 mg/L, 100 mg/L) and MTFMS (20 mg/L, 60 mg/L, 100 mg/L) were set. The treatment was carried out once every 3 days for a total of 3 times. Each treatment group contained 35 cotton plants. After the treatment, the disease index of the experimental group and the control group was statistically analyzed. Validation of DNA methyltransferase and DNA demethylase homologous genes Using the website https://cottonfgd.org , six homologous families of methyltransferases (a total of 15 genes) and three homologous genes of demethylases (a total of 12 genes) were identified in the cotton genome. The changes in gene expression of NDM8 and TM-1 relative to the control group at 0, 6, 12, 24, 36, and 48 h after V. dahliae stress were detected by qPCR. The VIGS technique was used to downregulate the expression of homologs of major DNA methyltransferase genes (DRM2, DRM1, CTM1, CTM2, and CTM3) and demethylase genes (ROS1 and DML) in cotton NDM8. The specific segments of the candidate genes were cloned into the pTRV2 vector (Wang et al., 2021a ). Approximately 10 days after Agrobacterium infection, the highly virulent strain LX2- 1 was inoculated, and the disease phenotype was observed 25 days later. Extraction of DNA and RNA and library construction Total DNA for whole genome bisulfite sequencing (WGBS) was extracted from cotton root tissues according to the modified CTAB method (Yadav et al., 2012 ). The genomic DNA was fragmented into 100–300 bp fragments by sonication. After end- repair, addition of an A - base at the 3’ end, and ligation of sequencing adapters, bisulfite treatment was carried out using the ZYMO EZ DNA Methylation - Gold kit. The DNA was then desalted, gel- purified, and the size of library fragments was screened. After PCR amplification, screening was performed again. Library construction and quality inspection were completed, and the qualified library was used for sequence on the machine. Total RNA was extracted from root tissues using the Spectrum Plant Total RNA Kit (STRN50, Sigma- Aldrich). After removing rRNA using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina (NEB, USA), a sequencing library was generated. Both WGBS and RNA sequencing were carried out on the Illumina Hiseq 2500/4000 platform (Tong et al., 2021 ; Liu et al., 2023 ). WGBS Analysis The sequencing reads were filtered to remove reads with an N- content ratio > 10% and low- quality reads (where the proportion of bases with a quality value Q 40%), thus obtaining clean reads. BSMAP (Xi and Li, 2009 , Version: 2.90, default parameters) was used to align the filtered data to the genomic sequence. Uniquely aligned sequences were selected for subsequent analysis, and the whole genome base alignment information (bam file) and C base methylation information (cout file) were obtained. Since the DNA samples were from multicellular samples, the C base methylation level ranged from 0–100%. It was calculated by dividing the sum of the methylation levels of effectively covered C bases by the total number of effectively covered bases. The methylation level of a single site = 100×(the number of sequences covering mC / the total number of effectively covered sequences). According to sequence characteristics, C bases were classified into three types: CG, CHG, and CHH. Methylated C bases were determined according to the modified algorithm of Lister et al. (Lister et al., 2008 ). The average methylation levels of various C bases (CG, CHG, and CHH) in different regions of coding genes (Genebody, Exon, Intron, CDS, Five_UTR, Three_UTR, Upstream_2k, Downstream_2k) were statistically analyzed. Identification of DMCs and DMRs The methylkit software (Akalin et al., 2012 , Version:1.4.1) was used for differential DNA methylation analysis. First, sites with low sequencing depth were filtered (the minimum sequencing depth of C sites was ≥ 4). Differential methylation analysis was performed on all C, CG, CHG, and CHH, followed by filtering (the absolute value of methylation difference > 0.1, Q- value < 0.05). A 200bp window was used for whole genome scanning, and the average DNA methylation rate within each window was calculated to compare the differences in methylation levels between samples. The GOseq R package and KOBAS software were utilized to conduct GO and KEGG enrichment analyses on differentially methylated genes. Yeast two hybrid experiment of AGO4 The pGBKT7- AGO4 and pGBKT7 were transformed into yeast competent cells and spread on SD- trp plates to verify that pGBKT7- AGO4 was non - toxic. Then, they were respectively spread on SD- trp, SD- trp/X- α- gal, and SD- trp/X- α- gal/AbA plates to verify no auto- activation. The cotton cDNA library plasmids and pGBKT7- AGO4 were transferred into yeast competent cells (Y2H). After double hybridization by the mating method, 868 colonies grew on the TDO/X- α- gal/AbA plates. After spotting onto the QDO/X- α- gal/AbA plates, 112 colonies turned blue. Through PCR detection with pGADT7 primers, sequencing, and genomic alignment, 40 non- redundant candidate positive clones were obtained. The yeast plasmids of the candidate positive clones were extracted, transformed into DH5α and Y2HGold successively, and then subjected to yeast two- hybrid with pGBKT7- AGO4 and spread on plates. The blue colonies on the TDO/X- α- gal/AbA plates were transferred to the QDO/X- α- gal/AbA plates. The colonies that grew well and showed blue color were judged as positive (Song et al., 2019 ). This method was used to verify the interactions between the four proteins ADH1, PER21, At5g56590, EXLB1 and AGO4. Declarations Acknowledgements This work was supported by the Natural Science Foundation of China (32372194), the Natural Science Foundation of Hebei (C2022204205), the Key Research and Development Program of Hebei Province (21326314D), the National Youth Top Talent Support Program and the National Plan for Shennong Talents. Author contributions statement ZYM and YZ designed the research. ZXZ, XYZ, ZCW, WYC, MJJ, MXJ, JZ performed experiments. YZ, DMZ and JY analyzed data. YZ and ZXZ wrote the manuscript. ZYM and XFW revised the manuscript. All authors read and approved the manuscript. Conflict of Interest Statement The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. Data availability All the authors confirm that the data supporting the findings of this study are available within the article and its Supporting Information. References Aditi R, Hollis RJ, Jinyi L, Thomas L, Priya R, Mitra M, Vince P, Neal SC, Meg S, Tarek H (2015) The methylome of soybean roots during the compatible interaction with the soybean cyst nematode. 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J Soil Sci Plant Nutr 24:6922–6937 Supplementary Files SupportingInformationLegends.docx Fig.S1.jpg Fig.S2.jpg Fig.S3.jpg TableS18.xls Cite Share Download PDF Status: Posted Version 1 posted 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. 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13:42:11","extension":"png","order_by":39,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":618643,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig.S2.png","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/ee86784f40f033fd5a2b0266.png"},{"id":92598434,"identity":"9eb2c7b1-2445-4193-9bdc-2b8e62e54cd8","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"png","order_by":40,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38702,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig.S3.png","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/10fd6c61acc3e4fea8a5c5a4.png"},{"id":92598873,"identity":"a318c425-937e-4250-b646-3a6fe16a0669","added_by":"auto","created_at":"2025-10-01 13:50:12","extension":"xml","order_by":41,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152995,"visible":true,"origin":"","legend":"","description":"","filename":"PCRED25010150structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/2ec85051a0f8a85c3697c9dc.xml"},{"id":92598431,"identity":"a79f56a6-6849-4d3e-b271-4ced26e1e8ff","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"html","order_by":42,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162290,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/b8d43fa9afb0d0b2c5b04500.html"},{"id":92598407,"identity":"467bc252-983e-4ec2-bc7b-a8a4aac00f26","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3094423,"visible":true,"origin":"","legend":"\u003cp\u003eThe role of DNA methylation in the resistance of cotton to Verticillium wilt. (a) The expression changes of DNA methyltransferase genes in NDM8 under the stress of \u003cem\u003eV. dahliae\u003c/em\u003e; (b) The expression changes of DNA demethylase genes in NDM8 under the stress of \u003cem\u003eV. dahliae\u003c/em\u003e; (c-d) The phenotypes of NDM8 with the application of MTFMS under the stress of \u003cem\u003eV. dahliae\u003c/em\u003e; (e-f) The phenotypes of TM-1 with the application of 5-azaC under the stress of \u003cem\u003eV. dahliae\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/df6827b8260c978190294f02.jpg"},{"id":92598404,"identity":"71626ec3-3ec7-4651-adf9-c23f87cec831","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5214232,"visible":true,"origin":"","legend":"\u003cp\u003eThe phenotypes of NDM8 with the silencing of genes related to DNA methyltransferases and DNA demethylases under the stress of \u003cem\u003eV. dahliae\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/ed2732224182102abcd80903.jpg"},{"id":92598406,"identity":"5d21ea88-626c-42b1-8171-f556d17d5050","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":890107,"visible":true,"origin":"","legend":"\u003cp\u003eMethylation distribution of 26 chromosomes based on upland cotton. (a) Methylation distribution map of 26 chromosomes in cotton. (b) The overall distribution of the methylation level on the chromosomes. (c) The hypermethylation positions of four chromosomes, namely A09, D07, D09, and D10. (d) The overall methylation level of each chromosome. (e) Comparison of the methylation levels of the two subgenomes in cotton. (f) The methylation levels of the two subgenomes in cotton under the environments of three types of sequences (CG, CHG, CHH).\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/e3b28f6ec8d50306c525cf48.jpg"},{"id":92598410,"identity":"cdf222a8-3d96-4b4d-9596-6355fc0906d8","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":441101,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic changes of DNA methylation in cotton infected by \u003cem\u003eV. dahliae. \u003c/em\u003e(a) The proportion of various types of mC sites in the total mC sites; (b) The average methylation level of various types of mC in the whole genome of cotton; (c) The methylation levels of the At and Dt subgenomes of cotton.\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/ce1a3bc2c7d80c8bd6f7d8b2.jpg"},{"id":92598413,"identity":"9e4adeb7-a990-4337-8dec-3fff232f98f5","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":764231,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of DNA methylation-related genes involved in the defense against Verticillium wilt. (a) The relationship between DNA methylation and gene expression in the CG context; (b) The relationship between DNA methylation and gene expression in the CHG context; (c) The relationship between DNA methylation and gene expression in the CHH context; (d)The differentially methylated genes (DMGs) of NDM8 and TM-1 respectively；(e)KEGG analysis of hyper-DMGs of NDM8 after \u003cem\u003eV. dahliae\u003c/em\u003e stress; (f) KEGG analysis of hypo-DMGs of NDM8 after \u003cem\u003eV. dahliae\u003c/em\u003estress.\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/629621fb6de2f6aa5d5d8b26.jpg"},{"id":92598423,"identity":"79d97c6f-2719-494a-9c5e-6fc3aee2e474","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":7183058,"visible":true,"origin":"","legend":"\u003cp\u003eFurther verification of genes related to the RdDM pathway. (a) Changes in the expression levels of homologous genes of cotton RNA polymerase IV, RNA polymerase V, RDR2, AGO4, and DCL3 under \u003cem\u003eV. dahliae\u003c/em\u003e stress. (b) Phenotypes of TM-1 after silencing the genes of RNA polymerase IV, RNA polymerase V, RDR2, AGO4, and DCL3 under \u003cem\u003eV. dahliae \u003c/em\u003estress.\u003c/p\u003e","description":"","filename":"Fig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/ead65c48d1cf1f1c7a4a5f6a.jpg"},{"id":92598862,"identity":"bba04641-9b7d-4c08-a654-3ef682986856","added_by":"auto","created_at":"2025-10-01 13:50:11","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":317697,"visible":true,"origin":"","legend":"\u003cp\u003eAGO4 can interact with ADH1, PER21, At5g56590, and EXLB1 shown by yeast two-hybrid assay. (a) SD-Trp plate transformed with pGBKT7; (b, c) SD-Trp plate transformed with pGBKT7-AGO4; (d) SD-Trp/X-α-Gal plate transformed with pGBKT7-AGO4; (e) SD-Trp/AbA/X-α-Gal plate transformed with pGBKT7-AGO4; (f) SD/-Ade-His-Leu-Trp/AbA /X-α-Gal- plate was used for one-to-one verification of protein interaction.\u003c/p\u003e","description":"","filename":"Fig.7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/d29a04a00766fc24e33a8c22.jpg"},{"id":92598863,"identity":"f1de3407-2e48-431d-8e8b-f7704deb1741","added_by":"auto","created_at":"2025-10-01 13:50:11","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":3109391,"visible":true,"origin":"","legend":"\u003cp\u003eVisualization diagrams of the differential CHH methylation regions and transcriptomes of the \u003cem\u003ePAL\u003c/em\u003e and \u003cem\u003ePME\u003c/em\u003e genes.\u003c/p\u003e","description":"","filename":"Fig.8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/70d2d318522a5593d585ef79.jpg"},{"id":93917446,"identity":"7e5e086a-f0bc-4733-abf3-bfb41e1c2c82","added_by":"auto","created_at":"2025-10-20 09:06:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":21795686,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/4d2cb5c9-e2d5-4d9b-b049-c14848a47414.pdf"},{"id":92598403,"identity":"47aca3ba-db2e-4f11-8f3e-e237d317e42f","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":14745,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingInformationLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/7a90ef5876d1356fcad69c64.docx"},{"id":92598409,"identity":"12789b56-fd88-4a38-a67d-630276fa5a88","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":300894,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/686cf757554150b98eaced25.jpg"},{"id":92600033,"identity":"206cff70-10da-4ae6-8266-8a7baafddb19","added_by":"auto","created_at":"2025-10-01 13:58:12","extension":"jpg","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":712464,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/8c0050a3a74485ddb4de9d03.jpg"},{"id":92598415,"identity":"f3a80d2e-a5be-4acc-a330-5f28ba1e1430","added_by":"auto","created_at":"2025-10-01 13:42:11","extension":"jpg","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":414836,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/256502abde70328625b7881f.jpg"},{"id":92598870,"identity":"05364c48-a426-4447-a164-81d0fafcbf24","added_by":"auto","created_at":"2025-10-01 13:50:11","extension":"xls","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":2690048,"visible":true,"origin":"","legend":"","description":"","filename":"TableS18.xls","url":"https://assets-eu.researchsquare.com/files/rs-7531123/v1/89b4c3cc1ee00b541978fc6b.xls"}],"financialInterests":"","formattedTitle":"The landscape of cotton DNA methylation and its epigenetic regulation in Verticillium wilt resistance","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCotton, a globally significant economic crop, plays a vital role in both agricultural and industrial sectors. However, cotton production has long been severely threatened by Verticillium wilt (VW), a devastating soil-borne disease caused by the fungus \u003cem\u003eVerticillium dahliae\u003c/em\u003e. This disease is among the most destructive to cotton cultivation, greatly hindering the sustainable development of the global cotton industry (Zhang et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Infection leads to substantial yield losses and reduced fiber quality, resulting in considerable economic damage to growers (Gong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Given the broad host range, prolonged persistence in soil, and ability of \u003cem\u003eV. dahliae\u003c/em\u003e to produce resilient dormant structures such as microsclerotia, controlling the pathogen is extremely challenging. Consequently, the use of resistant cotton cultivars has emerged as the most economical, environmentally safe, and effective strategy for managing Verticillium wilt (Xu et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). Ongoing research in breeding and genetic resistance remains essential to alleviating the impact of this persistent and widespread disease.\u003c/p\u003e\u003cp\u003eIn recent years, significant progress has been made in understanding the genetic basis and molecular mechanisms of cotton resistance to Verticillium wilt at the genomic, transcriptomic, and proteomic levels. For example, the molecular mechanisms underlying this resistance have been further elucidated through GWAS, revealing the involvement of NLR proteins containing dual TIR domains and leading to the identification of key resistance genes such as \u003cem\u003eGhRVD1\u003c/em\u003e (Zhang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Additionally, studies have uncovered the critical role of laccase-mediated defense-induced lignification in enhancing cotton VW resistance (Zhang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Recent advances also include the discovery of novel resistance-related genes and pathways through transcriptomic and proteomic analyses, providing a more comprehensive landscape of cotton's immune response to \u003cem\u003eV. dahliae\u003c/em\u003e infection. However, the role of epigenetic regulation, particularly DNA methylation, in mediating resistance to this disease remains largely unexplored and poorly understood.\u003c/p\u003e\u003cp\u003eEpigenetic modifications constitute a fundamental mechanism for regulating gene expression without altering the underlying DNA sequence, playing a critical role in mediating plant responses to both biotic and abiotic stresses (Lenin et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Among these modifications, DNA methylation stands out as a key epigenetic mark. It involves the covalent addition of a methyl group to the 5' carbon of cytosine, a reaction catalyzed by DNA methyltransferases using S-adenosylmethionine as the methyl donor. This modification is not only stable but can also be heritable across generations. It is categorized into three sequence contexts-CG, CHG, and CHH (where H represents A, T, or C)-based on the nucleotides immediately following the cytosine (Cokus et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Lister et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). DNA methylation plays a multifaceted role in regulating plant growth, development, and gene expression, and is increasingly recognized for its importance in response to environmental stresses (He et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Saze and Kakutani, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Under biotic stress, dynamic changes in DNA methylation patterns of stress-related genes can activate the expression of defense genes. For example, pronounced DNA hypomethylation has been observed in the roots of soybean and Arabidopsis following infection with cyst nematodes (Aditi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Tarek et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Likewise, abiotic stresses can trigger substantial changes in DNA methylation levels, as demonstrated in cotton anthers under high-temperature stress (Ma et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, despite these insights, the role of DNA methylation in cotton resistance to VW remains poorly understood. Consequently, elucidating the mechanistic basis of DNA methylation in cotton's defense against VW is of considerable importance.\u003c/p\u003e\u003cp\u003eThis study aims to comprehensively elucidate the mechanisms of DNA methylation in cotton VW resistance. Here we systematically investigated the dynamic changes in DNA methylation and their association with gene expression under \u003cem\u003eV. dahliae\u003c/em\u003e stress. Especially, we explored the functional roles and regulatory mechanisms of DNA methylation-related genes and signaling pathways in cotton VW resistance. This research provides novel theoretical insights into the molecular mechanisms underlying cotton VW resistance and offers a foundation for developing strategies to control Verticillium wilt and breed resistant cotton varieties.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDNA demethylation played an important role in cotton Verticillium wilt resistance\u003c/h2\u003e\u003cp\u003eTo investigate the influence of 5-mC in the cotton resistance against \u003cem\u003eV. dahliae\u003c/em\u003e, we identified all the genes that responded to regulating DNA methylation status in cotton, including DNA methyltransferase and DNA demethylase (Hu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Faiza et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Totally, we identified six methylase homologous families (comprising 15 genes) and three demethylase homologous genes (comprising 12 genes) within the cotton genome using \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cottonfgd.org\u003c/span\u003e\u003cspan address=\"https://cottonfgd.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Under \u003cem\u003eV. dahliae\u003c/em\u003e stress, we employed qRT-PCR to detect expression changes of these methylase-related genes and discovered that the expression levels of both DNA methyltransferase and DNA demethylase genes significantly increased compared to the mock plants of resistant NDM8 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b), and similar results were also observed in susceptible TM-1 (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). This result indicated that DNA demethylation may play an important role in cotton Verticillium wilt resistance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further confirm whether changes in DNA methylation affect the response of cotton to \u003cem\u003eV. dahliae\u003c/em\u003e, we treated NDM8 (resistant variety) and TM-1 (susceptible variety) with the DNA methylation accelerator methyl trifluoromethanesulfonate (MTFMS) and the DNA methyltransferase inhibitor 5-azacitidine (5-azaC) (Hideki et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), respectively. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ec, the resistant cotton seedlings treated by MTFMS with increased global DNA methylation, displayed compromised resistance under different concentrations in NDM8 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Whereas the susceptible cotton seedlings treated by 5-azaC with decreased global DNA methylation, showed improved resistance in TM-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, f). We also sprayed MTFMS and 5-azaC in the susceptible TM-1 and resistant NDM8, respectively. However, neither the treated TM-1 nor NDM8 displayed obvious altered disease resistance, indicating that global hypomethylation or hypermethylation maybe have a limited effect on VW resistance. Collectively, these results demonstrated that the DNA methylation level was an important influence factor in regulating VW resistance, and the relative lower DNA methylation level could help for enhancing cotton resistance.\u003c/p\u003e\u003cp\u003eFurtherly, we successfully suppressed the expression of homologous genes for key DNA methyltransferase genes (\u003cem\u003eDRM2\u003c/em\u003e, \u003cem\u003eDRM1\u003c/em\u003e, \u003cem\u003eCTM1\u003c/em\u003e, \u003cem\u003eCTM2\u003c/em\u003e, and \u003cem\u003eCTM3\u003c/em\u003e) and DNA demethylase genes (\u003cem\u003eROS1\u003c/em\u003e and \u003cem\u003eDML\u003c/em\u003e) under NDM8 background by using VIGS assay. qRT-PCR results showed that the expression level of each target gene decreased to 28.9%-41.9% compared to the control plants (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The silenced seedlings were inoculated with virulence strain LX2-1 and phenotypic investigation was performed. At 25 dpi, the silenced plants of each target gene exhibited more severe symptoms than the control plants, with disease index (DI) over 50.0 that regarded as susceptible (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This result also demonstrated that extremely changed the methylation level would destroy cotton defense system.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCorrelation between different DNA methylation patterns and gene expression during VW resistance\u003c/h3\u003e\n\u003cp\u003eTo study the influence of different DNA methylation patterns on gene expressions during cotton responded to \u003cem\u003eV. dahliae\u003c/em\u003e, we investigated the transcriptome dynamics using the RNA-seq data of NDM8\u003csup\u003eCK\u003c/sup\u003e, NDM8\u003csup\u003eVd\u003c/sup\u003e, TM-1\u003csup\u003eCK\u003c/sup\u003e, TM-1\u003csup\u003eVd\u003c/sup\u003e. A total of 4116 up-regulated genes and 20655 down-regulated genes were identified in the comparison of NDM8-CK vs NDM8-Vd, while a total of 5435 up-regulated genes and 22602 down-regulated genes were identified in the comparison of TM-1-CK vs TM-1-Vd. It was reported that the expression level of genes is often related to their methylation status. As expected, we observed that nonexpressed genes (fpkm\u0026thinsp;\u0026le;\u0026thinsp;1) showed relatively high methylation levels across different regions in all sequence contexts. Then we further focused on the expressed genes and divided them into three subsets according to expression levels ranked from high to low: low expression (1\u0026thinsp;\u0026lt;\u0026thinsp;fpkm\u0026thinsp;\u0026le;\u0026thinsp;10), medium expression (10\u0026thinsp;\u0026lt;\u0026thinsp;fpkm\u0026thinsp;\u0026le;\u0026thinsp;100) and high expression (fpkm\u0026thinsp;\u0026gt;\u0026thinsp;100) (Xu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In gene body region, all the genes in CG context display relatively high methylation level compared to CHG and CHH contexts. In the upstream region, the higher the methylation level, the lower the gene expression level in CG context, indicating a positive correlation between CG methylation levels in the promoter region were negatively correlated with expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, b). In contrast, gene CHH methylation in promoter region was positively correlated with expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). In the downstream, all the high expression genes maintained higher methylation levels in three contexts (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-c). These results would provide important guidance for further studying the function of methylation-mediated gene expression changes in cotton VW defense.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eAnalysis of Genes Associated with DNA methylation involved in VW defense\u003c/h3\u003e\n\u003cp\u003eTo further explore the potential biological functions of the differentially methylated genes (DMGs) involved in cotton defense against \u003cem\u003eV. dahliae\u003c/em\u003e, we performed KEGG analysis based on hyper-DMGs and hypo-DMGs. Totally, there were 6830 and 9669 non-redundant DMGs were identified in NDM8 and TM-1, respectively. The DMGs were unevenly distributed on different chromosomes, with most in At05 of NDM8 and Dt11 of TM-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). The number of DMGs in At was 0.96 and 0.92 times that in Dt for NMD8 and TM-1, respectively, which did not match with the fact that the genome of At was 1.70 times that of Dt, showing significantly lower density in At. KEGG results showed that photosynthesis, oxidative phosphorylation, RNA polymerase, ribosome biogenesis, sesquiterpenoid and triterpenoid biosynthesis, lipid metabolism etc. were significantly enriched based on hyper-DMG (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ee) and folate biosynthesis, glycosphingolipid biosynthesis, taurine and hypotaurine metabolism, phenylalanine/tyrosine/tryptophan biosynthesis, amino acids biosynthesis was also highlighted in hypo-DMGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003ef). During the early stage of cotton defense, our study demonstrated that photosynthesis pathway was the top of the significantly enriched metabolic pathways, which played an important role via by-products of cROS and/or epigenetic modification (Chen et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e). Here, we found that the 50 genes involved in photosynthesis hit 150 methylation sites. Of which, except for 39 non- or low expressed genes (averaged FPKM\u0026thinsp;\u0026lt;\u0026thinsp;0.5), nine out of the left 11 genes were all down regulated, especially for GhM_D05G1239 and GhM_A04G0565 sharply decreased (FPKM value from 133.0 to 17.0 and from 27.2 to 9.3, respectively), suggesting that the repression of these genes was regulated by \u003cem\u003eV. dahliae\u003c/em\u003e-induced DNA hypermethylation (Table S6). We also found that 23 hyper-DMR associated genes are enriched in the category of RNA polymerase. Most of them were significantly decreased in expression level except for non- or low expressed genes (Table S7). These results indicated that DNA hyper- and hypo-methylation potentially contributed to cotton VW resistance via modulation of genes in multiple pathways that involved in defense process.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe RdDM pathway played a central role in altering DNA methylation in cotton resistance to Verticillium wilt\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIt was reported that \u003cem\u003ede novo\u003c/em\u003e DNA methylation was mediated by the RNA directed DNA methylation (RdDM) pathway, which can specifically primer CHH methylation and involved in stress-responsive gene expression (Singh et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Long et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In our study, clear increases in CHH context in NDM8 and TM-1 roots upon \u003cem\u003eV. dahliae\u003c/em\u003e inoculation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003ea ) and many more DMRs occurred in the CHH context, we thus focused on changes in the RdDM pathway during cotton defense against \u003cem\u003eV. dahliae\u003c/em\u003e. Based on the above KEGG result, RNA polymerase was significantly enriched. It was proved that RNA polymerase IV (Pol IV) and polymerase V (Pol V), ARGONAUTE 4 (AGO4), RDR2, DCL3 were required in RdDM pathway (Matzke and Mosher, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wang and Axtell, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among them, 24- nt siRNA is loaded onto AGO4, which complements the RNA polymerase V transcripts and recruits the methylase DRM2 to complete the DNA methylation reaction. RNA polymerase IV forms a complex with RDR2 to synthesize double stranded RNA. After being processed into 24- nt siRNA, it pairs with the RNA produced by RNA polymerase V and recruits DRM2 to complete DNA methylation. The protein encoded by DCL3 is essential for the formation of endogenous RDR2 dependent siRNA (Liu et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe identified 31 \u003cem\u003eAGO4\u003c/em\u003e genes, two \u003cem\u003eRDR2\u003c/em\u003e genes and eight DCL3 genes in cotton genome. Transcriptional data showed that the expression levels of three \u003cem\u003eAGO4\u003c/em\u003e (\u003cem\u003eGhM_A05G1120\u003c/em\u003e, \u003cem\u003eGhM_A08G2555\u003c/em\u003e, \u003cem\u003eGhM_D05G1135\u003c/em\u003e), two RDR2 (\u003cem\u003eGhM_D12G3249\u003c/em\u003e, \u003cem\u003eGhM_A12G3363\u003c/em\u003e) and three DCL3 (\u003cem\u003eGhM_A05G0544\u003c/em\u003e, \u003cem\u003eGhM_A06G0971\u003c/em\u003e, \u003cem\u003eGhM_D06G0977\u003c/em\u003e) genes significantly changed after \u003cem\u003eV. dahliae\u003c/em\u003e infection, especially at 6 hpi (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). All above genes displayed decreased expression levels than the mock plants. This result indicated that these genes were involved in regulating DNA methylation and participated in the response of cotton to \u003cem\u003eV. dahliae\u003c/em\u003e stress. To verify this hypothesis, we used VIGS to downregulate the expression of above genes in cotton TM-1. We found that the silent plants were more resistant to \u003cem\u003eV. dahliae\u003c/em\u003e than the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). These findings proved that the cotton VW resistance was controlled by de novo DNA methylation mediated by small RNAs, RNA polymerase IV, RNA polymerase V, RDR2, AGO4 and DCL3.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eConsidering that AGO4 was a key protein in the RdDM pathway, we investigated the target genes or cooperative partners of AGO4 via yeast hybrid assay. We identified four proteins, ADH1, PER21, At5g56590, and EXLB1, interacted with AGO4. And all these four genes could respond to \u003cem\u003eV. dahliae\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003ea-f). For example, the FPKM values of \u003cem\u003eADH1\u003c/em\u003e and \u003cem\u003eEXLB1\u003c/em\u003e in NDM8 increased sharply from 452.9 to 2047.9 and from 62.0 to 2841.4 at 12 hpi, respectively. It was reported that \u003cem\u003eADH\u003c/em\u003e could regulate the balance of intracellular redox and participated in plant hormone signal transduction, playing important roles in plant stress resistance (Zeng et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These result suggested a microcosm of cotton AGO4 and its interacting protein regulating VW resistance.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further investigate the possible transcriptome alteration regulated by AGO4 in cotton, we performed RNA-seq of \u003cem\u003eAGO4\u003c/em\u003e silenced cotton and the control plants. We identified a total of 1,136 DEGs, including 220 significantly upregulated and 916 downregulated genes. KEGG pathway enrichment analysis showed that these DEGs were mainly involved in pathways that participated in defense response, such as cutin/suberine and wax biosynthesis, pentose and glucuronate interconversions, brassinosteroid biosynthesis, sesquiterpenoid and triterpenoid biosynthesis, ABC transporters, alanine/aspartate and glutamate metabolism, glycerophospholipid metabolism, fatty acid elongation and phenylalanine metabolism, pentose and glucuronate interconversions etc. Notably, we found pectin methyl esterase (PME) related genes in pentose and glucuronate interconversions pathway. Previous studies have demonstrated that PME could degrade the cell wall and thereby negatively regulated VW resistance (Sarah et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). In this study, silencing \u003cem\u003eAGO4\u003c/em\u003e significantly suppressed the expression of \u003cem\u003ePME\u003c/em\u003e related genes (Table S8), which is coordinated with the enhanced VW resistance of silenced-\u003cem\u003eAGO4\u003c/em\u003e compared to the mock plants. The phenylpropanoid biosynthesis pathway was recognized playing crucial role in VW resistance (Li et al.,2011; Sun et al.,2013; Lei et al.,2018), of which, the implicated genes such as phenylalanine ammonia lyase (\u003cem\u003ePAL\u003c/em\u003e), cinnamyl alcohol dehydrogenase (\u003cem\u003eCAD\u003c/em\u003e), and chalcone synthase (\u003cem\u003eCHS\u003c/em\u003e) displayed significant downregulation in \u003cem\u003eAGO4\u003c/em\u003e silenced plants (Table S8). Furthermore, genome-wide methylation analysis revealed significant changes in CHH methylation levels of \u003cem\u003ePAL\u003c/em\u003e genes (\u003cem\u003eGhM_A11G4070\u003c/em\u003e, \u003cem\u003eGhM_D11G3967\u003c/em\u003e, \u003cem\u003eGhM_A01G2656\u003c/em\u003e) and the \u003cem\u003ePME\u003c/em\u003e gene (\u003cem\u003eGhM_A12G3073\u003c/em\u003e) under \u003cem\u003eV. dahliae\u003c/em\u003e stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These findings reflected that the \u003cem\u003eAGO4\u003c/em\u003e medicated VW resistance depends on directly or indirectly changing the DNA methylation status of multiple defense genes, which may provide important evidence for the core regulatory role of the small RNA-mediated DNA methylation (RdDM) pathway in the process of VW resistance in cotton.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDNA methylation and other epigenetic modifications are of great significance for genomic stability, genomic imprinting, transposon silencing, and gene expression regulation in plant development and stress defense (Zhang et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This study focuses on the role of DNA methylation in cotton VW resistance, and the research findings are of great significance and practical value. In this study, we found that the expression of DNA methyltransferase and demethylase genes increased significantly under the stress of \u003cem\u003eV. dahliae\u003c/em\u003e. This revealed a possible causal relationship of DNA demethylation in cotton VW resistance, providing a new perspective for understanding the disease resistance mechanism. We also confirmed that a relative lower DNA methylation level is conducive to enhancing resistance, which provides potential molecular targets for breeding disease resistant varieties. Through the analysis of the whole genome DNA methylation profile, it was discovered that there are asymmetric methylation variations in the cotton genome. The methylation level of the A-subgenome is higher than that of the D-subgenome, and there are also differences among different chromosomes. This provides clues for studying the evolution and function of the cotton genome.\u003c/p\u003e\u003cp\u003eThis study has clarified that de novo DNA methylation mediated by the RdDM pathway plays a core regulatory role in cotton VW resistance. It was found that after inoculation with \u003cem\u003eV. dahliae\u003c/em\u003e, CHH methylation in cotton roots increased significantly, and more DMRs (Differentially Methylated Regions) were generated in the CHH context. Through analysis, several key genes involved in the RdDM pathway were identified, such as \u003cem\u003eAGO4\u003c/em\u003e, \u003cem\u003eRDR2\u003c/em\u003e, and \u003cem\u003eDCL3\u003c/em\u003e. Transcriptome data showed that the expression levels of these genes changed significantly after \u003cem\u003eV. dahliae\u003c/em\u003e infection, especially 6 hours post infection, when the expression decreased significantly. After down regulating the expression of related genes using VIGS (Virus Induced Gene Silencing), the silenced plants exhibited enhanced resistance to VW, reaching a disease tolerant level. This fully demonstrates the crucial role of the RdDM pathway in cotton VW resistance.\u003c/p\u003e\u003cp\u003eHowever, this study also has certain limitations. The samples only involve two cotton varieties, which are somewhat limited in terms of diversity. In subsequent research, more varieties with different genetic backgrounds and resistance levels can be added to further explore the DNA methylation regulatory network. In future research directions, on the one hand, it is necessary to investigate the dynamic changes of DNA methylation in different cotton varieties under various environmental conditions to clarify the influence of environmental factors. On the other hand, gene editing technologies can be utilized to precisely edit related genes, aiming to cultivate new cotton varieties with high resistance and promote the development of the cotton industry.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003ePlant materials and VW stress treatment\u003c/h2\u003e\u003cp\u003eIn this study, two cotton varieties with significant differences in VW resistance were selected: the disease tolerant variety NDM8 and the disease susceptible variety TM- 1. These cotton plants were cultivated hydroponically in the artificial culture room of the College of Agronomy, Hebei Agricultural University (Zhang et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The light cycle was set to 16 h, the temperature was controlled at (25\u0026thinsp;\u0026plusmn;\u0026thinsp;2) \u0026deg;C during the day and (23\u0026thinsp;\u0026plusmn;\u0026thinsp;2) \u0026deg;C at night, and the relative humidity was maintained at 75%. When the seedlings grew to the stage of two- leaf- one- heart, robust and uniformly growing plants were selected (Mo et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The highly virulent strain LX2- 1 was inoculated, and plants inoculated with distilled water served as the control. Each group retained 90 plants. Cotton roots were collected at 6, 12, 24, 36, and 48 h after inoculation, and samples were taken from the control group at the same time. The roots of every three evenly growing seedlings were pooled as one biological replicate, and three biological replicates were set for each treatment. After sample collection, they were quickly frozen in liquid nitrogen and stored in a -80\u0026deg;C freezer for future use.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTreatments with DNA methylation inhibitor and promoter under pathogen stress\u003c/h3\u003e\n\u003cp\u003eUnder the stress of \u003cem\u003eV. dahliae\u003c/em\u003e, the cotton varieties NDM8 and TM-1 were treated with the DNA methylation promoter\u0026rsquo;s methyl trifluoromethanesulfonate (MTFMS) and 5- azacytidine (5- azaC), and the plants treated with dH₂O served as the negative control (Zhang et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). To determine the optimal spraying concentration, different concentration gradients of 5- azaC (10 mg/L, 50 mg/L, 100 mg/L) and MTFMS (20 mg/L, 60 mg/L, 100 mg/L) were set. The treatment was carried out once every 3 days for a total of 3 times. Each treatment group contained 35 cotton plants. After the treatment, the disease index of the experimental group and the control group was statistically analyzed.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eValidation of DNA methyltransferase and DNA demethylase homologous genes\u003c/h2\u003e\u003cp\u003eUsing the website \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cottonfgd.org\u003c/span\u003e\u003cspan address=\"https://cottonfgd.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, six homologous families of methyltransferases (a total of 15 genes) and three homologous genes of demethylases (a total of 12 genes) were identified in the cotton genome. The changes in gene expression of NDM8 and TM-1 relative to the control group at 0, 6, 12, 24, 36, and 48 h after \u003cem\u003eV. dahliae\u003c/em\u003e stress were detected by qPCR. The VIGS technique was used to downregulate the expression of homologs of major DNA methyltransferase genes (DRM2, DRM1, CTM1, CTM2, and CTM3) and demethylase genes (ROS1 and DML) in cotton NDM8. The specific segments of the candidate genes were cloned into the pTRV2 vector (Wang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Approximately 10 days after Agrobacterium infection, the highly virulent strain LX2- 1 was inoculated, and the disease phenotype was observed 25 days later.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eExtraction of DNA and RNA and library construction\u003c/h2\u003e\u003cp\u003eTotal DNA for whole genome bisulfite sequencing (WGBS) was extracted from cotton root tissues according to the modified CTAB method (Yadav et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The genomic DNA was fragmented into 100\u0026ndash;300 bp fragments by sonication. After end- repair, addition of an A - base at the 3\u0026rsquo; end, and ligation of sequencing adapters, bisulfite treatment was carried out using the ZYMO EZ DNA Methylation - Gold kit. The DNA was then desalted, gel- purified, and the size of library fragments was screened. After PCR amplification, screening was performed again. Library construction and quality inspection were completed, and the qualified library was used for sequence on the machine. Total RNA was extracted from root tissues using the Spectrum Plant Total RNA Kit (STRN50, Sigma- Aldrich). After removing rRNA using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina (NEB, USA), a sequencing library was generated. Both WGBS and RNA sequencing were carried out on the Illumina Hiseq 2500/4000 platform (Tong et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eWGBS Analysis\u003c/h2\u003e\u003cp\u003eThe sequencing reads were filtered to remove reads with an N- content ratio\u0026thinsp;\u0026gt;\u0026thinsp;10% and low- quality reads (where the proportion of bases with a quality value Q\u0026thinsp;\u0026lt;\u0026thinsp;20 was \u0026gt;\u0026thinsp;40%), thus obtaining clean reads. BSMAP (Xi and Li, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Version: 2.90, default parameters) was used to align the filtered data to the genomic sequence. Uniquely aligned sequences were selected for subsequent analysis, and the whole genome base alignment information (bam file) and C base methylation information (cout file) were obtained. Since the DNA samples were from multicellular samples, the C base methylation level ranged from 0\u0026ndash;100%. It was calculated by dividing the sum of the methylation levels of effectively covered C bases by the total number of effectively covered bases. The methylation level of a single site\u0026thinsp;=\u0026thinsp;100\u0026times;(the number of sequences covering mC / the total number of effectively covered sequences). According to sequence characteristics, C bases were classified into three types: CG, CHG, and CHH. Methylated C bases were determined according to the modified algorithm of Lister et al. (Lister et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The average methylation levels of various C bases (CG, CHG, and CHH) in different regions of coding genes (Genebody, Exon, Intron, CDS, Five_UTR, Three_UTR, Upstream_2k, Downstream_2k) were statistically analyzed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eIdentification of DMCs and DMRs\u003c/h2\u003e\u003cp\u003eThe methylkit software (Akalin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, Version:1.4.1) was used for differential DNA methylation analysis. First, sites with low sequencing depth were filtered (the minimum sequencing depth of C sites was \u0026ge;\u0026thinsp;4). Differential methylation analysis was performed on all C, CG, CHG, and CHH, followed by filtering (the absolute value of methylation difference\u0026thinsp;\u0026gt;\u0026thinsp;0.1, Q- value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A 200bp window was used for whole genome scanning, and the average DNA methylation rate within each window was calculated to compare the differences in methylation levels between samples. The GOseq R package and KOBAS software were utilized to conduct GO and KEGG enrichment analyses on differentially methylated genes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eYeast two hybrid experiment of AGO4\u003c/h2\u003e\u003cp\u003eThe pGBKT7- AGO4 and pGBKT7 were transformed into yeast competent cells and spread on SD- trp plates to verify that pGBKT7- AGO4 was non - toxic. Then, they were respectively spread on SD- trp, SD- trp/X- α- gal, and SD- trp/X- α- gal/AbA plates to verify no auto- activation. The cotton cDNA library plasmids and pGBKT7- AGO4 were transferred into yeast competent cells (Y2H). After double hybridization by the mating method, 868 colonies grew on the TDO/X- α- gal/AbA plates. After spotting onto the QDO/X- α- gal/AbA plates, 112 colonies turned blue. Through PCR detection with pGADT7 primers, sequencing, and genomic alignment, 40 non- redundant candidate positive clones were obtained. The yeast plasmids of the candidate positive clones were extracted, transformed into DH5α and Y2HGold successively, and then subjected to yeast two- hybrid with pGBKT7- AGO4 and spread on plates. The blue colonies on the TDO/X- α- gal/AbA plates were transferred to the QDO/X- α- gal/AbA plates. The colonies that grew well and showed blue color were judged as positive (Song et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This method was used to verify the interactions between the four proteins ADH1, PER21, At5g56590, EXLB1 and AGO4.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Natural Science Foundation of China (32372194), the Natural Science Foundation of Hebei (C2022204205), the Key Research and Development Program of Hebei Province (21326314D), the National Youth Top Talent Support Program and the National Plan for Shennong Talents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZYM and YZ designed the research. ZXZ, XYZ, ZCW, WYC, MJJ, MXJ, JZ performed experiments. YZ, DMZ and JY analyzed data. YZ and ZXZ wrote the manuscript. ZYM and XFW revised the manuscript. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e All the authors confirm that the data supporting the findings of this study are available within the article and its Supporting Information.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAditi R, Hollis RJ, Jinyi L, Thomas L, Priya R, Mitra M, Vince P, Neal SC, Meg S, Tarek H (2015) The methylome of soybean roots during the compatible interaction with the soybean cyst nematode. 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J Soil Sci Plant Nutr 24:6922\u0026ndash;6937\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cotton, DNA methylation, Verticillium wilt, RdDM pathway, AGO protein","lastPublishedDoi":"10.21203/rs.3.rs-7531123/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7531123/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVerticillium wilt (VW) is a devastating disease that causes severe losses in cotton yield and fiber quality. While DNA methylation is known to regulate various processes in plant development and stress responses, its specific role in conferring host resistance remains unclear. To elucidate the regulatory mechanism of DNA methylation in VW resistance, we compared the genome-wide DNA methylation profiles of a resistant cotton cultivar (NDM8) and a susceptible cultivar (TM-1) under both normal and \u003cem\u003eV. dahliae\u003c/em\u003e-infected conditions using whole-genome bisulfite sequencing. Our results revealed that a lower overall level of DNA methylation was associated with enhanced VW resistance. We also found that the A-subgenome exhibited a higher methylation level than the D-subgenome, indicating an asymmetric methylation distribution between subgenomes. Furthermore, except for chromosomes A09, D07, D09, and D10, the chromosomal arms consistently showed significantly lower methylation levels than the centromeric regions. Upon \u003cem\u003eV. dahliae\u003c/em\u003e infection, altered DNA methylation patterns predominantly led to reduced gene expression. Analyses of differentially methylated regions (DMRs) and genes (DMGs), combined with gene silencing assays, demonstrated that the RNA-directed DNA methylation (RdDM) pathway plays a central regulatory role in cotton resistance to VW. Key components of this pathway, including Pol IV, Pol V, AGO4, RDR2, and DCL3, were implicated in this process. Moreover, we confirmed that AGO4 interacts with four proteins, including ADH1, to collectively regulate VW resistance. In summary, our study unveils an epigenetic mechanism underlying disease resistance in cotton, providing new insights into the defense response against Verticillium wilt.\u003c/p\u003e","manuscriptTitle":"The landscape of cotton DNA methylation and its epigenetic regulation in Verticillium wilt resistance","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 13:42:06","doi":"10.21203/rs.3.rs-7531123/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"039bc6af-360c-400d-ab18-8d67e465b930","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T08:57:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-01 13:42:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7531123","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7531123","identity":"rs-7531123","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}