Plants are permanently exposed to microbes including pathogens and rely on potent active immune responses to control infections. The first layer of the plant immune system involves the recognition of pathogen- or microbe-associated molecular patterns (PAMPs or MAMPs), which are sensed by surface-localized pattern-recognition receptors (PRRs) (Couto and Zipfel, 2016). Plant PRRs are composed of receptor-like kinases (RLKs) and receptor-like proteins (RLPs), which are structurally and functionally analogous to animal Toll-like receptors (TLRs) (Boutrot and Zipfel, 2017). Flagellin Sensing 2 (FLS2) is a well-characterized RLK PRR, which recognizes a conserved 22 amino acids epitope from the N-terminal part of the bacterial flagellin, named flg22 (Boller and Felix, 2009). Upon ligand binding, FLS2 initiates a complex phosphorylation cascade at the PRR complex that leads to early signalling events, which include production of reactive oxygen species (ROS), activation of mitogen-activated protein kinases (MAPKs) and differential expression of thousands of genes, which are in part regulated by WRKY transcription factors (TFs) (Navarro et al., 2004; Zipfel et al., 2004; Birkenbihl et al., 2017). To enable disease, pathogens secrete effectors that suppress PTI. For instance, the Gram-negative hemibiotrophic pathogenic bacterium Pseudomonas syringae pv. tomato strain DC3000 (Pto DC3000) injects 36 type-III effectors into plant cells to dampen PTI (Wei et al., 2015). Plants have evolved disease resistance (R) proteins that can perceive the presence of pathogen effectors and trigger a host counter-counter defence (Monteiro and Nishimura, 2018). Most R proteins belong to the nucleotide binding (NB) leucine-rich repeat (LRR) NLR superfamily, which is also present in animals (Jones et al., 2016). Plant NLRs contain N-terminal coiled-coil (CC) or Toll-interleukine (TIR) domains, a central NB domain and a C-terminal LRR, and are thus referred to as CNLs or TNLs, respectively (Monteiro and Nishimura, 2018). These immune receptors can sense, directly or indirectly, pathogen effectors and mount effector-triggered immunity (ETI), a potent immune response that significantly overlaps with PTI, although with a stronger amplitude (Jones et al., 2016; Thomma et al., 2011). However, very little is known about the functional relevance of NLRs in PTI and/or basal resistance towards phytopathogens (Roth et al., 2017).

Rapid and robust activation of plant immune responses is crucial to limit the spread and multiplication of phytopathogens. On the other hand, their sustained induction often leads to cell death and developmental defects. For instance, the constitutive expression of NLRs often triggers ectopic cell death (Oldroyd and Staskawicz, 1998; Zhang et al., 2004; Swiderski et al., 2009; Bernoux et al., 2011; Nishimura et al., 2017). A tight control of both plant immune receptors and downstream signalling factors is therefore crucial and involves multi-layered transcriptional, post-transcriptional and post-translational regulatory mechanisms (Zipfel et al., 2004; Halter and Navarro, 2015; van Wersch et al., 2020; Deleris et al., 2016). The transcriptional control of defence genes by DNA methylation and demethylation has emerged as a central regulatory process of the plant immune system (López et al., 2011; Yu et al., 2013; Dowen et al., 2012; López Sánchez et al., 2016; Le et al., 2014; Deleris et al., 2016; Kong et al., 2020).

DNA methylation is an epigenetic mark that negatively regulates the transcription and transposition of transposable elements (TEs). It can also trigger transcriptional silencing of some genes carrying TEs/repeats in their vicinity (Matzke and Mosher, 2014). Homeostasis of DNA methylation relies on the equilibrium between methylation and active demethylation pathways, and has been extensively studied in Arabidopsis thaliana. In this model organism, DNA methylation is established by the RNA-directed DNA methylation (RdDM) pathway, which is directed by short interfering RNAs (siRNAs) (Matzke and Mosher, 2014). These siRNAs are mainly produced from PolIV-dependent RNAs (P4RNAs) that are converted into double-stranded RNAs (dsRNAs) by RNA-DEPENDENT RNA POLYMERASE 2 (RDR2) (Matzke and Mosher, 2014; Blevins et al., 2015; Zhai et al., 2015; Yang et al., 2016). The resulting dsRNAs are predominantly processed by DICER-LIKE 3 (DCL3) into 23–24 siRNAs, but additionally, in some instances, by DCL2 and DCL4 into 22 nt and 21 nt siRNAs, respectively, which are all competent for RdDM (Xie et al., 2004; Matzke and Mosher, 2014; Panda et al., 2020). These siRNAs further direct ARGONAUTE 4 (AGO4) to TEs/repeats through base pairing with transcripts generated by Pol V (Zilberman et al., 2004; Chan et al., 2004; Qi et al., 2006; Wierzbicki et al., 2009). AGO4 then binds to DNA targets and recruits the de novo methyltransferase DOMAIN REARRANGED METHYLTRANSFERASE 2 (DRM2) that catalyses methylation in all cytosine sequence contexts (CG, CHG and CHH, where H is any nucleotide but not G) (Cao and Jacobsen, 2002; Cao et al., 2003; Lahmy et al., 2016). During DNA replication, symmetric CG and CHG methylations are maintained by METHYLTRANSFERASE 1 (MET1) and CHROMOMETHYLASE 3 (CMT3), respectively, while asymmetric CHH methylation is either actively perpetuated by RdDM or maintained by a siRNA-independent process mediated by CMT2 (Cao and Jacobsen, 2002; Matzke and Mosher, 2014; Stroud et al., 2014). On the other hand, Arabidopsis encodes four active demethylases with 5-methylcytosine DNA glycosylase/lyase activities, namely DEMETER (DME), DME-Like 1 (DML1)/ROS1 (Repressor of Silencing 1), DML2 and DML3 (Zhang et al., 2018). Both ROS1 and DME actively remove DNA methylation in all methylated cytosine contexts through a base excision repair (BER) mechanism (Gong et al., 2002; Mok et al., 2010). ROS1 is the active demethylase that has been the most characterized in vegetative tissues (Zhang et al., 2018). Mechanistically, ROS1 prunes siRNA-dependent or -independent DNA methylation at thousands of loci and this process often limits the spreading of DNA methylation at TE/repeat boundaries (Tang et al., 2016). Importantly, ROS1-directed removal of DNA methylation at specific promoters is critical to ensure a proper expression of genes required for developmental or abiotic stress responses (Yamamuro et al., 2014; Gong et al., 2002; Kim et al., 2019).

Several studies have unveiled a major role for DNA methylation in susceptibility against non-viral phytopathogens. For examples, DNA methylation-defective mutants of Arabidopsis are more resistant to Pto DC3000 and the obligate biotrophic oomycete pathogen Hyaloperonospora arabidopsidis (Pavet et al., 2006; Yu et al., 2013; Dowen et al., 2012; López Sánchez et al., 2016). Conversely, ros1 mutants display enhanced susceptibility towards Pto DC3000 and Hyaloperonospora arabidopsidis (Yu et al., 2013; López Sánchez et al., 2016), indicating that ROS1 promotes basal resistance against those pathogens. Furthermore, ROS1, DML2, DML3, and DME act cooperatively to orchestrate resistance towards Fusarium oxysporum, a devastating hemibiotrophic vascular fungal pathogen infecting a wide range of economically important crops (Le et al., 2014; Schumann et al., 2019). Altogether, these studies suggest that immune-responsive genes are likely to be regulated by DNA methylation and/or demethylation, which has been demonstrated at a subset of pathogen-responsive genes (Yu et al., 2013; Le et al., 2014; López Sánchez et al., 2016; Schumann et al., 2019; Kong et al., 2020). These findings also suggest that demethylation of defence gene promoters might ensure the DNA/chromatin binding of TFs during pathogen infection and/or elicitation, although this hypothesis has never been tested experimentally.

Here, we have characterized the Arabidopsis demethylase ROS1 in the context of antibacterial immunity. We first demonstrate that ROS1 positively regulates basal resistance against Pto DC3000 by antagonizing RdDM activity. Consistent with this observation, we find that the TNL RESISTANCE METHYLATED GENE 1 (RMG1) contributes to basal resistance against Pto DC3000, and that ROS1-directed suppression of RdDM at RMG1 promoter ensures a proper induction of this gene during PTI. Furthermore, we retrieve the whole set of flg22-responsive genes that are controlled by ROS1 and show that PAMP-triggered inducibility at two ROS1 targets, namely RMG1 and RLP43, depends on the cis-effect of demethylation at their promoters. Furthermore, ROS1-directed demethylation at a specific sequence of the RLP43 promoter, which carries a functional ‘W-box’ WRKY-binding site, is critical for the DNA binding of PAMP-responsive WRKY TFs. Overall, this study reveals the extent to which ROS1 orchestrates Arabidopsis transcriptional immune reprogramming and unveils a crucial role for this demethylase in the regulation of WRKY-DNA binding at immune-responsive promoters.

Active demethylation has emerged as a key regulatory mechanism of plant disease resistance. For examples, an enhanced susceptibility towards Pto DC3000 and Hyaloperonospora arabidopsidis was reported in ros1 mutants (Yu et al., 2013; López Sánchez et al., 2016). A heightened disease susceptibility towards Fusarium oxysporum was also found in the Arabidopsis ros1 dml2 dml3 (rdd) mutant, and this phenotype was exacerbated by knocking-down DME in this background (Le et al., 2014; Schumann et al., 2019). Although these data indicate that demethylases promote basal resistance against unrelated phytopathogens, very little is known about the mechanisms involved in this process. Here, we showed that Arabidopsis ros1 mutants exhibited enhanced growth and vascular propagation of Pto DC3000, two phenotypes which were almost fully rescued in ros1dcl23-infected mutants (Figure 1). Therefore, ROS1 promotes basal resistance against Pto DC3000 mainly by antagonizing DCL2 and/or DCL3 functions.

We further found that the reprogramming of more than 2000 genes was altered in ros1-elicited mutants, supporting a major role for ROS1 in controlling PAMP-triggered gene expression changes. Among these genes, only ~10% exhibited hyperDMRs in ros1 mutants and were thus potentially directly regulated by ROS1. This is congruent with a previous transcriptome study conducted in ros1 mutants infected with Hyaloperonospora arabidopsidis (López Sánchez et al., 2016) and suggests that the majority of biotic stress-responsive genes are ROS1 secondary targets. This phenomenon is likely explained by the fact that ROS1 directly controls the expression of a subset of central regulatory components of immune responses, such as plant immune receptors, which have large impact on downstream signalling events.

In addition, we found that a similar proportion of ROS1 putative primary targets were up-regulated (102 genes) and down-regulated (115 genes) in response to flg22. These results suggest that ROS1 is equally capable of promoting the induction and repression of genes during flg22 elicitation. Some of these repressed targets might act as plant defence repressors or, alternatively, as modulators of plant developmental or physiological processes, possibly to redirect resources towards immunity and away from growth. It is noteworthy that the role of active demethylation in promoting repression of genes has previously been reported in the context of fruit ripening, whereby the tomato ROS1 homolog SlDML2 was found to repress hundreds of ripening-related genes (Lang et al., 2017). Further studies are needed to determine whether this feature of active demethylases could occur in the context of other biological processes.

We also performed a detailed analysis of the flg22-induced ROS1 putative primary targets. Most of these genes exhibited hypermethylation at their promoters, an effect that was almost abolished in ros1dcl23 mutants (Figure 3C and D). These data suggest that ROS1 antagonizes RdDM at these promoters, presumably to facilitate their transcriptional activation during plant defence signalling. Consistent with this hypothesis, we found that the impaired induction of RMG1, RBA1 and of the phosphoglycerate mutase genes observed in ros1-elicited plants was either fully or partially restored in ros1dcl23-elicited mutants (Figures 2 and 3). This was, however, not the case of RLP43, which remained fully silenced in ros1dcl23-elicited mutants, a phenotype that was associated with a moderate gain of 21 nt siRNAs at the RLP43 hyperDMR in ros1dcl23 mutants (Figure 3, Figure 3—figure supplement 3). This observation suggests that DCL4 and/or DCL1 might compensate for the lack of DCL2 and DCL3 in the ros1 mutants to maintain RdDM at the RLP43 promoter. This would be consistent with recent findings showing that PolIV-dependent 21nt siRNA species, which are produced by DCL4, can trigger RdDM (Panda et al., 2020). The longer RNAs detected at the RLP43 hyperDMR in the ros1dcl23 mutants (Figure 3, Figure 3—figure supplement 3), and which exhibited classical features of P4RNAs (Figure 3—figure supplement 3; Blevins et al., 2015; Zhai et al., 2015), might also contribute to this phenomenon. The latter hypothesis is supported by the fact that P4RNA species can efficiently direct DNA methylation at a large set of RdDM targets in the absence of DCL-dependent siRNAs (Yang et al., 2016). Alternatively, and/or additionally, some yet-unknown RNA-independent mechanism(s) might ensure the maintenance of DNA methylation at this locus in the absence of ROS1, DCL2, and DCL3 factors.

Interestingly, our work demonstrated that the dominance of ROS1 over RdDM at two immune-responsive gene promoters can be alleviated by artificially producing siRNAs against these genomic regions (Figure 6). In particular, we showed that the stable expression of an inverted repeat transgene bearing sequence homologies to the ROS1 targeted regions of RMG1 and RLP43 promoters, resulted in their hypermethylation along with a compromised flg22-triggered induction of these genes (Figure 6). Furthermore, we found that these transgenic lines exhibited an enhanced susceptibility towards Pto DC3000, indicating that the silencing of these genes is sufficient to dampen basal resistance (Figure 6). We are anticipating that this approach will be extensively used in the future to assess the regulatory function of demethylases over any target(s) of interest. This strategy could also be exploited to transmit, and possibly maintain, epialleles at specific demethylase target(s), and perhaps even when the transgene is segregated away (if the intrinsic features of the targeted sequences are prone to form stable epialleles) (Catoni et al., 2017; Li et al., 2020). Such an epi-editing strategy would be particularly relevant in crops to prevent the unwanted expression of demethylase target(s) having negative effects on desirable trait(s).

Although the inactivation of demethylases is known to dampen resistance towards unrelated phytopathogens (Yu et al., 2013; López Sánchez et al., 2016; Le et al., 2014; Schumann et al., 2019), the functional relevance of individual demethylase targets in basal resistance remains ill-defined. Here, we have conducted an in-depth characterization of the ROS1 target RMG1, an orphan TNL gene containing two remnant RC/Helitron TEs in its promoter. The AtREP4 distal repeat was found highly methylated in all cytosine sequence contexts, a methylation pattern that was required to maintain a low basal expression of this gene (possibly to prevent trade-off effects caused by its overexpression) (Yu et al., 2013; Deleris et al., 2016). The AtREP11 proximal repeat was, conversely, unmethylated in Col-0 plants and gained high levels of methylation in ros1 mutants, particularly at the 3’ boundary of the AtREP11 repeat, which contains W-box cis-elements and displays DNA binding of WRKY TFs (Figure 2, Figure 4—figure supplement 4; Yu et al., 2013). Significantly, both the accumulation of siRNAs and the hypermethylation observed in ros1 mutant at this promoter region were found abolished in the ros1dcl23 mutant background (Figure 2). Furthermore, a full restoration of flg22-triggered inducibility of RMG1 was observed in ros1dcl23-elicited mutants, indicating that siRNAs limit the induction of this gene in the ros1-elicited mutant background (Figure 2). Importantly, we found that mutations in RMG1 enhanced disease susceptibility towards Pto DC3000, highlighting a major role of this TNL in basal resistance towards this bacterium (Figure 2). These data support previous findings showing that NLRs are not solely required for race-specific resistance but can also contribute to basal resistance, possibly by orchestrating PTI signalling and/or by mounting a weak ETI response through the recognition of virulence factors (Boccara et al., 2014; Canto-Pastor et al., 2019; Roth et al., 2017). Although RMG1 is a functional ROS1 target, the concomitant silencing of several other defence genes in ros1 must additionally account for the increased disease susceptibility phenotypes observed in this mutant background.

DNA methylation has been shown to block DNA binding of some TFs in vitro (Watt and Molloy, 1988; Iguchi-Ariga and Schaffner, 1989; Tate and Bird, 1993; O'Malley et al., 2016). However, recent mechanistic studies at the promoters and/or enhancers of mammalian genes have highlighted a more complex picture, whereby TFs are either sensitive to DNA methylation or, alternatively, bind to methylated regions and in turn trigger their demethylation (Domcke et al., 2015; Schübeler, 2015; Yin et al., 2017). In human cells, earlier studies suggested a role for active demethylation in modulating the chromatin accessibility of TFs in the context of bacterial elicitation or infection (Pacis et al., 2015). For example, a large set of genomic regions were found demethylated in human dendritic cells infected with Mycobacterium tuberculosis, leading to chromatin relaxation at enhancers carrying stress-responsive cis-elements (Pacis et al., 2015). Nevertheless, a recent study suggests that demethylation at these immune-responsive enhancers is unlikely required for the chromatin-based recruitment of TFs in these conditions, but is more probably occurring as a consequence of TFs binding at these genomic regions (Pacis et al., 2019). However, the exact role that demethylation could play in the DNA/chromatin accessibility for TFs remains ambiguous, because this work has not been conducted in human cells lacking individual demethylases. Here, we have exploited the genetically tractable model organism Arabidopsis thaliana to investigate this question at immune-responsive gene promoters. Interestingly, we found that the flg22-induced ROS1 primary targets exhibit an over-representation of in vitro WRKY TFs binding at discrete demethylated promoter regions (Figure 4, Figure 4—figure supplement 1). Some of these W-box elements are likely functional because in vivo recruitment of WRKYs was additionally observed at a subset of promoter regions in flg22-treated seedlings (Figure 4, Figure 4—figure supplement 5; Birkenbihl et al., 2017). By using a transcriptional fusion reporter approach, we also provided evidence that a single W-box element, centred in the RLP43 promoter region that is demethylated by ROS1, was essential for flg22-triggered induction of this gene (Figure 4). Furthermore, we demonstrated that ROS1-directed demethylation of this RLP43 promoter region facilitated DNA binding of the PAMP-responsive AtWRKY40 and AtWRKY18 (Figure 5, Figure 5—figure supplement 1; Birkenbihl et al., 2017). Based on these findings, we propose that ROS1 cis-regulates a subset of defence genes by ensuring binding of WRKY TFs at promoter-regulatory regions, thereby allowing their rapid and pervasive transcription during PTI. Consistent with this cis-effect model, we observed a compromised flg22-triggered inducibility of RLP43 and RMG1 by forcing methylation at discrete promoter-regulatory regions, which are normally demethylated by ROS1, and that carry W-box elements (Figure 4, Figure 6, Figure 6—figure supplement 1). ROS1-directed demethylation of defence gene promoters therefore likely provides a chromatin environment that is permissive for WRKY TFs binding, rendering these genes poised for transcriptional activation during plant defence signalling. It is noteworthy that the proposed mechanism might also hold true for other TF families, which exhibit in vitro binding at the demethylated promoter regions of flg22-induced ROS1 targets (Figure 4—figure supplement 1). Furthermore, this phenomenon might contribute to the down-regulation of genes during PTI, by facilitating the recruitment of repressive TFs at their promoters. Consistent with this hypothesis, different classes of TFs were found to preferentially bind to demethylated promoter regions of a subset of flg22-repressed ROS1 targets (Figure 4—figure supplement 2).

Plants and animals have evolved sophisticated epigenetic reprogramming prior and after fertilization. In mammals, two waves of global demethylation and remethylation occur during germ cell development and embryogenesis, which tightly control transgenerational epigenetic inheritance (Heard and Martienssen, 2014). In plants, epigenetic reprogramming during sexual reproduction is less robust than in mammals, rendering epiallele transmission more possible through generations. This is supported by the description of multiple artificial and natural epialleles, recovered from various plant species (Weigel and Colot, 2012; Heard and Martienssen, 2014). In Arabidopsis, the dynamics and mechanisms of epigenetic reprogramming have been extensively characterized during the last decade. While high levels of CG methylation are observed in male meiocytes, microspores, and sperm cells, a substantial erasure of CHH methylation occurs in the male germline (Calarco et al., 2012; Ibarra et al., 2012; Walker et al., 2018), which is regained during embryogenesis through RdDM (Bouyer et al., 2017; Kawakatsu et al., 2017). The latter phenomenon is accompanied by a restoration of active demethylation, which orchestrates removal of DNA methylation at incoming TEs/repeats and imprinted genes that display CG hypermethylation in the sperm cells, as a result of ROS1/DMLs repression in these cell types. Similarly, ROS1/DMLs might restore demethylation at defence gene promoters in the embryo, notably to ensure the reestablishment of poised W-box elements in the offspring (Deleris et al., 2016). Conversely, enhanced accumulation of endogenous siRNAs at these regulatory sequences is predicted to overcome demethylase reprogramming, as observed upon artificial production of siRNAs against RMG1 and RLP43 promoter regions carrying W-box cis-elements (Figure 3, Figure 6, Figure 6—figure supplement 1), and would likewise favour epiallele formation. Investigating whether such hypothetical mechanism could occur in nature and contribute to the emergence of immune-responsive expression variants will be essential to unravel the mechanisms by which environmental constraints drive the selection of new phenotypes during plant evolution and adaptation.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for all main figures and for figure supplements. Sequencing data have been deposited in SRA under the accession code SRP133028.

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Author details

1. Thierry Halter

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Funding acquisition, Validation, Investigation, Visualization, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4050-5981

2. Jingyu Wang

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Funding acquisition, Validation, Investigation

   Competing interests

   No competing interests declared

3. Delase Amesefe

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Software, Formal analysis, Investigation, Visualization, Writing - review and editing

   Competing interests

   No competing interests declared

4. Emmanuelle Lastrucci

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Software, Formal analysis, Investigation

   Competing interests

   No competing interests declared

5. Magali Charvin

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Validation, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1165-4336

6. Meenu Singla Rastogi

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Funding acquisition, Validation, Investigation

   Competing interests

   No competing interests declared

7. Lionel Navarro

   Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Université de recherche Paris, Sciences & Lettres (PSL), Paris, France

   Contribution

   Conceptualization, Supervision, Funding acquisition, Project administration, Writing -original draft, review and editing

   For correspondence

   lionel.navarro@ens.psl.eu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1083-9478

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