Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Mar 10.
Published in final edited form as: Cell Host Microbe. 2021 Feb 5;29(3):425–434.e4. doi: 10.1016/j.chom.2021.01.005

The chromatin remodeling protein BAF60/SWP73A regulates the plant immune receptor NLRs

Chien-Yu Huang 1, Diana Sanchez Rangel 1,2, Xiaobo Qin 1, Christine Bui 1, Ruidong Li 3, Zhenyu Jia 3, Xinping Cui 4, Hailing Jin 1,*
PMCID: PMC7987208  NIHMSID: NIHMS1670099  PMID: 33548199

Summary

In both plant and animal innate immune responses, surveillance of pathogen infection is mediated by membrane-associated receptors and intracellular nucleotide-binding domain & leucine-rich repeat receptors (NLRs). Homeostasis of NLRs is under tight multilayered regulation to avoid over-accumulation or over-activation, which often leads to autoimmune responses that cause detrimental effects on growth and development. How NLRs are regulated epigenetically at the chromatin level remains unclear. Here, we report that SWP73A, an orthologue of the mammalian switch/sucrose nonfermentable (SWI/SNF) chromatin remodeling protein BAF60, suppresses the expression of NLRs either directly by binding to the NLR promoters or indirectly by affecting the alternative splicing of some NLRs through the suppression of Cell Division Cycle 5 (CDC5), a key regulator of RNA splicing. Upon infection, bacteria-induced small RNAs silence SWP73A to activate a group of NLRs and trigger robust immune responses. SWP73A may function as a H3K9me2 reader to enhance transcription suppression.

Graphical Abstract

graphic file with name nihms-1670099-f0001.jpg

eTOC Blurb

NLR-mediated immunity is under precise control to avoid autoimmunity. Huang et al. report a new regulation mechanism in which the chromatin remodeling protein SWP73A suppresses NLRs’ expression directly by transcriptional suppression or indirectly by modulating NLR’s alternative splicing. SWP73A is silenced by bacteria-induced small RNAs to activate NLR expression.

Introduction

Intracellular nucleotide-binding domain and leucine-rich repeat receptors (NLRs) regulate innate immune responses against pathogen infection in both plants and animals (Jones et al., 2016; Zhou and Zhang, 2020). Typically, NLRs contain a central nucleotide-binding domain (NBD) and a C-terminal leucine-rich repeat (LRR) domain. Upon the recognition of pathogen effectors, NLR proteins oligomerize to form an oligomeric “resistosome” structure (Li et al., 2020; Wang et al., 2019), which induces rapid and robust effector-triggered immunity (ETI) (Lolle et al., 2020). Expression and activation of NLRs are precisely regulated at multiple levels, including transcriptional regulation, alternative mRNA splicing, small RNA (sRNA)-mediated post-transcriptional regulation, post-translational modifications, NLR dimerization or oligomerization, and proteasome-mediated degradation (Li et al., 2015; Lolle et al., 2020). This tight regulation is critical because over-accumulation or imbalanced activity of NLRs can lead to autoimmunity and serious fitness costs including reduced growth and development (Cui et al., 2015; Li et al., 2015; Lolle et al., 2020). Furthermore, heteromeric interaction between certain NLR alleles can also trigger autoimmunity, leading to cell death (Chae et al., 2014; Li et al., 2020; Tran et al., 2017).

To balance the trade-off between plant growth and defense, some sRNAs, including microRNA (miRNA) and small interfering RNA (siRNA), target NLRs and plant defense signaling genes, contributing to the precise regulation of plant immunity (Chen et al., 2010; Huang et al., 2019; Katiyar-Agarwal et al., 2007; Katiyar-Agarwal et al., 2006; Li et al., 2012; Shivaprasad et al., 2012). In this study, we identified two Arabidopsis sRNAs, including an miRNA and an siRNA, which were explicitly induced by a bacterium Pseudomonas syringae pv. tomato (Pst) strain carrying the effector, AvrRpt2 (Chellappan et al., 2010; Zhang et al., 2011). Both sRNAs target Arabidopsis SWP73A, an ortholog of the mammalian BRG1-Associated Factor 60 (BAF60). SWP73/BAF60 is a subunit of the SWI/SNF (switch/sucrose non-fermentable) chromatin remodeling complex, which utilizes the energy of ATP hydrolysis for nucleosome positioning on the DNA (Hopfner et al., 2012; Jerzmanowski, 2007). SWI/SNF complexes are well characterized as transcriptional activators but can also physically repress gene expression, depending on their regulatory dynamics (Pulice and Kadoch, 2016; Raab et al., 2015). Chromatin remodeling mediated by SWI/SNF complexes plays a regulatory role in many cellular processes in mammals (Gatchalian et al., 2020). For example, mammalian BAF60 is a transcriptional coactivator with NF-κB and activates pro-inflammatory genes during infection (Tartey et al., 2014). Whether plant BAF60 homologs regulate host innate immunity against pathogen infection is still unknown.

There are two SWP73/BAF60 variants in Arabidopsis, SWP73A, and SW73B. SWP73B functions in leaf and flower development (Sacharowski et al., 2015; Vercruyssen et al., 2014), DNA repair (Campi et al., 2012), and flowering time (Jegu et al., 2014). In contrast, the functions of SWP73A are still unknown. Here, we discovered that, unlike mammalian BAF60 which acts as a positive regulator of gene transcription, plant SWP73A acts as a negative regulator of gene expression and inhibits plant innate immune response to avoid autoimmunity in the absence of pathogens. Upon bacterial infection, SWP73A is suppressed by two bacteria-induced sRNAs, and plant immune responses are activated through the accumulation of a set of NLRs.

Results

Two sRNAs are specifically induced by Pst (AvrPpt2) infection and target SWP73A

From the sRNA profiles of Arabidopsis Col-0 plants infected by bacterium (Pst) DC3000 strains, we identified a set of sRNAs that were specifically induced by the avirulent strain Pst (AvrRpt2) (Zhang et al., 2011). The bacterial effector AvrRpt2 is recognized by the NLR protein RPS2 in Col-0, triggering the ETI response (Bent et al., 1994; Chellappan et al., 2010; Zhang et al., 2011). Two sRNAs, including one miRNA, miR3440, and one siRNA, siRNA-SWP73A, were explicitly induced by Pst (AvrRpt2) but not by the type III secretion system mutant strain, Pst DC3000 hrcC, virulent strain Pst DC3000 which carries an empty vector (EV) or the mock solution (Fig. 1a). In addition, the two sRNAs were not induced by Pst (AvrRpt2) infection in the RPS2 loss-of-function mutant, rps2–101c (Fig. S1a). Thus, the induction of the two sRNAs by Pst (AvrRpt2) is RPS2-dependent. miR3440 was predicted to target the stop codon region of the SWP73A gene, and siRNA-SWP73A targets the 5’ UTR of SWP73A (Fig. S1b). Indeed, the transcript level of SWP73A decreased after Pst (AvrRpt2) infection when both sRNAs were induced (Fig. 1b and c). Transient co-expression of SWP73A mRNA with miR3440 in Nicotiana benthamiana (Nb) leaves resulted in reduced SWP73A protein in comparison to co-expression with the negative control, miR395, confirming that SWP73A cDNA is a real target of miR3440 (Fig. S1c). The other SWP73/BAF60 variant in Arabidopsis, SWP73B (Fig. S2a), was not affected by Pst (AvrRpt2) infection at the transcript expression level (Fig. S2b).

Figure 1. SWP73A-targeting sRNAs, miR3440 and siRNA-SWP73A, are induced by Pst(AvrRpt2) infection.

Figure 1.

Open in a new tab

a. Northern blot analysis of miR3440 and siRNA-SWP73A in Pst (Empty-vector), hrcC Pst, and Pst (AvrRpt2) infected Arabidopsis at 14 hours post infection (hpi). Buffer inoculation was used as a mock control. U6 is the loading control. The relative abundance (RA) of the small RNAs detected is labeled under the U6 panel.

b. Expression level of SWP73A in Arabidopsis at various time points post Pst(AvrRpt2) infection analyzed by qRT-PCR and normalized to Actin2.

c. Northern blot analysis of miR3440 and siRNA-SWP73A in Arabidopsis infected by Pst (AvrRpt2) in a time course corresponding to panel b. U6 is the loading control. The RA of the small RNAs detected is labeled under the U6 panel.

SWP73A negatively regulates plant immune responses against Pst (AvrRpt2)

Because SWP73A is down-regulated upon Pst (AvrRpt2) infection, to characterize the function of SWP73A in plant immunity, we obtained the swp73a T-DNA insertion knockout mutant, which has no obvious vegetative developmental defect as reported before (Fig. 2a) (Sacharowski et al., 2015). The transcript levels of NLR gene RPS2, as well as the Pathogenesis-Related gene 1 (PR1), were elevated in the swp73a mutant (Fig. 2b). Furthermore, swp73a displayed accelerated hypersensitive response (HR) and reduced bacterial growth after Pst (AvrRpt2) infection compared with wild-type (WT) plants (Fig. 2c and d). These results suggest that SWP73A is a negative regulator of plant ETI.

Figure 2. SWP73A suppresses Arabidopsis defense response against Pst(AvrPpt2).

Figure 2.

Open in a new tab

a. Morphological phenotype of SWP73A T-DNA insertion knockout mutant, swp73a and the amiRswp73a/b knockdown double mutant.

b. The expression levels of RPS2 and PR1 in swp73 were analyzed by qRT-PCR and normalized to Actin2 gene. Significant difference is indicated by * (p < 0.01; ANOVA Dunnett’s multiple comparisons test to WT).

c. Accelerated HR response induced by Pst (AvrPpt2) in swp73a and amiRswp73a/b. Buffer inoculation was used as mock control.

d. The SWP73A mutants displayed enhanced resistance to Pst (AvrPpt2). Bacterial growth assay was performed at 0-, and 3-days post pathogen inoculation. Data are means ± SE. Different letters indicate a significant difference between groups (p < 0.01; ANOVA Dunnett’s multiple comparisons test to WT).

e. Morphological phenotype of SWP73A overexpressed plants (SWP73A OE).

f. The expression levels of RPS2 and PR1 in SWP73A OE plants compared to WT were analyzed by qRT-PCR and normalized to Actin2. Significant difference is indicated by * (p < 0.05; ANOVA Dunnett’s multiple comparisons test to WT).

g. Delayed HR response upon Pst (AvrPpt2) infection was observed in the SWP73A OE plants. Buffer inoculation was used as a mock control.

h. The SWP73A OE plants are more susceptible to Pst (AvrRpt2). Significant difference is indicated by * (p < 0.01; ANOVA Dunnett’s multiple comparisons test to WT).

In the swp73a mutant, SWP73B mRNA has a significantly higher expression level (Fig. S2d), suggesting that it has a partial compensatory effect on SWP73A when SWP73A is absent. Therefore, SWP73A and SWP73B double mutants AmiRswp73a/b were generated through silencing SWP73B using an artificial miRNA in the swp73a mutant (Fig. S2e). These plants displayed drastically reduced plant size (Fig. 2a), and elevated levels of RPS2 and PR1 compared to the swp73a single mutant plants (Fig. 2b). The AmiRswp73a/b double mutant plants also showed further accelerated HR and reduced bacterial growth after Pst (AvrRpt2) infection compared to the swp73a mutant (Fig. 2c and d). These characteristics indicate an autoimmune phenotype, which can be caused by the elevated expression of NLRs and PR genes leading to a strong fitness cost. The swp73b mutant has a defect in leaf and flower development and does not produce seeds (Sacharowski et al., 2015). Although the swp73b single mutant is also smaller than WT (Fig. S2f), the expression levels of RPS2 and PR1 exhibited no obvious changes compared to WT (Fig. S2g). Further, there was no difference between Pst (AvrRpt2) growth in WT and swp73b plants (Fig. S2h). Because Arabidopsis SWP73A and SWP73B are associated with the SWI/SNF complex in a mutually exclusive manner (Vercruyssen et al., 2014), SWP73B mainly regulates plant development and is not involved in plant immunity unless SWP73A is knocked out.

To investigate the function of SWP73A and avoid the compensatory effect of SWP73B, we generated CaMV 35S promoter-driven SWP73A-FLAG overexpression (OE) plants (Fig. 2e and S3a). Compared to WT plants, the SWP73A OE plants had slightly curly leaves (Fig. 2e), and significantly lower expression levels of RPS2 and PR1 (Fig. 2f). The SWP73A OE plants also displayed delayed HR and increased bacterial growth after Pst (AvrRpt2) infection compared to WT (Fig. 2g and 2h). All these results demonstrate that plant SWP73A plays an important role in suppressing ETI to prevent autoimmunity.

SWP73A acts as a transcription suppressor of a set of NLRs and plant immunity related genes

SWP73A is one of the core subunits of the SWI/SNF chromatin remodeling complex (Sacharowski et al., 2015; Vercruyssen et al., 2014). To identify the genes regulated by SWP73A, we conducted expression profiling using the Arabidopsis Affymetrix microarray to identify differentially expressed mRNAs between swp73a or SWP73A OE plants and WT. We used a q-value of 0.03 as a cutoff and identified 447 differentially expressed genes in the SWP73A OE versus WT comparison and 9 differentially expressed genes in the swp73a versus WT comparison (Table S1). The small number of differentially expressed genes between swp73a and WT further indicates the compensatory effects of SWP73B in the swp73a mutant background. Among the 447 differentially expressed genes between SWP73A OE and WT plants, 427 genes were down-regulated, and 19 genes were up-regulated (Table S1), which suggested that SWP73A may mostly act as a transcriptional suppressor. Gene ontology (GO) term enrichment analysis showed that 79 genes (18.5%) downregulated by SWP73A were related to biotic stress responses, including plant immune responses, defense responses to bacterium, systemic acquired resistance and the jasmonic acid biosynthetic process (Fig. S3b). Among them, seven NLRs represented 1.6% of the down-regulated genes (Table S1). In comparison, biotic stress-related genes and NLR genes only represent 3.7% and 0.5% of total genes in the Arabidopsis genome, respectively (Mondragon-Palomino and Gaut, 2005), making biotic stress-related genes five-fold enriched and NLRs 3.2 fold enriched in the SWP73A down-regulated genes list. In addition to RPS2, the expression levels of four more NLRs, RPS4, RRS1, ZAR1, and RPP1-like, were experimentally validated by RT-PCR in the SWP73A OE plants and the swp73 single and double mutants (Fig. 3a). All four NLRs exhibit elevated transcript levels in swp73a and amiRswp73a/b plants, and reduced expression levels in SWP73A OE lines, confirming that SWP73A suppresses the expression of a set of NLRs. We also checked another NLR gene, RPM1 (Grant et al., 1995; Lolle et al., 2020), whose response pathway shares some common upstream and downstream components with the signal transduction pathway of RPS2. The expression level of RPM1 had no significant difference among swp73a, WT and the SWP73A overexpression lines (Fig. S3c), which is consistent with the microarray data. The swp73a single mutant, swp73a/b double mutant and SWP73A OE lines showed similar levels of bacterial growth as wild-type plants upon infection of Pst (AvrRpm1) (Fig. S3d). These results support that expression of RPM1 is not regulated by SWP73A. Further, sRNA-mediated regulation of SWP73A was not altered after Pst (AvrRpm1) infection because miR3440 and siRNA-SWP73A were not induced by Pst (AvrRpm1) (Fig. S3e).

Figure 3. SWP73A suppresses the expression of a group of NLRs and negatively regulates Arabidopsis defense response against Pst(AvrRps4).

Figure 3.

Open in a new tab

a. Verification of differentially expressed NLRs identified by microarray analysis by qRT-PCR. Expression level of RPS4, RRS1 ZAR1, and RPP1-like were analyzed by qRT-PCR and normalized to Actin2. Significant difference is indicated by * (p < 0.01; ANOVA Dunnett’s multiple comparisons test to WT).

b. Northern blot analysis of miR3440 and siRNA-SWP73A in Pst (Empty-vector, EV), hrcC Pst, and Pst (AvrRpt2) infected Arabidopsis at 20 hours post infection (hpi). Buffer inoculation was used as a mock control. U6 is the loading control. The relative abundance (RA) of the small RNAs detected is labeled under the U6 panel.

c. Expression level of SWP73A in Arabidopsis at various time points post infection by Pst (AvrRpt2) analyzed by qRT-PCR and normalized to Actin2.

d. Northern blot analysis of miR3440 and siRNA-SWP73A with Arabidopsis infected by Pst (AvrRpt2) in a time course corresponding to panel b. U6 is the loading control. The RA of the small RNA detected is labeled under the U6 panel.

e and f. HR response induced by Pst (AvrRps4) in SWP73 mutants and SWP73 OE plants. Buffer inoculation was used as a mock control.

g. Pst(AvrRps4) growth assay on SWP73 mutants. Data are means ± SE. Significant difference is indicated by * (p < 0.05) or **(p < 0.01; ANOVA Dunnett’s multiple comparisons test to WT).

RPS4 and RRS1 are a divergent pair of NLRs that share the same promoter region. The RPS4 and RRS1 proteins form a complex that recognizes the bacterial effector AvrRps4 and triggers ETI (Le Roux et al., 2015; Sarris et al., 2015). We examined the expression of miR3440 and siRNA-SWP73A in response to Pst (AvrRps4) infection. Both sRNAs were induced by Pst (AvrRps4) but not by Pst (hrcC) or Pst (EV) (Fig. 3b). The expression level of their target gene, SWP73A, descended after Pst (AvrRps4) infection in a manner that corresponded to the time course of the two gradually increasing sRNAs (Fig. 3c, d). Upon infection by Pst (AvrRps4), both the single and double mutants, swp73a and amiRswp73a/b, showed accelerated HR, whereas SWP73A OE plants displayed a delayed HR compared with WT (Fig. 3e and f). As expected, SWP73A OE plants were more susceptible to Pst (AvrRps4), whereas the swp73a and amiRswp73a/b mutants were more resistant (Fig. 3g). Taken together, these results demonstrate that SWP73A also negatively regulates RPS4 and RRS1-mediated ETI.

SWP73A directly binds to the promoters of a group of NLRs to suppress their expression

The SWI/SNF complex components regulate gene expression by modulating nucleosome positioning. Transient expression of YFP-tagged SWP73A in Nb leaves confirmed the nuclear localization of SWP73A (Fig. 4a). We hypothesize that SWP73A regulates the transcription of NLRs and defense-related genes through direct association with their promoters. To identify the target genes directly regulated by SWP73A, we generated a native antibody against the first 200 residues of SWP73A, a region with low similarity with SWP73B (Fig. S2a). This anti-SWP73A antibody is highly specific to SWP73A protein as no signal was detected in the swp73a mutant (Fig. 4b). Using this anti-SWP73A antibody, we performed chromatin immunoprecipitation-sequencing (CHIP-Seq) in WT plants. We identified a total of 2061 peaks representing the potential SWP73A binding sites. When using a peak calling q<0.005 as a cutoff, we found 801 genes with SWP73A binding sites within 1 kb from their transcription start site (TSS) (Table S2). GO enrichment analysis indicates that these SWP73A-binding genes are enriched in biotic stress responses (Fig. S4a). The protein domain enrichment analysis showed that LRR, NB-ARC, and TIR domain are among the top 10 most enriched domains (Fig. S4b). We identified 21 NLRs and 95 biotic stress-related genes that had SWP73A binding peaks in their promoters (Table S2), including RPS2, ZAR1, RPP1-like (Fig. 4c and S4c). However, SWP73A was not found to be associated with the promoter region shared by RPS4 and RRS1. We further validated these results using CHIP-qPCR and confirmed that SWP73A was indeed associated with the promoter and TSS regions of RPS2, ZAR1 and RPP-like genes but not RPS4 and RRS1 (Fig. 4d, e and S4d). The binding of the RPS2 promoter with SWP73A was reduced after infection by Pst (AvrRpt2) (Fig. 4f), which leads to increased expression of RPS2 after Pst(AvrRpt2) infection (Fig. 2b and S4e). These results demonstrate that SWP73A directly binds to the promoters of RPS2, ZAR1, and RPP1-like genes to suppress their expression, whereas RPS4 and RRS1 might be regulated by SWP73A indirectly.

Figure 4. SWP73A suppresses the expression of RPS2 by promoter and TSS occupation but does not regulate RPS4 and RRS1.

Figure 4.

Open in a new tab

a. YFP-SWP73A is co-localized with the DAPI stained nucleus in an N. benthamiana transient expression assay.

b. SWP73A was detected by anti-swp73A antibody in the nuclei isolated from swp73a and WT plants mutants. H3K4me3 was used as a loading control.

c. The promoter and TSS regions of three NLR genes, RPS2, RPS4 and RRS1, were shown to associate with SWP73A by CHIP-seq analysis.

d. Diagrams show the promoter region of RPS2 and RRS1-RPS4. The solid lines and gray boxes indicate the promoter and CDS regions, respectively. ATG indicates the start codon, and TSS represents the transcription start site. Arrows represent the primer sets for CHIP-PCR amplification. RPS2 and RRS1-RPS4 promoter regions, I and II, associated with SWP73A were analyzed with CHIP-qPCR in panel e.

e. CHIP-qPCR analyses were performed with anti-SWP73A antibody in WT or anti-FLAG antibody in SWP73A OE plants with anti-IgG as a negative control. Significant difference is indicated by * (P < 0.05; T-test). The agarose gel analysis of CHIP-PCR amplified bands is shown in Fig. S6d.

f. CHIP-qPCR analysis of RPS2 and RPS4 promoter cross-linked with SWP73A in WT plants infected with Pst (AvrRpt2) (12hpi) or Pst(AvrRps4) (20hpi). Buffer inoculation was used as mock control. Significant difference is indicated by * (P < 0.05; T-test). The agarose gel analysis of CHIP-PCR amplified bands is shown in Fig. S6f.

SWP73A regulates RPS4 and RRS1 expression indirectly via CDC5

In order to determine how SWP73A regulates the expression of RPS4 and RRS1, we performed a Supernode network analysis to identify regulatory genes that connect SWP73A with RPS4 and RRS1 via a systems biology platform, VirtualPlant (http://virtualplant.bio.nyu.edu/)(Katari et al., 2010). CDC5, an R2R3 MYB transcription regulator and an evolutionary conserved spliceosome-associated protein, was identified as a regulatory hub that links SWP73A with RPS4 and RRS1 and three additional biotic stress-related genes identified from our expression profiling dataset (Fig. 5a). CDC5 was identified to be directly regulated by SWP73A in our CHIP-seq analysis (Table S2). Indeed, the CDC5 transcript was down-regulated in the SWP73A OE plants and up-regulated in both the swp73a and amiRswp73a/b mutants (Fig. S5a). CDC5 was reported to regulate the alternative splicing of RPS4, which is important for RPS4 activity (Palma et al., 2007; Zhang and Gassmann, 2007). The cdc5 loss-of-function mutant was more susceptible to Pst (AvrRps4) (Fig. S5b). Direct binding of SWP73A to the promoter of CDC5 was detected by both CHIP-seq and CHIP-qPCR analysis (Fig. 5b, c, and d), and the association was impaired by Pst (AvrRps4) infection (Fig. 5e).

Figure 5. SWP73A regulates CDC5 by directly binding to its promoter region.

Figure 5.

Open in a new tab

a. Supernode network analysis on SWP73A using the systems biology platform VirtualPlant (http://virtualplant.bio.nyu.edu/). CDC5, an R2R3 Myb transcription regulator, is regulated by SWP73A. The genes regulated by CDC5 and suppressed by SWP73A (Table S1) are represented by orange nodes. The biotic stress response genes are shown in red.

b. The promoter and TSS region of CDC5 was found associated with SWP73A by CHIP-seq analysis.

c. Diagrams show the promoter region of CDC5. CDC5 promoter regions, I and II, associated with SWP73A were analyzed by CHIP-qPCR in panel d.

d and e. The CDC5 promoter was cross-linked with SWP73A in WT with or without Pst (AvrRps4) (20hpi) infection. Buffer inoculation was used as a mock control. CHIP was performed using the anti-SWP73A antibody with anti-IgG as a negative control. Significant differences are indicated by * (p-value < 0.05; T-tests). The agarose gel analysis of CHIP-PCR amplified bands is shown in Fig. S17.

Alternative splicing of RPS4 is a critical regulatory step for producing a functional transcript (Zhang and Gassmann, 2007). The dominant functional transcript, TV3, is generated from transcript TV2A by excision of intron III (Fig. S5c). Since SWP73A suppresses the expression of CDC5, SWP73A likely regulates the alternative splicing of RPS4 indirectly through CDC5. We examined the transcript levels of TV2A and TV3 in WT and SWP73A OE plants before and after Pst (AvrRPS4) infection. The transcription level of TV2A was reduced in WT but not in SWP73A OE plants after Pst (AvrRPS4) infection (Fig. S5d). RRS1 also undergoes alternative splicing and generates two transcript variants of RRS1, a full-length functional RRS1.1, and a truncated RRS1.2. RRS1.2 retains the 5th intron and translates a truncated protein without the WRKY domain (Fig. S5c) (Noutoshi et al., 2005). After Pst (AvrRPS4) infection, RRS1.2 expression was decreased in WT but remained in SWP73A OE plants. On the contrary, the functional RPS4 TV3 and RRS1.1 transcripts were induced after Pst (AvrRPS4) infection in WT, but not in the SWP73A OE plants (Fig. S5e). Thus, these results demonstrate that SWP73A suppresses RPS4 and RRS1 expression by regulating their alternative splicing via CDC5.

SWP73A associates with histone marker H3K9me2

Previous CHIP-PCR analysis found that, in the SWP73B silencing mutants, the H3K27me3 histone markers on the FLOWERING LOCUS C promoter were decreased whereas the H3K9AC histone markers increased (Jegu et al., 2014). From the UCSC Genome Browser of histone marker CHIP-seq database (Karolchik et al., 2014; Stroud et al., 2012) of Arabidopsis, we found that RPS2 and CDC5 both have H3K9me2 markers associated with their promoter regions. H3K27me3 and H3K9me2 are transcriptional repression markers in plants (Pfluger and Wagner, 2007; Rosenfeld et al., 2009). H3K9me2 tends to span the entire gene and is correlated with low expression levels (West et al., 2014; Zhou et al., 2010). Co-immunoprecipitation (co-IP) analysis showed that SWP73A was associated with H3K9me2 but not with H3K9Ac (Fig. 6a). The promoter regions of RPS2 and CDC5, which are associated with SWP73A (Fig. 6b), were also associated with H3K9me2 but not with H3K27me3 (Fig 6c, S6a and S6b). The promoter regions of RPP1-like and ZAR1 were also associated with H3K9me2 (Fig. S6c). In Arabidopsis, H3K9me2 is mainly established by Su(var)3–9 family histone methyltransferases, SUVH4/KYP, SUVH5, and SUVH6, which are likely to be functionally redundant (Ebbs et al., 2005; Ebbs and Bender, 2006). To genetically examine whether SWP73A-mediated suppression of gene expression is associated with the histone repression marker H3K9me2, we performed CHIP-qPCR analysis on the triple mutant suvh456, which has impaired H3K9me2. The association between SWP73A and the RPS2 or CDC5 promoter was abolished or largely reduced in the suvh456 mutant (Fig. 6b and c), suggesting that SWP73A binds to chromatin in an H3K9me2-dependent manner. The level of H3K9me2 on promoters of RPS2 and CDC5 was significantly reduced after infection by Pst (AvrRpt2) and Pst (AvrRps4), respectively (Fig. 6d), which reduced SWP73A association and activated the expression of RPS2 and CDC5. In summary, the repression of RPS2 and CDC5 by SWP73A through H3K9me2 is abolished or largely reduced after pathogen infection in order to promote gene transcription and activate plant innate immunity.

Figure 6. SWP73A is associated with the histone marker H3K9me2.

Figure 6.

Open in a new tab

a. SWP73A was found to be associated with H3k9me2 histone markers but not H3K9Ac histone markers by co-IP. Anti-AGO2 antibody was used as a negative control.

b and c. CHIP-qPCR analysis of RPS2 and CDC5 promoters cross-linked with SWP73A (b) and H3K9me2 (c) in WT vs. suvh456. Anti-IgG was used as a negative control. The agarose gel analysis of CHIP-PCR amplified bands is shown in Fig. S6e.

d. CHIP-qPCR analysis of RPS2 and CDC5 promoters cross-linked with H3K9me2 in WT infected by Pst (AvrRpt2) (12hpi) or Pst (AvrRps4) (20hpi) infection. Buffer inoculation was used as a mock control. Anti-IgG was used as a negative control for CHIP analysis.

Significant difference was indicated by * in b, c and d (p-value < 0.05; T-tests). The agarose gel analysis of CHIP-PCR amplified bands is shown in Fig. S6f and S6g.

Discussion

Precise control of NLR expression and homeostasis is essential for plant immune responses. Over-accumulation/activation of NLRs typically causes autoimmunity (McDowell and Simon, 2006; Todesco et al., 2010), whereas insufficient NLR expression can result in higher susceptibility to diseases. Here, we identified a chromatin-remodeling protein, SWP73A, which acts as a transcription suppressor to prevent NLR over-accumulation through both direct and indirect regulation. Upon infection by avirulent bacteria, SWP73A is silenced by two bacterial-induced sRNAs, which leads to the transcription of NLRs, triggering a robust immune response ETI. Furthermore, we discovered that the expression of the other Arabidopsis SWP73/BAF60 variant SWP73B was elevated in swp73a plants and showed a compensatory effect on the function of SWP73A in swp73a to avoid over-accumulation of NLRs. This suggests that the compensatory effect of SWP73B in swp73a mutant could be a mechanism to protect the plant from autoimmunity when there is no pathogen challenge to ensure normal development.

In mammalian immune responses, BAF60 is a transcriptional co-activator and activates the promoters of pro-inflammatory genes in mouse macrophages during innate immune responses against viral or bacterial infection (Tartey et al., 2014). The mammalian SWI/SNF complex “reads” or “shapes” the chromatin landscape in order to epigenetically regulate target genes involved in the transition from myoblasts to myotubes and cardiac development (Gillette and Hill, 2015; Lange et al., 2008). On the contrary, plant BAF60/SWP73 acts mainly as a transcription repressor (Jegu et al., 2014). Here, we discovered that SWP73A associates with the repression marker H3K9me2 and may act as an H3K9me2 reader to potentiate its suppression function on NLRs and other defense signaling proteins. Our work has revealed a new layer of precise regulation of NLRs - epigenetic control at the chromatin level to ensure rapid induction of NLRs only upon bacterial infection and avoid autoimmunity when bacteria are absent.

STAR METHODS

RESOURCE AVAILABILITY

Lead Contact

Further information and requests for resources and reagents should be addressed to the Lead Contact, Hailing Jin (hailingj@ucr.edu)

Materials Availability

All plasmids and plant lines generated in this study are available from the Lead Contact with a completed Materials Transfer Agreement.

Data and Code Availability

Microarray data of SWP73 OE plants compared to WT are available in ELIXIR Core Data Resources with ArrayExpress accession E-MTAB-9308 (https://www.ebi.ac.uk/fg/annotare/). CHIP-Seq data of SWP73A are available in the National Center for Biotechnology Information Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra) (SRA): PRJNA642248.

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Plant Model

All Arabidopsis thaliana genotypes used in this study were in the Columbia wild-type (Col-0, N60000) background. Full information on all genotypes were included in Key Resources Table.

KEY RESOURCES TABLE

REAGENT or RESOURCE SOURCE IDENTIFIER
Antibodies
Rabbit polyclonal anti-AtSWP73A This paper N/A
Mouse monoclonal anti-Tubulin Sigma-Aldrich Cat# T6074, RRID:AB_477582
Rabbit polyclonal to Histone H3 (tri methyl K4) Abcam Cat# ab8580, RRID:AB_306649
Mouse monoclonal to Histone H3 (di methyl K9) Abcam Cat# ab1220, RRID:AB_449854
Rabbit Polyclonal to Histone H3 (tri methyl K27) Millipore Cat# 07-449, RRID:AB_310624
Rabbit polyclonal to Histone H3 (acetyl K9) Abcam Cat# ab10812, RRID:AB_297491
Mouse monoclonal anti-FLAG Sigma-Aldrich Cat# F3165, RRID:AB_25952
Goat anti-mouse IgG-HRP Santa Cruz Biotechnology Cat# sc-2005, RRID:AB_631736
Goat anti-rabbit IgG-HRP Santa Cruz Biotechnology Cat# sc-2030, RRID:AB_631747
Bacterial and Virus Strains
Pst (EV) Innes et al., 1993 N/A
Pst (AvrRpt2) Innes et al., 1993 N/A
Pst (AvrRps4) Hinsch and Staskawicz, 1996 N/A
Pst (hrcC−) Yuan and He, 1996 N/A
Chemicals, Peptides, and Recombinant Proteins
Protease Inhibitor Cocktails Sigma-Aldrich Cat# p9599,
Anti-FLAG M2 Affinity gel Sigma-Aldrich Cat# 200-350-383, RRID:AB_10704031
Protein A Agarose Roche PROTAA-RO
Critical Commercial Assays
NEBNext Ultra II DNA Library Prep Kit New England Biolabs Cat# 7645
Deposited Data
Microarray data This paper E-MTAB-9308; https://www.ebi.ac.uk/fg/annotare/
CHIP-Seq data SRA: PRJNA642248; https://www.ncbi.nlm.nih.gov/sra
Experimental Models: Organisms/Strains
Arabidopsis swp73a knockout mutant NASC ID: CS117257
Arabidopsis rps2–101c mutant Bent et al., 1994 N/A
Arabidopsis cdc5 knockout mutant Palma et al., 2007 N/A
Arabidopsis suvh456 triple mutant Ebbs et al., 2005; Ebbs and Bender, 2006). N/A
Arabidopsis SWP73A overexpression line This paper N/A
Arabidopsis AmiRswp73a/b mutant This paper N/A
Oligonucleotides
Primers for this study, see Table S3 This paper N/A
LNA oligos for siRNA-SWP73A detection:
AT+CTTC+TTCA+TCTT+CTTC+TTCT+AG		 This paper N/A
LNA oligos for miR3440 detection:
GAA+GTG+GAT+GGG+CCA+AGA+AAA		 Chellappan et al., 2010 N/A
Recombinant DNA
Plasmid: pEG202-SWP73ACDS This paper N/A
Plasmid: pEG202-SWP73AcDNA This paper N/A
Plasmid: pEG104-SWP73ACDS This paper N/A
Plasmid: pEG100-miR3440 This paper N/A
Plasmid: pGWB402- AmiRswp73a/b This paper N/A
Software and Algorithms
Robust multiarray analysis Irizarry et al., 2003 http://www.molmine.com/magma/loading/rma.htm
Significant Analysis of Microarray Tusher et al., 2001 https://statweb.stanford.edu/~tibs/SAM/
Bowtie Langmead and Salzberg, 2012 http://bowtie-bio.sourceforge.net/bowtie2/index.shtml
MACS2 Zhang et al., 2008 https://github.com/macs3-project/MACS
ChIPseeker Yu et al., 2015 https://guangchuangyu.github.io/software/ChIPseeker/
IGV Robinson et al., 2011 http://software.broadinstitute.org/software/igv/
ImageJ Schneider et al., 2012 https://imagej.nih.gov/ij/
Open in a new tab

Arabidopsis mutants were used in this study including swp73a knockout mutant (CS117257 from NASC stock), rps2–101c mutant (Bent et al., 1994), cdc5 knockout mutant (Palma et al., 2007), suvh456 triple mutant (Ebbs et al., 2005; Ebbs and Bender, 2006). Wide type of N. benthamiana were used for transient expressed assay.

Plant Growth Conditions

Arabidopsis and N. benthamiana plants were grown in a growth room under short day conditions with a 12-h light/12-h dark photoperiod at 23±1 °C.

Bacterial Strains

Pseudomonas syringae pv. tomato DC3000 bacterial strains were used for analysis including those carrying empty vector pVSP61 (EV) (Innes et al., 1993); pVSP61 plasmid with avirulence gene AvrRpt2 (Innes et al., 1993), or AvrRps4 (Hinsch and Staskawicz, 1996); and hrcC− strain that has a mutation in its type III secretion system (Yuan and He, 1996).

METHOD DETAILS

Generation of Transgenic Plants

To generate the SWP73A OE plant, the SWP73A CDS was cloned into a pEarleyGate (pEG) 202 destination vector by gateway cloning system (Invitrogen). Artificial miRNA to knockdown SWP73B in the swp73a mutant was designed according to WMD3-web miRNA Designer (Schwab et al., 2006). The amiRNA fragment was cloned into the pGWB402 destination vector using the gateway cloning system (Invitrogen). Arabidopsis plants were transformed using the floral dip method with Agrobacterium tumefaciens strain GV3101 carrying the cloned vectors.

Transient Expression Analysis in N. benthamiana

Transient co-expression assays were performed by infiltrating 3-week-old N. benthamiana plants with Agrobacterium GV3101 (OD600=1.0) carrying constructs containing the miR3440 or miR395 precursor (in PEG100) and Agrobacterium (OD600=1.0) containing binary vector with insertion of SWP73A cDNA (pEG202) or CDS (pEG104). The same amount of leaf tissue was collected 48 hours post infiltration and processed to perform western blotting.

RNA Extraction, Northern Blot, and qRT-PCR Analysis

Total RNA was extracted by TRIzol Reagent (Invitrogen) following the manufacturer’s instructions. RNA is separated on a 14% denaturing 8 M urea-PAGE gel then transferred and chemically crosslinked onto a Hybond N+ membrane (GE Healthcare Life Sciences) with N-(3-Dimethylaminopropyl)-N′(3-Dimethylaminopr hydrochloride. Oligonucleotide probes used for miR3440 and siRNA-SWP73A detection were GAA+GTG+GAT+GGG+CCA+AGA+AAA (Chellappan et al., 2010) and AT+CTTC+TTCA+TCTT+CTTC+TTCT+AG, respectively. Oligonucleotide probes end-labeled with γ32P were used to probe sRNAs and exposed to a phosphor imager screen. Relative abundance levels between samples were measured by ImageQuant TL 7.0 software (GE Healthcare Life Sciences). For quantification of relative gene expression, cDNA was synthesized by reverse transcription (RT) with Superscript III (Invitrogen) according the manufacturer’s instructions. Quantitative real-time RT–PCR was performed with SYBR green dye on a CFX detection system (Bio-Rad). The primers for all experiments are listed in Table S3.

Immunoblot

Plant tissue was ground in liquid nitrogen and total proteins were extracted by 1 × SDS sampling buffer. The protein samples were resolved with a 12% SDS–PAGE gel and transferred onto PVDF membranes in a Tris-Glycine transfer buffer. The membrane was blocked with TBS/0.5% (v/v) Tween 20/3% (w/v) fat-free milk power and immunoblotted with appropriate antibodies: monoclonal mouse anti-FLAG (Sigma-Aldrich, F3165, 1:3,000 dilution); monoclonal mouse anti-α tubulin (Sigma-Aldrich, T6074, 1:3,000 dilution); polyclonal rabbit anti-SWP73A (serum containing polyclonal antibodies was produced in rabbits immunized with peptide containing the first 200 amino acids of the SWP73A protein, AbMax Biotechnology Co., Ltd., 1:1,000 dilution); goat anti-mouse IgG-HRP (Santa Cruz Biotechnology, sc-2005, 1:3,000 dilution); and goat anti-rabbit IgG-HRP (Santa Cruz Biotechnology, sc-2030. 1:3,000 dilution). Enhanced chemiluminescence (ECL) reagents (Amersham) were used for detection. Relative abundance levels between samples were measured by ImageJ (Schneider et al., 2012).

Pst Growth Assay

For bacterial growth assays, 4-week-old Arabidopsis plants were infiltrated with a 5 × 105 c.f.u. per ml bacterial suspension by syringe. From each treatment group, 12 leaf discs from 4 plants were collected 3 days post infection. Bacterial titer was determined by counting the colonies on Pseudomonas Agar F (BD Difco) plate with serial dilution and incubation. Three biological repeats were performed with similar results. For infection sample collected for northern and the half leaf HR assay, 1 × 107 c.f.u. per ml bacterial suspension was used. A total of 12 leaves were inoculated for the half leaf HR assay and monitored for the appearance of HR symptoms.

Nuclear Extraction and Immunoprecipitation

Ten grams of three week old leaf tissue was ground to a fine powder in liquid nitrogen and homogenized in lysis buffer (20 mm Tris-HCl, pH 7.4, 25% glycerol, 20 mm KCl, 2 mm EDTA, 2.5 mm MgCl2, 250 mm sucrose, Protease Inhibitor Cocktails[sigma, p9599]) at 4°C for 30 mins. The homogenate was sequentially filtered through a 70-μm nylon mesh. The nuclei were pelleted by centrifugation at 1500 g for 15 min and washed three times with nuclei resuspension buffer (20 mm Tris–HCl, pH 7.4, 25% glycerol, 2.5 mm MgCl2, 0.2% Triton X-100) at 4°C. The nuclei were then resuspended in 2 ml IP binding buffer (20 mm Tris-HCl pH 7.5, 150 mM NaCl,1% NP-40, 2 mM EDTA, 1 mm DTT and Protease Inhibitor Cocktails [sigma, p9599]) and sonicated with 5-sec on and 10-sec off intervals for 10 times to release nuclear proteins. The nuclear proteins solution was then used to perform western blot analysis or for protein co-immunoprecipitation. 1ml of nuclear proteins solution was pre-cleaned with 20 μl protein A agarose beads (Sigma) and mixed with 5 μl of anti-SWP73A and the other with 5 μl of anti-AGO2 antibody as a negative control in 4°C overnight than pulled-down with 20 μl protein A agarose beads by centrifuge in 300g for 5 minutes. The beads were then washed 3 times with washing buffer (20 mm Tris-HCl pH 7.5, 150 mM NaCl, 1 mm DTT, 0.3% Triton X-100, 0.2 mm EDTA, with protease inhibitors). Finally, proteins were eluted with 50 μl of 1XSDS sampling buffer and incubated at 95°C for 10 mins. The co-IP samples were subsequently analyzed with by western blot.

ChIP, ChIP-seq Library Preparation, Sequencing and Data Analysis

Chromatin was isolated from 2g of 3-week-old leaf tissue. Methods for CHIP analysis were adapted from Saleh et al. (2008)(Saleh et al., 2008). After cross-linking to DNA, proteins were subjected to immunoprecipitation using 25 μl of Anti-FLAG M2 Affinity gel (Sigma) or 5 mg anti-SWP73A, anit-H3K9me2 (Abcam, ab1220), or anti-H3k27me3 (Millipore 07–449) antibodies to pull-down with 25 μl protein A Agarose beads (Sigma), according to the manufacturer’s protocol. The percentage of input was calculated using the 2−ΔΔCt method (Schmittgen and Livak, 2008). Shearing of chromatin used for preparing ChIP-seq libraries was conducted by Covaris S220 Focused-ultrasonicator (Covaris) and milliTUBE 1 ml AFA Fiber (Covaris) with standard settings that sheared the chromatin around 200bp. The resulting DNA was using for ChIP-seq libraries that were prepared by the NEBNext Ultra II DNA Library Prep Kit (New England Biolabs, cat. no. 7645) and sequenced (single-end read 150-bp) on a HiSeq 4000 machine (Illumina). Quality control of reads was performed with FASTQC. The reads were then mapped onto the TAIR10 assembly with 2-bp mismatch permission by Bowtie (Langmead and Salzberg, 2012). The Broad peak calling function of MACS2 was used to identify the significantly enriched binding regions (Zhang et al., 2008). Visualization and analysis of genome-wide enrichment profiles were done with IGV (Robinson et al., 2011). Peak annotations including, proximity to genes and overlap on genomic features such as transposons and genes, were assigned using ChIPseeker (Yu et al., 2015).

Microarray Analysis

Microarray data were preprocessed using robust multiarray analysis (RMA) for background adjustment and normalization (Irizarry et al., 2003). Significant Analysis of Microarray (SAM) software was used for differential analysis with 0.03 as FDR cutoff (Tusher et al., 2001).

Subcellular Localization

Three-week-old N. benthamiana plants were infiltrated with Agrobacterium carrying pEG104 with SWP73A CDS after 48 hpi and staining with DAPI. Subcellular localization of fluorescent-tagged proteins was observed by using Leica SP5 confocal microscopy.

QUANTIFICATION AND STATISTICAL ANALYSISSUPPLEMENTAL INFORMATION

Details of data visualization, sample number and statistical analysis used for each dataset can be found in the corresponding figure legend. All plots display means ±SE. Statistic alanalyses were performed by Prism (https://www.graphpad.com/scientific-software/prism/) with ANOVA Dunnett’s multiple comparisons test to WT or with Student’s T-test. P-values from analyses with multiple comparisons were adjusted using methods indicated in figure legends. Significance was indicated by asterisks.

Supplementary Material

1
2

Table S1: Genes are differentially expressed in SWP73A OE plants by microarray analysis. Related to Figure 3.

3

Table S2: Identification of SWP73A associated binding site by MACS2 with broad region calling. Related to Figure 4 and 5.

Highlights.

  • Homeostasis of NLRs is under multilayered regulation to avoid autoimmune responses.

  • BAF60 orthologue SWP73A suppresses the expression of some NLRs directly or indirectly.

  • Expression of SWP73A is silenced by bacteria-induced small RNAs.

  • The transcription suppression of SWP73A functions through H3K9me2.

Acknowledgement

We thank Dr. Judith Bender for providing seeds of suvh456 mutant, Dr. Gloria Coruzzi for helpful discussion on VirtualPlant, and Rachael Hamby for editing the manuscript. This work was supported by grants from the National Institute of Health (R01 GM093008 and R35 GM136379) and the National Science Foundation (IOS-2017314) to H.J., and an AES-CE Award (CA-R-STA-7132-H) awarded to X.C.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Conflict of Interest: None of the co-authors have a conflict of interest to declare.

REFERENCES

  1. Bent AF, Kunkel BN, Dahlbeck D, Brown KL, Schmidt R, Giraudat J, Leung J, and Staskawicz BJ (1994). RPS2 of Arabidopsis thaliana: a leucine-rich repeat class of plant disease resistance genes. Science 265, 1856–1860. [DOI] [PubMed] [Google Scholar]
  2. Campi M, D’Andrea L, Emiliani J, and Casati P (2012). Participation of chromatin-remodeling proteins in the repair of ultraviolet-B-damaged DNA. Plant physiology 158, 981–995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Chae E, Bomblies K, Kim ST, Karelina D, Zaidem M, Ossowski S, Martin-Pizarro C, Laitinen RA, Rowan BA, Tenenboim H, et al. (2014). Species-wide genetic incompatibility analysis identifies immune genes as hot spots of deleterious epistasis. Cell 159, 1341–1351. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Chellappan P, Xia J, Zhou X, Gao S, Zhang X, Coutino G, Vazquez F, Zhang W, and Jin H (2010). siRNAs from miRNA sites mediate DNA methylation of target genes. Nucleic acids research 38, 6883–6894. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chen HM, Chen LT, Patel K, Li YH, Baulcombe DC, and Wu SH (2010). 22-Nucleotide RNAs trigger secondary siRNA biogenesis in plants. Proceedings of the National Academy of Sciences of the United States of America 107, 15269–15274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cui H, Tsuda K, and Parker JE (2015). Effector-triggered immunity: from pathogen perception to robust defense. Annual review of plant biology 66, 487–511. [DOI] [PubMed] [Google Scholar]
  7. Ebbs ML, Bartee L, and Bender J (2005). H3 lysine 9 methylation is maintained on a transcribed inverted repeat by combined action of SUVH6 and SUVH4 methyltransferases. Molecular and cellular biology 25, 10507–10515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Ebbs ML, and Bender J (2006). Locus-specific control of DNA methylation by the Arabidopsis SUVH5 histone methyltransferase. The Plant cell 18, 1166–1176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Gatchalian J, Liao J, Maxwell MB, and Hargreaves DC (2020). Control of Stimulus-Dependent Responses in Macrophages by SWI/SNF Chromatin Remodeling Complexes. Trends in immunology 41, 126–140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Gillette TG, and Hill JA (2015). Readers, writers, and erasers: chromatin as the whiteboard of heart disease. Circulation research 116, 1245–1253. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Grant MR, Godiard L, Straube E, Ashfield T, Lewald J, Sattler A, Innes RW, and Dangl JL (1995). Structure of the Arabidopsis RPM1 gene enabling dual specificity disease resistance. Science 269: 843–846. [DOI] [PubMed] [Google Scholar]
  12. Hinsch M, and Staskawicz B (1996). Identification of a new Arabidopsis disease resistance locus, RPs4, and cloning of the corresponding avirulence gene, avrRps4, from Pseudomonas syringae pv. pisi. Molecular plant-microbe interactions : MPMI 9, 55–61 [DOI] [PubMed] [Google Scholar]
  13. Hopfner KP, Gerhold CB, Lakomek K, and Wollmann P (2012). Swi2/Snf2 remodelers: hybrid views on hybrid molecular machines. Current opinion in structural biology 22, 225–233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Huang CY, Wang H, Hu P, Hamby R, and Jin H (2019). Small RNAs - Big Players in Plant-Microbe Interactions. Cell host & microbe 26, 173–182. [DOI] [PubMed] [Google Scholar]
  15. Innes RW, Bisgrove SR, Smith NM, Bent AF, Staskawicz BJ, and Liu YC (1993). Identification of a disease resistance locus in Arabidopsis that is functionally homologous to the RPG1 locus of soybean. The Plant journal : for cell and molecular biology 4, 813–820. [DOI] [PubMed] [Google Scholar]
  16. Irizarry RA, Ooi SL, Wu Z, and Boeke JD (2003). Use of mixture models in a microarray-based screening procedure for detecting differentially represented yeast mutants. Statistical applications in genetics and molecular biology 2, Article1. [DOI] [PubMed] [Google Scholar]
  17. Jegu T, Latrasse D, Delarue M, Hirt H, Domenichini S, Ariel F, Crespi M, Bergounioux C, Raynaud C, and Benhamed M (2014). The BAF60 subunit of the SWI/SNF chromatin-remodeling complex directly controls the formation of a gene loop at FLOWERING LOCUS C in Arabidopsis. The Plant cell 26, 538–551. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Jerzmanowski A (2007). SWI/SNF chromatin remodeling and linker histones in plants. Biochimica et biophysica acta 1769, 330–345. [DOI] [PubMed] [Google Scholar]
  19. Jones JD, Vance RE, and Dangl JL (2016). Intracellular innate immune surveillance devices in plants and animals. Science 354. [DOI] [PubMed] [Google Scholar]
  20. Karolchik D, Barber GP, Casper J, Clawson H, Cline MS, Diekhans M, Dreszer TR, Fujita PA, Guruvadoo L, Haeussler M, et al. (2014). The UCSC Genome Browser database: 2014 update. Nucleic acids research 42, D764–770. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Katari MS, Nowicki SD, Aceituno FF, Nero D, Kelfer J, Thompson LP, Cabello JM, Davidson RS, Goldberg AP, Shasha DE, et al. (2010). VirtualPlant: a software platform to support systems biology research. Plant physiology 152, 500–515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Katiyar-Agarwal S, Gao S, Vivian-Smith A, and Jin H (2007). A novel class of bacteria-induced small RNAs in Arabidopsis. Genes & development 21, 3123–3134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Katiyar-Agarwal S, Morgan R, Dahlbeck D, Borsani O, Villegas A Jr., Zhu JK, Staskawicz BJ, and Jin H (2006). A pathogen-inducible endogenous siRNA in plant immunity. Proceedings of the National Academy of Sciences of the United States of America 103, 18002–18007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Lange M, Kaynak B, Forster UB, Tonjes M, Fischer JJ, Grimm C, Schlesinger J, Just S, Dunkel I, Krueger T, et al. (2008). Regulation of muscle development by DPF3, a novel histone acetylation and methylation reader of the BAF chromatin remodeling complex. Genes & development 22, 2370–2384. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Langmead B, and Salzberg SL (2012). Fast gapped-read alignment with Bowtie 2. Nature methods 9, 357–359. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Le Roux C, Huet G, Jauneau A, Camborde L, Tremousaygue D, Kraut A, Zhou B, Levaillant M, Adachi H, Yoshioka H, et al. (2015). A receptor pair with an integrated decoy converts pathogen disabling of transcription factors to immunity. Cell 161, 1074–1088. [DOI] [PubMed] [Google Scholar]
  27. Li F, Pignatta D, Bendix C, Brunkard JO, Cohn MM, Tung J, Sun H, Kumar P, and Baker B (2012). MicroRNA regulation of plant innate immune receptors. Proceedings of the National Academy of Sciences of the United States of America 109, 1790–1795. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Li L, Habring A, Wang K, and Weigel D (2020). Atypical Resistance Protein RPW8/HR Triggers Oligomerization of the NLR Immune Receptor RPP7 and Autoimmunity. Cell host & microbe 27, 405–417 e406. [DOI] [PubMed] [Google Scholar]
  29. Li X, Kapos P, and Zhang Y (2015). NLRs in plants. Current opinion in immunology 32, 114–121. [DOI] [PubMed] [Google Scholar]
  30. Lolle S, Stevens D, and Coaker G (2020). Plant NLR-triggered immunity: from receptor activation to downstream signaling. Current opinion in immunology 62, 99–105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. McDowell JM, and Simon SA (2006). Recent insights into R gene evolution. Molecular plant pathology 7, 437–448. [DOI] [PubMed] [Google Scholar]
  32. Mondragon-Palomino M, and Gaut BS (2005). Gene conversion and the evolution of three leucine-rich repeat gene families in Arabidopsis thaliana. Molecular biology and evolution 22, 2444–2456. [DOI] [PubMed] [Google Scholar]
  33. Noutoshi Y, Ito T, Seki M, Nakashita H, Yoshida S, Marco Y, Shirasu K, and Shinozaki K (2005). A single amino acid insertion in the WRKY domain of the Arabidopsis TIR-NBS-LRR-WRKY-type disease resistance protein SLH1 (sensitive to low humidity 1) causes activation of defense responses and hypersensitive cell death. The Plant journal : for cell and molecular biology 43, 873–888. [DOI] [PubMed] [Google Scholar]
  34. Palma K, Zhao Q, Cheng YT, Bi D, Monaghan J, Cheng W, Zhang Y, and Li X (2007). Regulation of plant innate immunity by three proteins in a complex conserved across the plant and animal kingdoms. Genes & development 21, 1484–1493. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Pfluger J, and Wagner D (2007). Histone modifications and dynamic regulation of genome accessibility in plants. Current opinion in plant biology 10, 645–652. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Pulice JL, and Kadoch C (2016). Composition and Function of Mammalian SWI/SNF Chromatin Remodeling Complexes in Human Disease. Cold Spring Harbor symposia on quantitative biology 81, 53–60. [DOI] [PubMed] [Google Scholar]
  37. Raab JR, Resnick S, and Magnuson T (2015). Genome-Wide Transcriptional Regulation Mediated by Biochemically Distinct SWI/SNF Complexes. PLoS genetics 11, e1005748. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Robinson JT, Thorvaldsdottir H, Winckler W, Guttman M, Lander ES, Getz G, and Mesirov JP (2011). Integrative genomics viewer. Nature biotechnology 29, 24–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Rosenfeld JA, Wang Z, Schones DE, Zhao K, DeSalle R, and Zhang MQ (2009). Determination of enriched histone modifications in non-genic portions of the human genome. BMC genomics 10, 143. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Sacharowski SP, Gratkowska DM, Sarnowska EA, Kondrak P, Jancewicz I, Porri A, Bucior E, Rolicka AT, Franzen R, Kowalczyk J, et al. (2015). SWP73 Subunits of Arabidopsis SWI/SNF Chromatin Remodeling Complexes Play Distinct Roles in Leaf and Flower Development. The Plant cell 27, 1889–1906. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Saleh A, Alvarez-Venegas R, and Avramova Z (2008). An efficient chromatin immunoprecipitation (ChIP) protocol for studying histone modifications in Arabidopsis plants. Nature protocols 3, 1018–1025. [DOI] [PubMed] [Google Scholar]
  42. Sarris PF, Duxbury Z, Huh SU, Ma Y, Segonzac C, Sklenar J, Derbyshire P, Cevik V, Rallapalli G, Saucet SB, et al. (2015). A Plant Immune Receptor Detects Pathogen Effectors that Target WRKY Transcription Factors. Cell 161, 1089–1100. [DOI] [PubMed] [Google Scholar]
  43. Schmittgen TD, and Livak KJ (2008). Analyzing real-time PCR data by the comparative C(T) method. Nature protocols 3, 1101–1108. [DOI] [PubMed] [Google Scholar]
  44. Schneider C, Rasband W & Eliceiri K (2012). NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9, 671–675 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Schwab R, Ossowski S, Riester M, Warthmann N, and Weigel D (2006). Highly specific gene silencing by artificial microRNAs in Arabidopsis. The Plant cell 18, 1121–1133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Shivaprasad PV, Chen HM, Patel K, Bond DM, Santos BA, and Baulcombe DC (2012). A microRNA superfamily regulates nucleotide binding site-leucine-rich repeats and other mRNAs. The Plant cell 24, 859–874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Stroud H, Otero S, Desvoyes B, Ramirez-Parra E, Jacobsen SE, and Gutierrez C (2012). Genome-wide analysis of histone H3.1 and H3.3 variants in Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the United States of America 109, 5370–5375. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Tartey S, Matsushita K, Vandenbon A, Ori D, Imamura T, Mino T, Standley DM, Hoffmann JA, Reichhart JM, Akira S, et al. (2014). Akirin2 is critical for inducing inflammatory genes by bridging IkappaB-zeta and the SWI/SNF complex. The EMBO journal 33, 2332–2348. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Todesco M, Balasubramanian S, Hu TT, Traw MB, Horton M, Epple P, Kuhns C, Sureshkumar S, Schwartz C, Lanz C, et al. (2010). Natural allelic variation underlying a major fitness trade-off in Arabidopsis thaliana. Nature 465, 632–636. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Tran DTN, Chung EH, Habring-Muller A, Demar M, Schwab R, Dangl JL, Weigel D, and Chae E (2017). Activation of a Plant NLR Complex through Heteromeric Association with an Autoimmune Risk Variant of Another NLR. Current biology : CB 27, 1148–1160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Tusher VG, Tibshirani R, and Chu G (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences of the United States of America 98, 5116–5121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Yu G, Wang LG, and He QY (2015). ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383. [DOI] [PubMed] [Google Scholar]
  53. Yuan J, and He SY (1996). The Pseudomonas syringae Hrp regulation and secretion system controls the production and secretion of multiple extracellular proteins. Journal of bacteriology 178, 6399–6402. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Vercruyssen L, Verkest A, Gonzalez N, Heyndrickx KS, Eeckhout D, Han SK, Jegu T, Archacki R, Van Leene J, Andriankaja M, et al. (2014). ANGUSTIFOLIA3 binds to SWI/SNF chromatin remodeling complexes to regulate transcription during Arabidopsis leaf development. The Plant cell 26, 210–229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Wang J, Hu M, Wang J, Qi J, Han Z, Wang G, Qi Y, Wang HW, Zhou JM, and Chai J (2019). Reconstitution and structure of a plant NLR resistosome conferring immunity. Science 364. [DOI] [PubMed] [Google Scholar]
  56. West PT, Li Q, Ji L, Eichten SR, Song J, Vaughn MW, Schmitz RJ, and Springer NM (2014). Genomic distribution of H3K9me2 and DNA methylation in a maize genome. PloS one 9, e105267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, et al. (2008). Model-based analysis of ChIP-Seq (MACS). Genome biology 9, R137. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Zhang W, Gao S, Zhou X, Chellappan P, Chen Z, Zhou X, Zhang X, Fromuth N, Coutino G, Coffey M, et al. (2011). Bacteria-responsive microRNAs regulate plant innate immunity by modulating plant hormone networks. Plant molecular biology 75, 93–105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Zhang XC, and Gassmann W (2007). Alternative splicing and mRNA levels of the disease resistance gene RPS4 are induced during defense responses. Plant physiology 145, 1577–1587. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Zhou J, Wang X, He K, Charron JB, Elling AA, and Deng XW (2010). Genome-wide profiling of histone H3 lysine 9 acetylation and dimethylation in Arabidopsis reveals correlation between multiple histone marks and gene expression. Plant molecular biology 72, 585–595. [DOI] [PubMed] [Google Scholar]
  61. Zhou JM, and Zhang Y (2020). Plant Immunity: Danger Perception and Signaling. Cell 181, 978–989. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1670099-supplement-1.pdf (2MB, pdf)
2

Table S1: Genes are differentially expressed in SWP73A OE plants by microarray analysis. Related to Figure 3.

NIHMS1670099-supplement-2.xlsx (40.6KB, xlsx)
3

Table S2: Identification of SWP73A associated binding site by MACS2 with broad region calling. Related to Figure 4 and 5.

NIHMS1670099-supplement-3.xlsx (84.1KB, xlsx)

Data Availability Statement

Microarray data of SWP73 OE plants compared to WT are available in ELIXIR Core Data Resources with ArrayExpress accession E-MTAB-9308 (https://www.ebi.ac.uk/fg/annotare/). CHIP-Seq data of SWP73A are available in the National Center for Biotechnology Information Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra) (SRA): PRJNA642248.

RESOURCES