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Occupancy-based mechanism is the chief mode of ROS1 function in preventing DNA hypermethylation

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Abstract

DNA demethylation is essential for maintaining genome-wide DNA methylation balance. Despite the substantial risk to genome stability, the prevailing paradigm posits that the Arabidopsis demethylase ROS1 prevents genome-wide DNA hypermethylation in vivo mainly through its 5-methylcytosine DNA glycosylase/lyase activity. Here we challenge this paradigm by demonstrating that ROS1, through its occupancy, drives extensive passive demethylation independent of its glycosylase/lyase activity and maintains hypomethylation primarily by preventing de novo DNA methylation. This occupancy-based mechanism eliminates the need for genome-wide base excision for active demethylation, thereby minimizing threats to genomic fidelity and stability. Beyond its role in demethylation, ROS1 also functions as a key marker and regulator of chromatin accessibility. This regulation operates in both DNA methylation-dependent and -independent contexts, with ROS1 acting as either a reserve or active protector of accessible chromatin, depending on the functional state of DNA methylation systems. Our findings redefine the diverse roles of ROS1 in DNA methylation regulation and chromatin accessibility, highlighting their intricate interplay.

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Fig. 1: ROS1 occupancy varies across tissues and genotypes in correlation with chromatin accessibility changes.
Fig. 2: N- and C-terminal domains are essential for ROS1 binding to accessible chromatin.
Fig. 3: Relationship between ROS1 occupancy, RdDM recruitment and DNA methylation.
Fig. 4: ROS1 occupancy mediates passive DNA demethylation independent of glycosylase/lyase activity.
Fig. 5: ROS1 maintains accessible chromatin independently and redundancy with GCN5.
Fig. 6: ROS1 serves as a reserve protector of accessible chromatin at specific genomic regions.
Fig. 7: ROS1 regulates chromatin accessibility in both DNA methylation-dependent and independent contexts.

Data availability

All sequence data generated in this study have been deposited in National Center for Biotechnology Information Gene Expression Omnibus under the accession number GSE282076. All accessions of published data used in this study are provided in Supplementary Table 1f. All data supporting the findings of this study are available within the paper and its supporting information. Source data are provided with this paper.

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (2023YFF1000700 to L.Z.), the National Natural Science Foundation of China (32400476 to L.D., 32370636 and 32222063 to L.Z., 31930032 to J.S., and 32188102 to J.-K.Z.), the National Key Research and Development Program of China (2021YFA1300404 to J.-K.Z.), the Fundamental Research Funds for the Central Universities (2662025YLQD004 to L.D.), and Shenzhen Science and Technology Program (KQTD20240729102038044 to J.-K.Z.). We thank the bioinformatics computing platform at National Key Laboratory of Crop Genetic Improvement in Huazhong Agricultural University.

Author information

Author notes

  1. These authors contributed equally: Li Deng, Guangfeng Zhu, Wenying Zhong, Zhibo Jia.

Authors and Affiliations

  1. National Key Laboratory of Crop Genetic Improvement, National Engineering Research Center of Rapeseed, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China

    Li Deng, Guangfeng Zhu, Wenying Zhong, Zhibo Jia, Qiangwei Zhou, Minyan Zhang, Zhixin Si, Qing Zhang, Guoliang Li, Jinxiong Shen & Lun Zhao

  2. Institute of Advanced Biotechnology and School of Medicine, Southern University of Science and Technology, Shenzhen, China

    Yafeng Liang & Jian-Kang Zhu

  3. Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China

    Xuan Du

  4. Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China

    Yanfei Mao

  5. Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, China

    Jian Wu

Authors
  1. Li Deng
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  2. Guangfeng Zhu
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Contributions

Conception and design, L.Z. and J.-K.Z.; material and data generation, G.Z., L.Z. and Z.J., with the assistance of M.Z., Z.S., Q. Zhang, Y.L., X.D. and Y.M.; bioinformatics analysis, W.Z. and L.D., with the assistance of Q. Zhou, J.S., J.W. and G.L.; data interpretation and paper writing, L.Z., L.D., G.Z., W.Z. and J.-K.Z.

Corresponding authors

Correspondence to Jian-Kang Zhu or Lun Zhao.

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Extended data

Extended Data Fig. 1 Identification of the genome-wide binding sites of ROS1 and its occupancy pattern.

a, Comparison of signal-to-noise ratio based on FRiP for ROS1 ChIP-seq datasets generated by the indicated methods. The proROS1::ROS1-Flag/ros1-4 transgenic plants were used. rChIP, regular ChIP-seq; eChIP, enhanced ChIP-seq; aChIP, advanced ChIP-seq. FRiP, fraction of reads in peaks. The dashed line represents the 30% FRiP threshold. b, Distribution of normalized ROS1 peak intensities generated by the indicated methods. Flag Col-0 ChIP-seq served as the control. The ChIP-seq signals are shown as counts per million (CPM) of mapped reads. Flanking regions include 2 kb upstream and downstream of the peak regions. c, Genome browser screenshots showing ROS1-Flag aChIP, eChIP and rChIP data. Flag Col-0 ChIP-seq served as the control. d, Pearson correlation between two replicates of ROS1 aChIP. Each point represents the log2 of mapped reads within the combined peaks of the two replicates. The R value calculated by Pearson correlation coefficient at the combined peaks is shown. e, Venn diagram illustrating the overlap of peaks between the two replicates of ROS1 aChIP. f, Distinct clusters of ROS1 binding sites defined by chromatin accessibility and histone modification patterns in wild-type plants. Black dashed lines indicate the summits of ROS1 binding sites within the indicated clusters. The number of ROS1 binding sites in each cluster is shown. g, Distribution of ROS1 occupancy, ATAC-seq signals, and the indicated histone modifications at ROS1-bound intragenic regions. TSS, transcription start sites; TTS, transcription terminal sites. h, ATAC-seq signals at regions surrounding the summits of ROS1 binding sites with different peak intensity levels (n = 4,409 peaks per rank). i, Three categories defined by the association between ROS1 occupancy and accessible chromatin. j, Genome-wide distribution of ROS1 occupancy and ATAC-seq signals in the categories defined in (i). k, Representative examples from (i). NarrowPeak files generated by MACS2 were used to display the called peaks. The red bars indicate statistically significant peaks (q value < 0.01). Note that although a ROS1 or ATAC-seq peak may exist, it will only be marked by a red bar if identified as a significant peak by the MACS2 program.

Extended Data Fig. 2 Epigenomic features associated with the occupancy of truncated ROS1 variants, DME, DML2, DML3, and B. napus ROS1 homologs.

Distinct clusters of binding sites for these proteins defined by chromatin accessibility and histone modification patterns in wild-type plants. Black dashed lines indicate the summits of their binding sites within the indicated clusters. The number of binding sites for each protein in each cluster is shown.

Extended Data Fig. 3 Epigenomic feature comparison and functional redundancy analysis among Arabidopsis ROS1 family, truncated ROS1, and B. napus ROS1 homologs.

a, Association of full-length and truncated ROS1 occupancy at regions surrounding the summits of H3K9ac and H3K9me2 histone modifications. b, Venn diagram illustrating the overlap of binding sites of the indicated truncated ROS1 variants. c, Venn diagram illustrating the overlap between the truncated ROS1 binding sites and the representative histone modifications in wild-type plants. d, Association of ROS1 family protein occupancy at regions surrounding the summits of accessible chromatin and the indicated histone modifications. e, Association of ATAC-seq signals and ROS1 family protein occupancy at regions surrounding the ROS1-bound intergenic regions. f, Venn diagram illustrating the overlap between hyper-DMRs identified in ros1-4 and rdd-2 (ros1-4 dml2-2 dml3-2) triple mutant compared with wild-type (Col-0) plants. g, Relationships among less accessible regions (LARs) in ros1-4 relative to Col-0, LARs in rdd-2 relative to Col-0, and hyper-DMRs specific to rdd-2. Venn diagram (left) illustrating the overlap between LARs identified in ros1-4 and rdd-2 relative to Col-0. Of the 85 rdd-2-specific LARs, 21 co-localized with rdd-2-specific hyper-DMRs (right). h, Representative examples for (g) and (j). i, Venn diagram illustrating the overlap between hyper-DMRs identified in ros1-4 and drdd (dmeDD7pro ros1-4 dml2-2 dml3-2) quadruple mutant compared with Col-0. j, Relationships among LARs in ros1-4 relative to Col-0, LARs in drdd relative to Col-0, and hyper-DMRs specific to drdd. Venn diagram (left) illustrating the overlap between LARs identified in ros1-4 and drdd relative to Col-0. Of the 350 drdd-specific LARs, 156 co-localized with drdd-specific hyper-DMRs (right). k, l, Association between B. napus ROS1 occupancy and accessible chromatin.

Extended Data Fig. 4 Amino acid sequence alignment of Arabidopsis ROS1 family proteins and B. napus ROS1 homologs.

a, Amino acid sequence alignment of Arabidopsis ROS1 family proteins. ROS1 domains are indicated in the top row. b, Amino acid sequence alignment of Arabidopsis ROS1 and Brassica napus ROS1 homologs. ROS1 domains are indicated in the top row. The gene IDs are as follows: AT2G36490, BnaC04G0102100WE, and BnaA05G0075000WE.

Extended Data Fig. 5 The occupancy-based mechanism for ROS1-mediated maintenance of DNA hypomethylation.

a, Representative examples illustrating the relationship between ROS1 occupancy and DNA methylation. DNA methylation is generally excluded from ROS1-bound loci, whereas ROS1-unbound loci are frequently methylated in wild-type plants. b, Schematic diagram illustrating the proposed antagonistic mechanism between ROS1 and RdDM at distinct loci. In contrast to RdDM type I loci, which are targeted by RdDM rather than ROS1, two distinct hypotheses were proposed for the antagonistic mechanism between ROS1 and RdDM at RdDM type II loci: (1) ROS1 and RdDM may be simultaneously recruited to the same loci in wild-type plants, where RdDM establishes DNA methylation while ROS1 initiates active DNA demethylation; (2) ROS1 exclusively occupies these loci to prevents RdDM recruitment and the establishment of DNA methylation, allowing RdDM to act only after ROS1 removal. c, Identification of candidate loci for hypothesis (1). Venn diagram illustrating the overlap among hypo-DMRs in nrpd1-3 ros1-4 versus ros1-4, ROS1 Type II loci (hyper-DMRs in ros1-4 versus Col-0, overlapping ROS1-Flag peaks in ROS1-Flag/ros1-4), and NRPD1-Flag peaks present in both NRPD1-Flag/nrpd1-3 and NRPD1-Flag/nrpd1-3 ros1-4. A total of 77 candidate loci were identified for hypothesis 1. d, Association of NRPD1 occupancy and ROS1 occupancy at regions surrounding the summits of ROS1 peak overlapping the 77 candidate loci. e, Representative examples from (c). Red and purple bars indicate hyper-DMRs in ros1-4 versus Col-0 and hypo-DMRs in nrpd1-3 ros1-4 versus ros1-4, respectively. Purple dashed boxes indicate the overlapping regions between ros1-4 versus Col-0 hyper-DMRs and nrpd1-3 ros1-4 versus ros1-4 hypo-DMRs, which show features resembling those of RdDM Type II loci shown in Fig. 3f. Red dashed boxes indicate the residual regions of nrpd1-3 ros1-4 versus ros1-4 hypo-DMRs after exclusion of ros1-4 versus Col-0 hyper-DMRs, suggesting that these regions are independent of ROS1. f, g, ROS1 maintains hypomethylation at most target loci independently of its glycosylase/lyase activity despite transgenerational methylation in ros1. Left, Venn diagram showing the overlap of ROS1-bound hyper-DMRs in ros1 at the first (G1) and tenth (G10) generations relative to Col-0; middle, approximately 94% (G1) and 90% (G10) of ROS1-bound hyper-DMRs remained hypomethylated in ROS1D971A in situ substitution plants, whereas the remaining 6% and 10% exhibited strong hypermethylation comparable to ros1; right, DNA methylation levels of these two groups are presented for the indicated genotypes. h, Representative examples from (f, g).

Extended Data Fig. 6 ROS1 occupancy mediates passive DNA demethylation independently of its glycosylase/lyase activity.

a, Purification of ROS1D971A protein in vitro. WT ROS1 (residues 510-1,393) served as the control for the in vitro enzymatic activity assay (Fig. 4a). b, Epigenomic features associated with ROS1D971A occupancy. Distinct clusters of ROS1D971A binding sites defined by chromatin accessibility and histone modification patterns in wild-type plants. All three independent ROS1D971A-Flag/ros1-4 transgenic lines exhibited results similar to the control ROS1-Flag/ros1-4 lines (Extended Data Fig. 1f). Black dashed lines indicate the summits of ROS1D971A binding sites within the indicated clusters. The number of ROS1D971A binding sites in each cluster is shown. c, DNA methylation levels for the indicated genotypes at active-dominant (ROS1D971A undemethylated) and passive-dominant (ROS1D971A demethylated) loci. Two additional ROS1D971A-Flag/ros1-4 (#2 and #3) lines are shown, along with the numbers of passive- and active-dominant loci. d, The majority of the 603 demethylated loci shown in Fig. 4d remain hypomethylated in ROS1D971A in situ substitution plants. Of the 603 ROS1-demethylated loci, 94% remained hypomethylated in ROS1D971A in situ substitution plants, whereas 6% exhibited strong hypermethylation comparable to ros1-4. The number of loci in each group is shown (right), and DNA methylation levels for loci in these two groups are presented for the indicated genotypes (left). e, Representative examples from (d).

Extended Data Fig. 7 Identification of mutants used in this study and the redundant role of ROS1, GCN5, and SDG2 in regulating chromatin accessibility.

a, Schematic diagrams illustrating the T-DNA insertion sites or mutation positions. The PCR primers used for genotyping are indicated. b, Genotyping of the indicated mutants. c, Growth phenotypes of the indicated mutants and wild type. Five-week-old plants are shown. Bar, 5 cm. d, Association of ATAC-seq and H3K9ac signals at regions surrounding the 52 accessible chromatin regions co-regulated by ROS1 and the histone acetyltransferase GCN5 (as shown in Fig. 5c) in both H3K9ac-associated and H3K9ac-unassociated contexts. H3K9ac-associated regions are defined as those with decreased H3K9ac levels in the gcn5 and gcn5 ros1-4 mutants compared with Col-0 and ros1-4, while H3K9ac-unassociated regions lack H3K9ac signals in a 2 kb window surrounding the 52 additional LARs across all four genotypes. e, Representative examples of accessible chromatin regions co-regulated by ROS1 and GCN5. f, Identification of accessible chromatin regions co-regulated by ROS1 and the H3K4 methyltransferase SDG2. Venn diagram illustrating the overlap of LARs in sdg2 ros1-4 compared with Col-0, ros1-4, and sdg2. A total of 32 LARs were identified in the overlap (left). Distribution of ATAC-seq signals at regions surrounding these 32 LARs for the indicated genotypes are presented (right). g, Representative examples of accessible chromatin regions co-regulated by ROS1 and SDG2.

Extended Data Fig. 8 DNA methylation levels at the MEMS locus of the ROS1 promoter and expression levels of ROS1 in the indicated mutants and wild type.

The red dashed box highlights the DNA methylation levels at the MEMS locus of the ROS1 promoter for the indicated genotypes. ddcc, drm1 drm2 cmt2 cmt3; mddcc, met1 drm1 drm2 cmt2 cmt3.

Extended Data Fig. 9 Relationship between chromatin accessibility and DNA methylation across the indicated tissues and genotypes.

a, Representative examples from Fig. 7a. b, Chromatin accessibility dynamics across tissues primarily occur in contexts that are independent of DNA methylation. Distribution of ATAC-seq signals and DNA methylation levels at LARs and HARs between the indicated wild-type tissues in DNA methylation-independent contexts are shown. These contexts are defined as those exhibiting minimal or absent DNA methylation (mC% < 2%) in both tissues. The numbers of HARs and LARs in DNA methylation-independent contexts are shown. c, Identification of loci that lose DNA methylation but did not become accessible in met1-9 compared with Col-0. The brown region of the Venn diagram indicates hypo-DMRs in met1-9 compared with Col-0, characterized by minimal or absent DNA methylation (mC% < 2%) in met1-9 and a lack of detectable ATAC-seq signal in both genotypes (upper). A total of 22,596 loci were identified. Distribution of DNA methylation levels and ATAC-seq signals at regions surrounding these loci for the indicated genotypes are presented. d, Identification of loci that lose DNA methylation become accessible in met1-9 compared with Col-0. Venn diagram illustrates the overlap of HARs and hypo-DMRs in met1-9 (mC% < 2%) compared with Col-0. A total of 960 loci were identified in the overlap. Distribution of DNA methylation levels and ATAC-seq signals at regions surrounding these loci for the indicated genotypes are presented. e, Representative examples revealing that not all loci that lose DNA methylation become accessible in met1-9.

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Summary of transcriptome and epigenome data and primers in this study.

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Deng, L., Zhu, G., Zhong, W. et al. Occupancy-based mechanism is the chief mode of ROS1 function in preventing DNA hypermethylation. Nat. Plants (2026). https://doi.org/10.1038/s41477-026-02258-z

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