Unique cell-type-specific patterns of DNA methylation in the root meristem

  • Nature Plants 2, Article number: 16058 (2016)
  • doi:10.1038/nplants.2016.58
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DNA methylation is an epigenetic modification that differs between plant organs and tissues, but the extent of variation between cell types is not known. Here, we report single-base-resolution whole-genome DNA methylomes, mRNA transcriptomes and small RNA transcriptomes for six cell populations covering the major cell types of the Arabidopsis root meristem. We identify widespread cell-type-specific patterns of DNA methylation, especially in the CHH sequence context, where H is A, C or T. The genome of the columella root cap is the most highly methylated Arabidopsis cell characterized so far. It is hypermethylated within transposable elements (TEs), accompanied by increased abundance of transcripts encoding RNA-directed DNA methylation (RdDM) pathway components and 24-nt small RNAs (smRNAs). The absence of the nucleosome remodeller DECREASED DNA METHYLATION 1 (DDM1), required for maintenance of DNA methylation, and low abundance of histone transcripts involved in heterochromatin formation suggests that a loss of heterochromatin may occur in the columella, thus allowing access of RdDM factors to the whole genome, and producing an excess of 24-nt smRNAs in this tissue. Together, these maps provide new insights into the epigenomic diversity that exists between distinct plant somatic cell types.

DNA methylation is an epigenetic modification of cytosine bases implicated in gene regulation. In plants, DNA methylation occurs in three distinct cytosine contexts: CG, CHG and CHH. CG and CHG methylation is stably maintained by DNA METHYLTRANSFERASE 1 (MET1) and CHROMOMETHYLASE 3 (CMT3), respectively. De novo DNA methylation is catalysed by DOMAINS REARRANGED METHYLTRANSFERASE 2 (DRM2) in all three sequence contexts, in a process that is guided by 24-nt smRNAs, known as RdDM (refs 1,2). DNA methylation may also be maintained independently of the RdDM pathway through the concerted action of DDM1 and CHROMOMETHYLASE 2 (CMT2)3,4. DDM1 functions to displace the linker histone H1 in heterochromatic regions of the genome, allowing CMT2 access to the DNA, where it is able to catalyse the methylation of cytosines in the CHG and CHH contexts3,4. Although DNA methylation can be a stable epigenetic mark, faithfully maintained for many hundreds of generations5, dynamic changes in DNA methylation patterns can be observed during short time scales in response to the environment6,7, or in different cell types of a single individual8,​9,​10,​11, presumably a result of differential regulation of the RdDM or CMT2-mediated DNA methylation pathways. Thus, DNA methylation is a stable but reversible epigenetic modification, and may reflect, or play an important role in maintaining, cell-type identity. However, further investigation is needed to characterize the epigenome in distinct cell types to investigate the potential role of any differences.

In Arabidopsis, a major biological role of DNA methylation is in silencing TE transcription. Loss of DNA methylation because of mutations in DDM1 or MET1 is sufficient for transcriptional activation of demethylated TE sequences, and transposition of some of these activated TEs3,12,13. Although TE insertions may contribute to novel modes of gene regulation, excess TE activity produces deleterious mutations, and efficient TE silencing is crucial for the maintenance of genome integrity. Plants may be most vulnerable to TE activity in the stem cells, as these are the progenitor cells from which all others derive, and TE insertions within the stem cells will therefore be inherited by all descendant cells. Indeed, highly complex mechanisms of TE silencing have been reported in the sperm and embryo. TE silencing in the sperm is thought to be assisted by 21-nt smRNAs derived from the vegetative cell nucleus, a non-generative companion to the sperm, and in the developing embryo by endosperm-derived 24-nt smRNAs9,​10,​11, indicating that silencing of TEs may be particularly important in these cells. Plants have stem cell niches at distal axes, known as the shoot apical meristem (SAM) and root apical meristem (RAM). RdDM factors, DNA methyltransferases, and DDM1 are all upregulated to reinforce TE silencing in the SAM (ref. 14). There is some indication that gross levels of DNA methylation may be distinct in the RAM (refs 15,16), but patterns of DNA methylation in the RAM have not been studied at high resolution, and the dynamics of DNA methylation-mediated TE silencing in the RAM are so far unexplored. Here we describe comprehensive DNA methylation and transcriptome profiling of six distinct cell types of the Arabidopsis RAM, revealing unique cell-type-specific characteristics of DNA methylation and the machinery responsible for shaping the methylome.


Columella is the most CHH-hypermethylated cell type in Arabidopsis

To investigate patterns of DNA methylation in different plant cell types, we used protoplasting followed by fluorescence-activated cell sorting (FACS) of cell populations marked by green fluorescent protein (GFP) in a range of reporter lines. These lines represent the major cell types or tissues in the root: epidermis (ProWER–GFP), cortex (ProCOR–GFP), endodermis (ProSCR–GFP), stele (ProWOL–GFP), whole columella root cap (PET111 enhancer trap line) and lower columella (ProCYCD5–GFP) (Fig. 1a). Two independently generated reporter lines were analysed for the endodermis. Following isolation of highly enriched populations of each cell type (Supplementary Fig. 1), we generated single-base resolution maps of cytosine methylation by whole-genome bisulphite sequencing and transcriptome profiles by RNA-seq and smRNA-seq (Fig. 1b and Supplementary Table 1). Analysis of global levels of DNA methylation in the six cell populations revealed that methylation in all sequence contexts (mCG, mCHG, mCHH) were higher in the columella, with dramatically increased levels of mCHH (Fig. 1c). Comparison with previously published Arabidopsis methylomes showed that mCHH levels in the columella are higher than in any other tissue or cell type analysed to date10,11 (Fig. 1c). The enrichment of mCHH in the columella was the most pronounced in the pericentromeric regions of the chromosome (Fig. 1d). Whole root tips from the PET111 transgenic line, and from Col-0, showed similar patterns and levels of mC as the non-columella cell types (Fig. 1c,d), indicating that the differences observed in the columella cell populations were due to cell type and not a widespread perturbation of DNA methylation in the transgenic lines used for cell isolation.

Figure 1: Cell-type-specific patterns of DNA methylation in the root meristem.
Figure 1

a, Schematic representation of the six root cell types used in this study. *MethylC-seq data only. b, A genome browser snapshot showing DNA methylation level, RNA-seq reads and smRNA-seq reads. The endodermis (EN) has two independent replicates (EN-1 and EN-2) for MethylC-seq and RNA-seq. c, Global levels of DNA methylation in each context for root and reproductive cells (VN, vegetative nucleus11; SP, sperm11; MS, microspore10; EM, embryo30; EN, endosperm30). d, Heat map showing mC levels within 100 kb bins and genes and TEs within 50 kb bins across the entire genome. Maximum mC levels are 0.91 (mCG), 0.72 (mCHG) and 0.34 (mCHH).

Columella hypermethylation is the major source of widespread differential DNA methylation in the root meristem

To further investigate the large differences in DNA methylation patterns, we identified differentially methylated regions (DMRs) in the genome between the cell types. With a target false discovery rate of 5%, we identified 38,307 DMRs among the different cell types (Fig. 2a). Of these, 13.6% (5,225) were differentially methylated only in the CG context (CG-DMRs), whereas 82.9% (31,761) were differentially methylated only in the CH context (CH-DMRs) (Fig. 2a, Supplementary Tables 2 and 3). Regions differentially methylated in both the CG and CH context (C-DMRs) were rare, with only 1,321 such regions observed (Fig. 2a and Supplementary Table 4). The DMR length also seemed to be associated with DNA methylation context, with CG-DMRs being, on average, shorter than CH- and C-DMRs (Fig. 2b). Overall, 13.8% of the nuclear genome was differentially methylated between the six cell types, mostly in the CH context (Fig. 2c).

Figure 2: Differentially methylated regions (DMRs) among six root cell types.
Figure 2

a, The numbers of each type of DMR. b, The average sizes of each type of DMR. c, The genomic fraction of each type of DMR relative to the whole genome. d, The genome-wide distribution of each type of DMR. The counts were scaled with 1.0 as the maximum count. e, Genomic features covering DMRs. f, Hierarchical clustering of six root cell types for CG-, CH- and C-DMRs. g, mCHH levels within CH- and C-DMRs. h, 24-nt smRNA expression levels in CH- and C-DMRs. i, Correlation between DMR methylation and gene expression levels. ‘Combinations’ refers to the number of all possible comparisons between DMRs and the nearby genomic features. See Methods for details.

Some regions of the genome are prone to spontaneous changes in DNA methylation levels17,18. To determine if the regions of differential DNA methylation between cell types were due to spontaneous fluctuations in DNA methylation levels between the different transgenic lines used, we compared the root cell-type-specific DMRs with two types of previously identified spontaneous DMRs: transgenerational DMRs (ref 17) and population DMRs (ref 19). We found that 76 and 60% of root cell-type-specific CG-DMRs and C-DMRs, respectively, overlapped with population DMRs, whereas only 5 and 2% of root cell-type-specific CG- and C-DMRs overlapped with transgenerational CG- and C-DMRs (Supplementary Fig. 2). We concluded that the majority of root cell-type-specific DMRs occur in regions of the genome known to be epigenetically labile, likely to be due to variation in smRNAs.

To determine if the enrichment of DNA methylation in pericentromeric regions (Fig. 1d) was linked to DMRs, we assessed the distribution of DMRs along the chromosomes (Fig. 2d and Supplementary Fig. 3). Although CG-DMRs are most abundant in the chromosome arms, the number of CH- and C-DMRs peaked in the proximal and distal pericentromeric regions, respectively. Closer inspection of the genomic features intersecting each set of DMRs revealed that more than 80% of CG-DMRs overlapped with protein-coding gene bodies (Fig. 2e), and 73% of CH-DMRs and 44% of C-DMRs overlapped with TEs. The remaining CH-DMRs and C-DMRs were found to overlap mainly with intergenic regions or pseudogenes.

Hierarchical clustering based on differences in DNA methylation showed that the columella cells form a highly distinct group compared with other cells of the root (Fig. 2f). Interestingly, DNA methylation patterns seemed to be more similar between cell types located physically close to one another in the root, regardless of their lineage, whereas transcriptional profiles were more dependent on cell lineage than physical position in the root (Supplementary Fig. 4). This may suggest that methylation patterns are in part regulated by positional information or cell–cell communication. Columella cells were highly distinct in their DNA methylation landscape, particularly in the mCHH context. Methylation at CH- and C-DMRs was higher in the columella than in other cell types, suggesting that CHH hypermethylation in the columella is the primary basis for CH- and C-DMRs among root meristem cells (Fig. 2g and Supplementary Fig. 5).

As mCHH is deposited by two distinct DNA methyltransferases, DRM2 and CMT2 (refs 3,4), we sought to determine which methyltransferase was responsible for mediating changes in mCHH in each set of DMRs. We analysed mCHH levels within DMR coordinates in leaves of wild-type, drm1 drm2 and cmt2 plants to categorize DMRs as DRM2 or CMT2 targets, using previously published DNA methylation data20 (Supplementary Fig. 6). For CH-DMRs, both drm1 drm2 and cmt2 showed decreased mCHH in these regions, but the effect of cmt2 was much larger, whereas for C-DMRs only drm1 drm2 caused a decrease in mCHH levels. These results reveal that mCHH within CH-DMRs and C-DMRs is mainly catalysed by CMT2 and DRM2, respectively. DRM2 is involved in two types of RdDM: the canonical Pol IV-mediated RdDM guided by 24-nt smRNAs1,2, and RDR6-mediated RdDM guided by 21- and 22-nt smRNAs21. We detected upregulation of 21–24-nt smRNA abundance within both CH-DMRs and especially C-DMRs in the columella, but 24-nt smRNAs were predominant (Fig. 2h and Supplementary Fig. 7), suggesting that the canonical Pol IV-mediated RdDM pathway plays a major role in establishing these DMRs. We did not observe higher steady-state transcript abundance of TEs in the columella (Supplementary Fig. 8).

Gene body methylation in the CG context is correlated with constitutive gene expression22,​23,​24. In contrast, DNA methylation in gene-flanking regions is thought to repress gene expression. To address whether DMRs affect the expression of nearby genes, we correlated DMR methylation levels and nearby gene expression levels (Fig. 2i). Most CG-DMRs were located within the gene bodies, especially near transcriptional termination sites. However, minimal correlation between methylation levels at CG-DMRs and expression levels of nearby genes was observed. CH- and C-DMRs are largely excluded from the gene bodies. The correlation between CH- and C-DMR methylation and gene expression was also variable, but methylation at transcription start sites was weakly negatively correlated with the transcript abundance of nearby genes. Similarly, methylation at C-DMRs within gene bodies showed a negative correlation with gene expression. These results suggest root cell-type-specific CH and C-DMRs are only weakly associated with cell-type-specific gene expression patterns. Additionally, gene ontology enrichment analysis showed that CH-DMR-associated genes were enriched for response genes, such as ‘defence response’ and ‘innate immune response’ (Supplementary Fig. 9). This suggests that CH-DMRs only weakly correlate with nearby gene expression, and may only have an impact on gene expression under specific environmental circumstances.

Transposable elements are targets for CHH hypermethylation

Although only a small percentage of CH-DMRs were found to intersect with gene bodies (Fig. 2f), these still represented more than 1,000 gene loci because of the abundant nature of CH-DMRs. To further investigate whether there was a correlation between mCHH levels within genes and the transcript abundance of those genes, we placed all TAIR10 genes in order on the basis of the average transcript abundance among cell populations and further analysed patterns of DNA methylation (Fig. 3). This revealed that whereas levels and patterns of mCG and mCHG were similar between cell types (Fig. 3a) lowly expressed and silent genes were CHH hypermethylated in the columella. Furthermore, we found that the number of genes harbouring TEs was also enriched in genes with lower expression (Fig. 3a), suggesting that increases in mCHH within lowly expressed genes may be due to the hypermethylation of TEs contained within these genes. As mCHH serves to transcriptionally silence TEs in Arabidopsis, and most CH-DMRs were found within annotated TEs, we compared patterns and levels of DNA methylation across all TEs in the genome (Fig. 3b–d). Levels of mCG and mCHG in TEs were only moderately higher in both of the columella cell populations, consistent with our observations on a genome-wide scale (Fig. 1c). However, a large increase in mCHH in in TEs in both of the columella cell populations was observed compared with the other cell types, and this was consistent across all known TE superfamilies in Arabidopsis (Supplementary Fig. 10). This indicates that, although some CH-DMRs were found to intersect with protein-coding genes, differences in mCHH between cell types can be attributed almost entirely to the CHH hypermethylation of TEs in the columella. As TEs are greatly enriched in the pericentromeric heterochromatin, this would also explain the enrichment of mCHH and CH-DMRs in the pericentromeric regions (Figs 1c and 2d).

Figure 3: DNA methylation in genes and TEs.
Figure 3

a, DNA methylation patterns within genes ordered by average mRNA abundance. b, DNA methylation patterns and levels within TEs for each cell type. TEs show greatly increased mCHH in the columella genome, whereas mCG and mCHG levels are similar and moderately higher than other cell types.

Enhanced RNA-directed DNA methylation in the columella

As we observed an increase in mCHH in TEs, as well as an increase in 24-nt smRNA abundance at CH-DMRs, we next sought to determine whether there might be transcriptional upregulation of the RdDM pathway in the columella. Analysis of the RNA-seq data revealed an increase in transcripts encoding components of the RdDM pathway in the columella compared with the other cell populations (Fig. 4a). In particular, we found an enrichment for transcripts encoding proteins needed for smRNA biogenesis, such as the major unique Pol IV component NRPD1a, as well as CLSY1, RDR2 and DCL3, and those components involved directly in the deposition of DNA methylation were only mildly upregulated in the columella25,​26,​27,​28. To investigate whether this increased production of smRNA biogenesis machinery in the columella translated into an increase in the proportion of 24-nt smRNAs sequenced, we assessed levels of uniquely mapped 21, 22, 23 and 24-nt smRNAs genome wide (Fig. 4b and Supplementary Table 5). This revealed a strong increase in the fraction of 24-nt smRNAs in the columella, indicating that the hypermethylation of TEs in the columella is coupled with the transcriptional upregulation of the smRNA biogenesis machinery and increased production of 24-nt smRNAs needed for the RdDM pathway.

Figure 4: Transcript levels of DNA-methylation-related genes.
Figure 4

a, Increased transcript abundance for genes involved in smRNA biogenesis in the columella. Scale is log2-fold change FPKM for each cell type compared to average FPKM for all cell types. Average FPKM for all cell types are also shown. b, Fraction of uniquely mapped smRNA for each size class relative to total uniquely mapped smRNA. The proportion of 24-nt smRNAs relative to other size classes is greatly increased in the columella.

DDM1 protein is not present in the columella

In the vegetative cell nucleus of the pollen, a loss of mCG and mCHH throughout the genome is coupled with increased mCHH at the centromere, the absence of DDM1 protein, and loss of heterochromatin9,10 (Supplementary Fig. 11). This triggers TE transcriptional activation and increased production of 21-nt smRNAs from TE transcripts, which are thought to be transported to the sperm cells to reinforce TE silencing in the germline9,10. We observed an increase in 24-nt smRNAs and CHH hypermethylation of TEs in columella cells. Although no decrease in DDM1 transcript abundance specific to the columella was detected (Figs 4a and 5a), analysis of a transgenic line expressing the DDM1–GFP fusion protein revealed that DDM1–GFP was undetectable in the columella, whereas it was present in the nuclei of other root cell types (Fig. 5b). This indicates that DDM1 is transcribed in the columella, but either the transcripts are not translated or there is rapid degradation of DDM1 protein. Despite an apparent lack of DDM1 in the columella, and in contrast to ddm1, normal levels of mCG and mCHG are maintained at TEs, and there are elevated levels of mCHH (Figs 3d and 5c).

Figure 5: Loss of DDM1 in the columella.
Figure 5

a, DDM1 transcript abundance in all cell types. b, Absence of DDM1–GFP in the columella. c, mCHH levels and smRNA accumulation around methylated TEs. Methylated TEs were classified into four clusters based on TE body methylation levels of wild type, drm1 drm2, cmt2 and ddm1 in leaf tissue using the k-means method. Left panel shows mCHH levels within TEs and their 2 kb upstream and downstream regions. Each region consists of 40 equally sized bins. The right panel shows smRNA expression levels as in the left panel. TEs were ordered by coordinate within each cluster. d, Representative genome browser snapshots for TEs in each cluster.

DDM1-dependent mCHH deposition is catalysed by the DNA methyltransferase CMT2 (ref. 3), and the RdDM pathway together with CMT2 are responsible for almost all mCHH in the genome4. We classified all methylated TEs into four clusters, based on the mCHH levels within TE bodies of the wild-type, drm1 drm2, cmt2 and ddm1 leaf tissue (Fig. 5c, left). mCHH levels in TEs in clusters 1 and 2 were decreased in drm1 drm2, indicating that they were RdDM-dependent. mCHH levels in TEs in cluster 3 and cluster 4 were decreased in cmt2, indicating that their methylation was CMT2 dependent. Strikingly, in the columella, TEs in all four clusters were hypermethylated (Fig. 5c). RdDM-dependent TEs were hypermethylated, accompanied by 24-nt, but not 21-nt, smRNA accumulation. CMT2-dependent TEs were hypermethylated in the columella, and those located in chromosome arms were accompanied by 24-nt smRNA accumulation, consistent with 24-nt smRNA enrichment in CH-DMRs. The edges of CMT2-dependent TEs are subjected to RdDM, and 24-nt smRNAs are enriched in these regions3. However, the edges as well as the bodies of CMT2-dependent TEs accumulated 24-nt smRNAs in the columella (Fig. 5c,d), suggesting that the bodies of CMT2-dependent TEs are also subjected to RdDM. This may account for CHH hypermethylation of CMT2-dependent TEs, but lower expression of CMT2 in the columella (Fig. 4a).

DDM1 is normally required for the displacement of histone H1 at heterochromatic regions of the genome, allowing DNA methyltransferases MET1, CMT3 and CMT2 to access and methylate the DNA3. As loss of H1 suppresses the reduction in DNA methylation in ddm1 mutants, we examined transcript levels for the two canonical histone H1 genes, H1.1 and H1.2, and observed lower abundance of transcripts for both genes in columella cells than in other cells in the root meristem (Fig. 4a). Also H2A.W6 and H2AW.7, which are required for chromatin condensation29, were downregulated in the columella (Fig. 4a), suggesting that the columella may lose heterochromatin by a reduction of heterochromatin-related components. Loss of heterochromatin in the columella may play a role in enhancing generation of the 24-nt smRNA transcripts needed for RdDM, leading to the observed CHH hypermethylation of TEs.


Plants are complex multicellular organisms that contain a broad variety of cell types with specialized functions. Although differences in patterns of DNA methylation have been observed previously between different somatic tissues16 and reproductive cell types9,​10,​11,30, this is the first report of differences in DNA methylation between cell types from the same somatic tissue. The root meristem contains a diverse variety of cell types. Among these, the columella is a group of specialized gravity-sensing cells required for proper development of the root31,32. The most striking and unique feature of these root cell methylomes is the CHH hypermethylation of TEs in the columella, which is obscured when methylomes are analysed using whole roots or dissected root tips. The majority of detected DMRs are columella hypermethylated CH-DMRs occurring in epigenetically labile regions. To date, the columella is the most highly methylated tissue or cell type characterized in Arabidopsis, and such an extreme level of hypermethylation is not recapitulated by any known gene-silencing mutant. Columella cells are rapidly replaced in the root as they grow outward from the columella initials, located below the quiescent centre, and are ultimately detached into the soil. Consequently, columella cells are short lived and undergo rapid differentiation. mCHH primarily serves to silence TE transcription in Arabidopsis, preventing potentially damaging genetic mutations caused by transposition. Owing to the terminally differentiated and short-lived nature of columella cells, it is reasonable to expect that TE insertions in the columella would have little impact on root function and fitness, as these mutations would be quickly lost from the plant. The apparent enhancement of DNA methylation-mediated TE silencing in the columella is therefore counterintuitive. One possible explanation for this seeming contradiction is that the columella acts as a companion to nearby stem cells, and is similar in function to the reproductive companion cells found in the developing pollen and seed9,​10,​11,30. Excess 24-nt smRNAs produced by the columella, required for initiation of RdDM at TEs, may be transported into the neighbouring stem cell niches such as the quiescent centre, reinforcing transcriptional silencing of TEs in these stem cells in a manner analogous to the smRNA transport thought to occur between the vegetative cell nucleus and sperm cells in the developing pollen, between the central cell and egg, and possibly between the endosperm and embryo10,11. As the root stem cells are responsible for the establishment of tissue patterning in the root, and all cells of the root descend from these stem cells, transpositions in them may have a larger impact on plant fitness, and therefore have a greater need for effective TE silencing, similar to generative stem cells in the germline. Although DDM1 is undetectable in both the columella and the vegetative cell nucleus of the pollen, the patterns of mCHH at TEs are distinct between these two cell types, with mCHH levels in the vegetative cell nucleus being more similar to that found in ddm1. Heterochromatin has been suggested to inhibit RdDM, whereas open chromatin increases the accessibility of RdDM components to the genome leading to hypermethylation33. DDM1, and associated proteins such as H1, may play an important role in regulating the exclusion of RdDM-related factors from the heterochromatin, and it is possible that DDM1 protein accumulation is actively suppressed in the columella to allow RdDM at DDM1-regulated heterochromatic regions. Another possible explanation for the CHH hypermethylation and upregulation of the RdDM pathway in the columella may be that special attributes of the columella, such as the rapid differentiation after one division of the stem cell and possible increased ploidy level34, are conducive to hypermethylation of TEs. Future experiments will be needed to further examine these hypotheses.


Cell isolation

Seedlings were grown vertically for 6 days after plating on 1× Murashige and Skoog media supplemented with 1% sucrose and 1% agar. All seedlings were grown under standard long day conditions (16 h of light, 8 h of darkness, 22 °C). FACS was performed using cell-specific GFP lines as described previously35. The columella root cap was marked with the enhancer trap PET111 (ref. 36), the bottom two layers of the columella were marked with ProCYCD5–GFP (ref. 37), the stele with ProWOL–GFP (ref. 38), the endodermis with ProSCR–GFP (ref. 39), the cortex with ProCORTEX–GFP (ref. 40), and both the epidermis and lateral root cap with ProWER–GFP (ref. 41). Sorted cells were collected directly into specific lysis buffers that were compatible with downstream applications. Cells used for bisulphite sequencing, mRNA-seq and smRNA-seq were lysed in Buffer AP1 (Qiagen), Buffer RLT (Qiagen), Trizol (Invitrogen). All samples were immediately stored at −80 °C until genomic DNA and RNA had been extracted using the DNeasy Plant mini kit (Qiagen) and the RNeasy Plant mini kit (Qiagen) or Trizol, respectively.


MethylC-seq library preparation, read mapping and base calling were performed as described previously42,​43,​44, except that reads were mapped against the C-to-T converted TAIR10 reference genome, and library amplification was performed with either the KAPA HiFi U+ (KAPA) or the PfuTurboCx enzyme (Agilent). The bisulphite non-conversion rate was estimated from the total number of cytosine base calls divided by the total coverage at cytosine positions in the naturally unmethylated chloroplast genome.

Identification of differentially methylated regions

DMRs were identified using the methylpy pipeline45. Briefly, differentially methylated sites (DMSs) were identified by root mean square tests with a false discovery rate at 0.05 using 1,000 permutations. Cytosine positions at least with four reads were examined for differential methylation. Then, DMSs within 200 bp were collapsed into DMRs. DMRs were classified into CG-DMRs (only CG difference), CH-DMRs (only CHG and/or CHH difference), C-DMRs (CG and CHG and/or CHH difference). In addition, CG-DMRs, CH-DMRs and C-DMRs with fewer than five, five and ten DMSs, respectively, were discarded in the following analysis. Differential methylation tests were performed among samples, not in a pairwise manner, generating a set of all non-redundant DMRs among the samples. The methylation levels in each region were calculated as weighted methylation levels46, in which the methylation level was equal to the frequency of C base calls at C positions within the region divided by the frequency of C and T base calls at C positions within the region.


RNA-seq library preparation was performed using the Illumina TruSeq RNA Library Prep kit from polyA+ selected mRNA as per the manufacturer's instructions. smRNA sequencing data were obtained from a previous study47. smRNA data were processed and mapped to the TAIR10 genome as described previously48. smRNAs levels were normalized to TE size and library size by counting the reads per kilobase of TE per million reads mapped (RPKM). Only reads that mapped uniquely to the genome contributed to the average count for each TE. RNA-seq data were mapped to the TAIR10 reference genome using Tophat2 with the default parameters49 and quantified using Cuffdiff (ref. 50).

Associating DMRs with proximal genes

DMRs located within 3 kb of gene upstream regions, gene bodies and 3 kb of gene downstream regions were extracted, and relative position to genes were assigned by the middle position of DMRs. Some DMRs were located within multiple genomic features, for example in the 3 kb upstream regions, gene bodies or 3 kb downstream regions for more than one gene. We refer to all possible pairwise comparisons between DMRs and nearby genomic features as ‘combinations’. Pearson correlation coefficients between the methylation levels of DMRs and the expression levels of proximal genes (FPKM) were computed and plotted as density.

Clustering TEs

mCHH levels within annotated TE bodies at least 400 bp in length were computed, and only TEs with a minimum of 10% of mCHH in at least one sample from Col-0, drm1 drm2, cmt2 and ddm1 were assigned as methylated TEs. TEs were then clustered into four clusters by using R k-means function, with the ‘centres’ parameter set to 4.

Microscopy analysis

The DDM1–GFP transgenic line has been described previously9. Seeds were plated on 1/2× Linsmaier and Skoog media. Three days after germination, seedlings were incubated in propidium iodide for 5 min to stain cell walls of root tips, and imaged using Zeiss LSM 710 Confocal Microscope.

Accession codes

All sequence data can be downloaded from NCBI GEO under accession GSE79710, and can also be viewed at


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We thank K. Slotkin (Ohio State Univ., USA) and J.A.H. Murray (Univ. Cardiff, UK) for kindly providing DDM1–GFP seeds and ProCYCD5–GFP seeds, respectively. T.K. was supported by the Japan Society for the Promotion of Sciences Research Abroad Fellowship. T.S was supported by the Jean Rogerson Postgraduate Scholarship. This research was supported by grants from the National Science Foundation (MCB-1344299 to J.R.E and IOS-1021619 to P.N.B.), by the National Institutes of Health (GM R01-043778 to P.N.B.) and by the Gordon and Betty Moore Foundation (GBMF3034 to J.R.E and GBMF3405 to P.N.B.). R.L. was supported by the Australian Research Council (FT120100862). R.J.S. was supported by the National Institutes of Health (R00GM100000). J.R.E. and P.N.B. are investigators of the Howard Hughes Medical Institute.

Author information

Author notes

    • Taiji Kawakatsu
    • , Tim Stuart
    •  & Manuel Valdes

    These authors contributed equally to this work.


  1. Plant Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA

    • Taiji Kawakatsu
    • , Robert J. Schmitz
    •  & Joseph R. Ecker
  2. Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA

    • Taiji Kawakatsu
    • , Robert J. Schmitz
    • , Joseph R. Nery
    • , Mark A. Urich
    • , Ryan Lister
    •  & Joseph R. Ecker
  3. Genetically Modified Organism Research Center, National Institute of Agrobiological Sciences, Tsukuba, Ibaraki 305-8602, Japan

    • Taiji Kawakatsu
  4. ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Perth, Western Australia 6009, Australia

    • Tim Stuart
    •  & Ryan Lister
  5. Department of Biology, Duke University, Durham, North Carolina 27708, USA

    • Manuel Valdes
    • , Natalie Breakfield
    • , Xinwei Han
    •  & Philip N. Benfey
  6. Department of Genetics, University of Georgia, Athens, Georgia 30602, USA

    • Robert J. Schmitz
  7. Howard Hughes Medical Institute, Duke University, Durham, North Carolina 27708, USA

    • Philip N. Benfey
  8. Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, California 92037, USA

    • Joseph R. Ecker


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P.N.B., J.R.E. and R.L. designed and supervised research. N.B., X.H. and M.V. collected cells. T.K., R.L., J.R.N. and M.A.U. conducted MethylC-seq experiments. R.L., J.R.N. and M.A.U. conducted RNA-seq experiments. T.K. and R.L. performed sequencing data processing. T.K., R.L., R.J.S. and T.S. performed statistical and bioinformatic analyses. R.J.S. performed imaging analyses. P.N.B., J.R.E., T.K., R.L. and T.S. prepared the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ryan Lister or Philip N. Benfey or Joseph R. Ecker.

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