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Single-molecule targeted accessibility and methylation sequencing of centromeres, telomeres and rDNAs in Arabidopsis

Nature Plants volume 9, pages 1439–1450 (2023)Cite this article

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Abstract

The short read-length of next-generation sequencing makes it challenging to characterize highly repetitive regions (HRRs) such as centromeres, telomeres and ribosomal DNAs. Based on recent strategies that combined long-read sequencing and exogenous enzymatic labelling of open chromatin, we developed single-molecule targeted accessibility and methylation sequencing (STAM-seq) in plants by further integrating nanopore adaptive sampling to investigate the HRRs in wild-type Arabidopsis and DNA methylation mutants that are defective in CG- or non-CG methylation. We found that CEN180 repeats show higher chromatin accessibility and lower DNA methylation on their forward strand, individual rDNA units show a negative correlation between their DNA methylation and accessibility, and both accessibility and CHH methylation levels are lower at telomere compared to adjacent subtelomeric region. Moreover, DNA methylation-deficient mutants showed increased chromatin accessibility at HRRs, consistent with the role of DNA methylation in maintaining heterochromatic status in plants. STAM-seq can be applied to study accessibility and methylation of repetitive sequences across diverse plant species.

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Fig. 1: STAM-seq simultaneously profiles chromatin accessibility and DNA methylation in HRR regions.
Fig. 2: Strand-specific analysis of epigenetic patterns in the centromeric region.
Fig. 3: Single-molecule analysis of the chromatin accessibility and DNA methylation at centromeric region.
Fig. 4: STAM-seq reveals distinct epigenetic patterns of rRNA gene variants.
Fig. 5: Chromatin accessibility and DNA methylation on telomeric region.

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Data availability

The STAM-seq data generated in this study have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA: CRA008945) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa. Source data are provided with this paper.

Code availability

Source code for analysis is available at https://github.com/ZhaiLab-SUSTech/STAM-seq/.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (32270631 to X.D.), the Youth Innovation Promotion Association of CAS (2018131), the National Key R&D Program of China Grant (2019YFA0903903), the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2016ZT06S172), the Shenzhen Sci-Tech Fund (KYTDPT20181011104005), the Key Laboratory of Molecular Design for Plant Cell Factory of Guangdong Higher Education Institutes (2019KSYS006), the Stable Support Plan Program of Shenzhen Natural Science Fund Grant (20200925153345004), the Youth Innovation Promotion Association of CAS (Y2022039) and the Center for Computational Science and Engineering at Southern University of Science and Technology.

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Author notes

  1. These authors contributed equally: Weipeng Mo, Yi Shu.

Authors and Affiliations

  1. Institute of Plant and Food Science, Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China

    Weipeng Mo, Yi Shu, Bo Liu, Yanping Long & Jixian Zhai

  2. State Key Laboratory of Plant Genomics and National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China

    Tong Li, Xiaofeng Cao & Xian Deng

  3. University of Chinese Academy of Sciences, Beijing, China

    Xiaofeng Cao

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Contributions

J.Z., W.M. and Y.S. conceived and designed the experiments. Y.S., W.M., Y.L. and B.L. performed the experiments. W.M. and Y.S. analysed the data. J.Z. and X.D. oversaw the study. X.C. and T.L. provided conceptual insight. W.M., Y.S., J.Z. and X.D. wrote the manuscript, and all authors revised the manuscript.

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Correspondence to Xian Deng or Jixian Zhai.

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Nature Plants thanks Ian Henderson, James Walker and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 The fraction of bases called as 6 mA in the libraries.

Arabidopsis genomic DNA was treated with or without the EcoGII enzyme. Shown are the average methylation levels for A nucleotides.

Extended Data Fig. 2 Sequencing coverage of HRR regions relative to non-HRR regions in the library with or without adaptive sampling.

The target regions include centromeres, telomeres, and 45 S rDNA in Arabidopsis genome.

Extended Data Fig. 3 Comparison of STAM-seq with WGBS.

The IGV genomic tracks display a target region located adjacent to the left telomere on Chromosome 1. The tracks show the DNA methylation levels observed in the CG, CHG, and CHH contexts of aggregated STAM-seq data compared to previously published WGBS data (ENA accession PRJEB9919).

Extended Data Fig. 4 Comparison of DNA methylation levels between wildtype and mutants over transposable elements (TE) and gene bodies.

a. Metaplots of DNA methylation levels in CG, CHG, and CHH contexts over TE in wildtype and mutant samples. b. Metaplots of DNA methylation levels in CG, CHG, and CHH contexts over gene bodies in wildtype and mutant samples.

Extended Data Fig. 5 Comparison of STAM-seq profiles between replicates.

a. Correlation of STAM-seq accessibility signal between replicates over promoters. Shown is the average 6 mA ratio over the TSS ± 200. b-d. The correlation of STAM-seq DNA methylation levels between replicates. Methylation levels for CG, CHG, and CHH were illustrated in panels b, c, and d, respectively.

Extended Data Fig. 6 Strand-specific analysis of accessibility for genic regions.

a, b. The strand-specific view of chromatin accessibility and DNA methylation signal at genic region. Only reads that fully spanned the region were shown. The reads in each panel are arranged from top to bottom in order of increased chromatin accessibility. c. Metaplots illustrating the chromatin accessibility signal over genes from different strands. The blue color corresponds to the forward strand (5′→3′) of the reference genome, while the red color represents the reverse strand (3′→5′).

Extended Data Fig. 7 Strand-specific analysis for centromeric region.

a. Strand-specific view of CG methylation for the centromeric region. The reads in each panel are arranged from top to bottom in order of decreased CG methylation. b. Strand-specific view of CHH methylation for the centromeric region. The reads in each panel are arranged from top to bottom in order of decreased CHH methylation. c. Strand-specific view of chromatin accessibility signal for the centromeric region. Only reads that fully spanned the region were shown. The inaccessible reads (accessibility signal = 0) are highlighted by brackets. The reads in each panel are arranged from top to bottom in order of increased chromatin accessibility. d. Distribution of the accessibility signal for the example depicted in (c). The dotted line marks the division between accessible and inaccessible reads, with the left side representing the region containing the inaccessible reads.

Extended Data Fig. 8 Epigenetic patterns over the 45 S rRNA genes.

a. Metaplots of accessibility (top) and DNA methylation (bottom) over the 45 S rRNA genes. The schematic of 45 S rRNA gene region was shown on the top. b. Metaplots of accessibility (top) and DNA methylation (bottom) at transcription initiation site (TATATAGGGGG, +1 is underlined) of the 45 S rRNA genes. The accessibility signal reveals the nucleosome positioning pattern.

Extended Data Fig. 9 Epigenetic patterns between different 45 S rDNA classes.

a, d. Metaplots of accessibility (a), CG methylation (b), CHG methylation (c), and CHH methylation (d) in different 45 S rRNA gene variants.

Extended Data Fig. 10 DNA methylation level of the three consecutive cytosines in the telomeric repeat.

The methylation level was calculated as the ratio of 5-methylcytosine (5mC) to total cytosine (C) at these positions.

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Mo, W., Shu, Y., Liu, B. et al. Single-molecule targeted accessibility and methylation sequencing of centromeres, telomeres and rDNAs in Arabidopsis. Nat. Plants 9, 1439–1450 (2023). https://doi.org/10.1038/s41477-023-01498-7

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