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SIMPLE-seq to decode DNA methylation dynamics in single cells

Nature Reviews Genetics (2024)Cite this article

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Chemical modifications to the genome, including 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), orchestrate gene expression programmes in a cell type-specific manner. These modifications fine-tune how transcriptional factors bind to cis-regulatory elements. DNA 5mC is deposited by methyltransferases and eliminated by both replication-dependent and replication-independent active DNA demethylation processes. DNA 5hmC — generated by Ten-eleven translocation (TET) family proteins oxidizing 5mC — can be an intermediate product of the active DNA demethylation process or a stable epigenetic modification that possesses distinct regulatory functions1. Therefore, the ability to pinpoint 5mC and 5hmC simultaneously in the same cells is key to understanding the dynamics and regulatory functions of these epigenetic marks.

In dynamic biological processes such as development and differentiation, the epigenome is reprogrammed to turn on and off specific genes for intended functions. SIMPLE-seq measures the closely linked 5mC and 5hmC modifications and can serve as a powerful tool to identify genome regions or cells undergoing DNA methylation changes from ‘snap-shot’ single-cell datasets. For example, by analysing mouse embryonic stem cells during epigenetic transitions between naive and primed pluripotent states, SIMPLE-seq identified the potential ‘intermediate’ cell population by pinpointing cells with more disordered 5mC–5hmC relationships. Furthermore, by identifying 5hmC sites selectively generated from methylated regions, SIMPLE-seq can predict putative regulatory elements in the genome. This dual-omics approach also facilitates the characterization of methylation landscapes from complex tissue samples. For example, in differentiated cells with relatively stable DNA methylation, such as peripheral blood mononuclear cells, 5mC profiles revealed all major cell populations. In brain cells, which have higher 5hmC levels, using both modalities further improved cell type identification. Thus, SIMPLE-seq can be widely applied in various biological systems for analysis of DNA methylation dynamics.

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Fig. 1: Key features of SMILE-seq.

References

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Authors and Affiliations

  1. New York Genome Center, New York, NY, USA

    Dongsheng Bai & Chenxu Zhu

  2. Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA

    Chenxu Zhu

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  1. Dongsheng Bai
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  2. Chenxu Zhu
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Correspondence to Dongsheng Bai or Chenxu Zhu.

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Bai, D., Zhu, C. SIMPLE-seq to decode DNA methylation dynamics in single cells. Nat Rev Genet (2024). https://doi.org/10.1038/s41576-024-00729-7

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