Cell & Bioscience (Jan 2023)

Single-cell DNA methylation sequencing by combinatorial indexing and enzymatic DNA methylation conversion

  • Zac Chatterton,
  • Praves Lamichhane,
  • Diba Ahmadi Rastegar,
  • Lauren Fitzpatrick,
  • Hélène Lebhar,
  • Christopher Marquis,
  • Glenda Halliday,
  • John B. Kwok

DOI
https://doi.org/10.1186/s13578-022-00938-9
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 11

Abstract

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Abstract Background DNA methylation is a critical molecular mark involved in cellular differentiation and cell-specific processes. Single-cell whole genome DNA methylation profiling methods hold great potential to resolve the DNA methylation profiles of individual cell-types. Here we present a method that couples single-cell combinatorial indexing (sci) with enzymatic conversion (sciEM) of unmethylated cytosines. Results The sciEM method facilitates DNA methylation profiling of single-cells that is highly correlated with single-cell bisulfite-based workflows (r2 > 0.99) whilst improving sequencing alignment rates, reducing adapter contamination and over-estimation of DNA methylation levels (CpG and non-CpG). As proof-of-concept we perform sciEM analysis of the temporal lobe, motor cortex, hippocampus and cerebellum of the human brain to resolve single-cell DNA methylation of all major cell-types. Conclusion To our knowledge sciEM represents the first non-bisulfite single-cell DNA methylation sequencing approach with single-base resolution.

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