Multiplexed Single-Cell DNA Methylation Workflow Enables Analysis of Blood Disorders

DNA methylation helps regulate gene activity and plays an important role in cell development and disease, including blood disorders and cancer. Conventional sequencing measures average methylation levels across large populations of cells, which can obscure differences between individual cells.

Single-cell sequencing can reveal this variation, but the small amount of DNA available from each cell makes sample preparation technically challenging. Researchers have now developed a standardized workflow for single-cell DNA methylation analysis.

Image: Workflow of Msc-RRBS library preparation and methylation analysis. (Photo courtesy of GU Hongcang)

Researchers at the Institute of Health and Medical Technology at the Hefei Institutes of Physical Science, Chinese Academy of Sciences (Hefei, China), developed a protocol for multiplexed single-cell reduced representation bisulfite sequencing. The workflow combines an improved laboratory procedure with SingleCellMethPipe, an automated data analysis tool, to support the detection and analysis of DNA methylation differences between individual cells.

The laboratory workflow simplifies several sample preparation steps. Cell preparation, DNA digestion, and other reactions are performed within the same microwell, reducing the need for repeated purification and helping minimize DNA loss. Molecular barcodes are used to label individual samples, allowing 24 single-cell samples to be pooled for downstream processing while reducing reagent use.

The team evaluated the method in 96 individual blood-forming stem and progenitor cells obtained from a healthy donor and a patient with myelodysplastic syndrome, a disorder that affects the production of healthy blood cells. Of these cells, 86 passed quality-control checks, corresponding to a success rate of 89.6%. The analysis identified differences in DNA methylation between cell types as well as between healthy and disease samples.

SingleCellMethPipe automates the processing of sequencing data, identification of methylation patterns, and assessment of data quality. The protocol was published in Nature Protocols. According to the researchers, the standardized approach provides a practical tool for investigating how cells develop and how changes in DNA methylation are associated with blood disorders and cancer.

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Hefei Institutes of Physical Science, Chinese Academy of Sciences